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Wednesday, January 23
 

6:30pm

PRE-REGISTRATION & WELCOME DRINKS
Join us for networking drinks and a welcome note from Nina D'Amato from The San Francisco Department of Technology. This will be a great opportunity for you to collect your badge to avoid the rush on Thursday morning.

Speakers
avatar for Nina D'Amato, The San Francisco Department of Technology

Nina D'Amato, The San Francisco Department of Technology

Chief of Staff, The San Francisco Department of Technology
Nina D’Amato is the Chief of Staff at the San Francisco Department of Technology, The San Francisco Department of Technology is an enterprise information and technology services organization that supports approximately 35,000 employees and 56 departments of the City and County of... Read More →


Wednesday January 23, 2019 6:30pm - 8:00pm
Grand Ballroom Foyer Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA
 
Thursday, January 24
 

8:00am

REGISTRATION & LIGHT BREAKFAST
Thursday January 24, 2019 8:00am - 9:00am
Grand Ballroom Foyer Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:00am

Compère Welcome - Deep Learning Stage
Our compère for the Deep Learning Stage today will be Anirudh Koul, Head of AI & Research at Aira.

Speakers
avatar for Anirudh Koul, Aira

Anirudh Koul, Aira

Head of AI & Research, Aira
Anirudh Koul is the Head of AI & Research at Aira (Visual interpreter for the blind), and upcoming author of 'Practical Deep Learning for Cloud and Mobile'. Previously at Microsoft AI & Research, he founded Seeing AI App - often considered the defacto app in the blind and low vision... Read More →


Thursday January 24, 2019 9:00am - 9:15am
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:05am

Compère Welcome - AI Assistant Stage
Speakers
avatar for Ann Thyme-Gobbel, Sound United

Ann Thyme-Gobbel, Sound United

Voice & Natural Language UI / UX Researcher & Designer, Sound United
While doing a PhD in Cognitive Science and Linguistics at UCSD, Ann's interest in phonetics and NLP led to a dissertation using neural networks to model how speakers of a language form new words via paradigm patterning and token analogy. After that, Ann did R&D and product development... Read More →


Thursday January 24, 2019 9:05am - 9:15am
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:15am

Compère Welcome - Education & AI Stage
Speakers
avatar for Preetham Vishwanatha, Course Hero

Preetham Vishwanatha, Course Hero

VP of AI & Machine Learning, Course Hero
Preetham Vishwanatha is the Vice President of Artificial Intelligence and Machine Learning at Course Hero, an online learning platform where members can access over 20 million course-specific study resources contributed by a community of students and educators. Preetham joined Course... Read More →


Thursday January 24, 2019 9:15am - 9:25am
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:15am

Beyond Supervised Driving
Crowd-sourced steering does not sound as appealing as automated driving. We need to go beyond supervised learning for automated driving, including for computer vision problems seeing great progress with strong supervision today. First, we will motivate exciting scientific problems that have huge implications in the research and development of long-term large-scale autonomous robots, such as unsupervised domain adaptation, self-supervised learning, and robustness to edge cases. Second, we will talk about the robotics system perspective, especially end-to-end vs modular design and human-robot interaction. Finally, we will describe some of TRI's related research directions, especially around world-scale cloud robotics. In particular, we will discuss recent related results obtained in the ML team at TRI on state-of-the-art methods for self-supervised depth and pose prediction from monocular imagery, end-to-end panoptic segmentation, and large scale distributed deep learning on GPUs in the cloud.

Speakers
avatar for Adrien Gaidon, Toyota Research Institute

Adrien Gaidon, Toyota Research Institute

Machine Learning Lead & Snr. Research Scientist, Toyota Research Institute
Adrien Gaidon is the Manager of the Machine Learning team and a Senior Research Scientist at the Toyota Research Institute (TRI) in Los Altos, CA, USA, working on open problems in world-scale learning for autonomous driving. He received his PhD from Microsoft Research - Inria Paris... Read More →


Thursday January 24, 2019 9:15am - 9:35am
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:15am

Past, Present, and Future of Conversational AI
Conversational AI has always been the holy grail task for many scientists since the last several decades. Yet we observe tremendous advances from the early spoken language understanding systems used for call routing in 80s to modern personal assistants. In this talk, I will review the origins of conversational AI giving examples from pioneering systems, then present an overview of modern industrial and academic goal-oriented conversational systems, showing directions in our quest to building ultimate AI machines talking to humans.

Speakers
avatar for Gokhan Tur, Uber AI Labs

Gokhan Tur, Uber AI Labs

Director of Conversational AI, Uber AI Labs
Dr. Gokhan Tur is a leading artificial intelligence expert on human/machine conversational language understanding systems. He co-authored more than 150 papers published in journals or books and presented at conferences. He is the editor of the book entitled "Spoken Language Understanding... Read More →


Thursday January 24, 2019 9:15am - 9:40am
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:25am

Rising Star Feature: Disrupting Education with ML
Education has remained stagnant over the past century while technology has grown exponentially. One of the biggest problems with education today, is creating a curriculum that keeps up with innovation. Machine Learning can begin to solve this by autonomously generating curriculum for virtually any topic.

Speakers
avatar for Jerry Qu, The Knowledge Society (TKS)

Jerry Qu, The Knowledge Society (TKS)

Innovator, The Knowledge Society (TKS)
Jerry Qu is a Machine Learning (ML) developer who strives to solve real-world problems with exponential technologies. At 17 years old, Jerry has built numerous ML solutions, from an app that enables the visually impaired to better understand their world, to simulating self driving... Read More →


Thursday January 24, 2019 9:25am - 9:45am
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:35am

Object-oriented Perception and Control
Why are infants better at sensory motor tasks than our current AI systems? We are born with learning mechanisms to map our sensory experience into objects and abstractions over them. My talk will present unsupervised approaches integrating deep/reinforcement learning and probabilistic programming, to learn about objects and goal-directed control grounded in them. I will give demonstrations in a few domains including video understanding, game playing and robotics.

Speakers
avatar for Tejas Kulkarni, DeepMind

Tejas Kulkarni, DeepMind

Research Scientist, DeepMind
I am a Research Scientist at Google DeepMind. Previously, I was a PhD student at MIT under the supervision of Joshua Tenenbaum. I am primarily interested in understanding how the mind works. My current research goal is to build learning algorithms that acquire grounded common-sense... Read More →


Thursday January 24, 2019 9:35am - 10:00am
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:40am

Why Aren't Our AI Assistants Smarter?
Do our current crop of AI Assistants really use AI? If not, are they still useful? We'll look at the current state of AI Assistants, the challenges of building them, and speculate on what the future might bring.

Speakers
avatar for Cathy Pearl, Google

Cathy Pearl, Google

Head of Conversation Design Outreach, Google
Cathy Pearl is Head of Conversation Design Outreach at Google, and the author of the O'Reilly book, "Designing Voice User Interfaces". She's been designing and creating Voice User Interfaces (VUIs) for nearly 20 years and is passionate about helping everyone make the best conversational... Read More →


Thursday January 24, 2019 9:40am - 10:05am
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:45am

Rising Star Feature: Can We Learn to Learn
A key challenge in the current state of machine intelligence is its inability to generalize and adapt to new tasks. Humans are able to adapt intelligently because of our fundamental brain structure that learns how to learn. The idea of teaching machines to learn how to learn, known as meta-learning, has been shown to be a promising approach in enabling agents to adapt to new tasks. In this talk, Bonnie will present the results of meta reinforcement learning applied to both research and application domains, as well as the development and the frontiers of this approach.

Speakers
avatar for Bonnie Li, The Knowledge Society (TKS)

Bonnie Li, The Knowledge Society (TKS)

Research Intern & Machine Learning Developer, The Knowledge Society (TKS)
Bonnie Li is a Machine Learning researcher who is passionate about pushing the current boundaries of the field. At 17 year old, Bonnie is working on fundamental research in Reinforcement Learning at Mila under Yoshua Bengio. Bonnie holds a Deep Reinforcement Learning nanodegree from... Read More →


Thursday January 24, 2019 9:45am - 10:05am
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

10:00am

Adversarial Machine Learning
Most machine learning algorithms are based on optimization: given a cost function, the algorithm adapts the parameters to reduce the cost. Adversarial machine learning is instead based on game theory: multiple "players" compete to each reduce their own cost, often at the expense of other players. In this talk I show how adversarial machine learning is related to many active machine learning research areas.

Speakers
avatar for Ian Goodfellow, Google Brain

Ian Goodfellow, Google Brain

Staff Research Scientist, Google Brain
Ian Goodfellow is a Staff Research Scientist at Google Brain. He is the lead author of the MIT Press textbook Deep Learning. In addition to generative models, he also studies security and privacy for machine learning. He has contributed to open source libraries including TensorFlow... Read More →


Thursday January 24, 2019 10:00am - 10:25am
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

10:05am

Rising Star Feature: Transforming Civilization With Quantum Computing
Speakers
avatar for Tommy Moffat , The Knowledge Society (TKS)

Tommy Moffat , The Knowledge Society (TKS)

Innovator, The Knowledge Society (TKS)
Tommy is a 17-year-old working on applying quantum computing and deep learning to difficult problems like drug discovery and materials design. Tommy has been focusing specifically on how the powerful ability to manipulate quantum mechanics for computation will disrupt and evolve DL... Read More →


Thursday January 24, 2019 10:05am - 10:25am
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

10:05am

COFFEE BREAK 
Thursday January 24, 2019 10:05am - 11:05am
Grand Ballroom Foyer Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

10:10am

Compère Welcome - Industry Applications Stage
Speakers
avatar for Mike Del Balso

Mike Del Balso

Founding Product Manager, Uber's ML Platform, Michelangelo
Mike Del Balso is the founding product manager behind Uber's Machine Learning Platform, Michelangelo. His team built Uber's core ML infrastructure and scaled ML across the company from a first few use cases in 2015 to over 100 production ML applications today that span various domains... Read More →


Thursday January 24, 2019 10:10am - 10:20am
Pacific I-K Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

10:20am

GE Power Business & Digital Transformation
Speakers
avatar for Vivek Thakral, GE

Vivek Thakral, GE

Director, Artificial Intelligence, GE
Digital Technology leadership program and MBA graduate with over 16 years of experience. Driving productivity benefits across Finance, Supply Chain, Commercial Operations, and Human Resource Operations by executing strategic programs, improving processes, and deploying artificial... Read More →


Thursday January 24, 2019 10:20am - 10:45am
Pacific I-K Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

10:45am

Breaking Through Challenges in Industry Series: Using Deep Learning to Make Smarter Decisions for Retail Operations - Walmart Case Study
Pricing, assortment selection, space utilization and replenishment are some of the core tasks that are key to success of profitable store operations. In this talk, we present how the machine learning team for Walmart stores is making use of recent advances in machine learning to automate some of these store operations.

Speakers
avatar for Prakhar Mehrotra, Walmart Labs

Prakhar Mehrotra, Walmart Labs

Senior Director of Machine Learning, Walmart Labs
Prakhar Mehrotra currently is Senior Director of Machine Learning for Retail Data Science at Walmart Labs, based out of Sunnyvale CA. He overseas research and development of pricing, assortment, replenishment and planning algorithms to help merchants take smarter decisions. Prior... Read More →


Thursday January 24, 2019 10:45am - 11:15am
Pacific I-K Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:00am

Dialog Management with a Software 2.0 Stack
Multi-turn conversations with users are hard. Writing code to handle each dialog path is easy to get started with but does not scale to all variations. Purely data-driven approaches are tough to get off the ground. How do we cross this chasm? This talk will present an approach to reliably scale to the long tail of conversational interactions using a combination of software development and machine learning.

Thursday January 24, 2019 11:00am - 11:20am
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:00am

Human Insight Project – 21st Century Education System
Objective measures support that there has never been a better time to be alive, yet equally objective metrics show dissatisfaction levels rising at an alarming rate known as the Paradox of Progress. The rapid pace of technological development means multiple paradigm shifts now occur in a lifetime, shifts that previously occurred once a millennium. Without the proper tools to address our individuality and existence, the paradox will break most coping mechanisms. The challenge is providing personalized assistance for each human to build resilience through rapidly increasing rate of change. With the coming AI shift, it becomes possible to provide timely omnipresent assistance to aid in decision-making. Care should be taken to avoid the dangers of blindly following the data or delegating personal responsibility to an outside agency. Data gathering, and making sense of it, should fall within the human agency. The seed for modern AI is also just data, it just learns to retain the examples it’s been shown. Human Insight Project is the basis of the true 21st-century education system where personalized context by AI can aid every human to navigate through the maps of our outer and inner life terrains.

Speakers
avatar for Kelvin Lwin, NVIDIA Deep Learning Institute

Kelvin Lwin, NVIDIA Deep Learning Institute

Senior Deep Learning Instructor, NVIDIA Deep Learning Institute
After spending nearly a decade at UC Berkeley, Kelvin decided to repay his debt to the public education system by helping build UC Merced. He spent seven years teaching 4,500 students across 55 classes, while redesigning the undergraduate Computer Science curriculum. He is now busy... Read More →


Thursday January 24, 2019 11:00am - 11:25am
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:05am

Combining Planning and Learning
In order to build agents that can reason about the consequences of their actions and control the world, it is important to acquire rich priors that capture a notion of how to plan forward into the future. Imagining the consequences in raw pixels is unlikely to scale well for large environments and also has no incentive to ignore aspects of the raw sensory stream that are irrelevant to the task at hand. I will talk about ways to circumvent this issue by introducing explicit differentiable planning inside the policy's computation graph and show that the learned priors are generalizable across different robot morphologies and can capture a generic notion of the underlying task in its representation.

Speakers
avatar for Aravind Srinivas, UC Berkeley

Aravind Srinivas, UC Berkeley

Ph.D. Student, UC Berkeley
Aravind is a second year Ph.D. student at UC Berkeley advised by Prof. Pieter Abbeel and is part of the Berkeley AI Research lab. He has spent time at OpenAI and is interested in learning representations from raw sensory data for general intelligence.


Thursday January 24, 2019 11:05am - 11:25am
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:15am

Breaking Through Challenges in Industry Series: OCR at Scale at Dropbox
There are many billions of images in Dropbox.  About 15% of them are photos of documents -- receipts, business cards, contracts, etc. -- with text content that is hidden from our search index.  To allow our users to search for these "documents," Dropbox built an OCR system.  In this talk I'll describe Dropbox's OCR project from its initial, small-scale deployment of a third-party library, through development and large-scale deployment of a homegrown solution using deep networks, focussing on the performance and scaling problems we encountered and solved along the way.

Speakers
avatar for Thomas Berg, Dropbox

Thomas Berg, Dropbox

Machine Learning Engineer, Dropbox
Thomas Berg is a Machine Learning Engineer at Dropbox, where he's worked on image classification, OCR, and user activity prediction. He has a PhD from Columbia University, where he worked on face recognition and fine-grained image classification in Peter Belhumeur's lab.


Thursday January 24, 2019 11:15am - 11:45am
Pacific I-K Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:20am

Machine Learning for Continuous Improvement
The Autodesk Virtual Agent, AVA, plays a critical role in the Autodesk Digital Help & Experience organization’s goal of providing a seamless blend of digital and human support across all Autodesk help properties. In this talk, Nikhil will share how their virtual assistant has evolved since going live last year. He will touch upon AVA's beginnings in the customer support domain, improvements using customer interaction data, how to develop conversational analytics, integrating machine learning work from other teams and finally modularization strategy.

Speakers
avatar for Nikhil Mane, Autodesk

Nikhil Mane, Autodesk

Engineer - Conversation AI, Autodesk
Nikhil Mane is a Conversation Engineer at Autodesk developing technology with the goal of making it easy for customers to seek support. He works on developing software for delivering conversational solutions, exploring new technologies for expanding the team's capabilities and defining... Read More →


Thursday January 24, 2019 11:20am - 11:40am
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:25am

Compère Welcome - Connect Stage
Speakers
avatar for Thomas Simonini, Deep Reinforcement Learning Course

Thomas Simonini, Deep Reinforcement Learning Course

Deep Learning Engineer, Deep Reinforcement Learning Course
Thomas Simonini is a Deep Learning Engineer specialized in Deep Reinforcement Learning. After a Bachelor Degree of French Law and Political Sciences in 2016, he decided to change career by learning AI. He graduated from Deep Learning Foundations and Artificial Intelligence Nanodegree... Read More →


Thursday January 24, 2019 11:25am - 11:35am
Pacific G-H Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:25am

Go-Explore: A New Type of Algorithm for Hard-exploration Problems
A grand challenge in reinforcement learning is producing intelligent exploration, especially when rewards are sparse or deceptive. I will present Go-Explore, a new algorithm for such ‘hard exploration problems.’ Go-Explore dramatically improves the state of the art on benchmark hard-exploration problems, enabling previously unsolvable problems to be solved. I will explain the algorithm and the new research directions it opens up. I will also explain why we believe it will enable progress on previously unsolvable hard-exploration problems in a variety of domains, especially the many that harness a simulator during training (e.g. robotics). More information can be found at https://eng.uber.com/go-explore

Speakers
avatar for Jeff Clune, Uber AI Labs

Jeff Clune, Uber AI Labs

Senior Research Scientist & Founding Member, Uber AI Labs
Jeff Clune is the Loy and Edith Harris Associate Professor in Computer Science at the University of Wyoming and a Senior Research Scientist and founding member of Uber AI Labs. He focuses on robotics, reinforcement learning, and training neural networks either via deep learning or... Read More →


Thursday January 24, 2019 11:25am - 11:45am
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:25am

Panel: Changemakers in AI - Young People Using AI for Good
AI has the potential to impact daily life in countless ways. As we talk about the future of this disruptive and transformative technology, it is critical to include the voice of today's youth who represent society's future. The young people of today will be faced with the impact of the decisions we make about AI, and so having their perspectives, ideas, concerns and solutions is critical for creating responsible and beneficial AI. Join 3 high school-age AI4ALL alumni for a discussion moderated by AI4ALL’s CEO, Tess Posner, about what drew them to AI, how they’re using AI in their own work now, and what they anticipate for the future.

Speakers
avatar for Tess Posner, AI4ALL

Tess Posner, AI4ALL

CEO, AI4ALL
Tess Posner is a social entrepreneur focused on increasing equity and inclusion in the tech economy. As CEO of AI4ALL, she is working to make artificial intelligence more diverse and inclusive and to ensure that AI is developed responsibly. Before joining AI4ALL, she was Managing... Read More →
avatar for Ria Doshi, Stanford AI4ALL

Ria Doshi, Stanford AI4ALL

High School Student, Stanford AI4ALL
Ria Doshi is a high school sophomore in California who is passionate about computer science. Ever since she attended a coding class at a library years ago, she became fascinated with the multi-faceted world of programming. Motivated by how she could use technology to help better the... Read More →
avatar for Jocelin Su, Stanford AI4ALL

Jocelin Su, Stanford AI4ALL

High School Student, Stanford AI4ALL
Jocelin Su is a high school student in San Jose, California who is interested in studying math and CS. She currently conducts research in computational genetics at Stanford University, and was a participant of the national Math Olympiad Summer Program. After attending Stanford AI4ALL... Read More →
avatar for Eshika Saxena, Stanford AI4ALL

Eshika Saxena, Stanford AI4ALL

High School Student, Stanford AI4ALL
Eshika Saxena is a high school senior in Bellevue, Washington. She attended Stanford AI4ALL in 2016. As an AI4ALL grant recipient, Eshika has organized many workshops to introduce kids in her community to programming and AI. In her high school, Eshika is the founder and president... Read More →


Thursday January 24, 2019 11:25am - 12:25pm
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:35am

A Hands-on Introduction to Pytorch, Using Text Classification
PyTorch is a popular framework for deep learning. This is a 45-minute workshop for PyTorch beginners. We will walk you through the basics of the PyTorch library, using a text classification application as an example. During the workshop, we will demonstrate a Jupyter notebook, which will allow participants to directly experiment with the code.

Prerequisites: The examples will run in Python, so knowing the basics of Python syntax is recommended. Bring a computer with Anaconda (Python 3) and Pytorch installed.

Speakers
avatar for Yannet Interian, University of San Francisco

Yannet Interian, University of San Francisco

Assistant Professor, University of San Francisco
 Yannet is an Assistant Professor at the University of San Francisco, in the Masters in Data Science program. Her research involves applying machine learning and deep learning to medical data. She holds a Ph.D. in Applied Mathematics from Cornell University. She worked for five years... Read More →


Thursday January 24, 2019 11:35am - 12:20pm
Pacific G-H Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:40am

Conversational AI @ Facebook
Conversational AI is becoming a key part of various products at Facebook, including Portal, Messenger suggestions, Marketplace, recommendations, to name just a few. Being able to ship delightful conversational experiences means we also need to invest in solving hard research problems in areas such as language understanding, dialog management and language generation. In this talk, I will talk about some of the current work we're doing in these areas, as all as work we've done with Pytorch in order to enable our research scientists to quickly prototype and deploy advanced NLP models.

Speakers
avatar for Rushin Shah, Facebook

Rushin Shah, Facebook

Senior Manager, Facebook Conversational AI
Rushin Shah is a senior manager leading the natural language understanding group at Facebook Conversational AI. Previously, he was at Siri at Apple for 5 years, where he built and headed the natural language understanding group. He also worked at the query understanding group at Yahoo... Read More →


Thursday January 24, 2019 11:40am - 12:00pm
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:45am

Deep Learning for Robotics and Robotics for Deep Learning
Large-scale, data-driven techniques for robotic learning have imbued robots with unprecedented capabilities in recent years. However, a long-standing challenge for goal-directed learning on robots is the problem of supervision: how do we know if the robot actually achieved some goal, such as picking up the correct object? I present recent work in which we use robotic interaction to provide free supervision signals for deep representation learning, and reuse those very same representations to learn instance grasping. This synergy leads to interpretable visual representation learning and useful grasping skills, freeing us from ever having to label any data.

Speakers
avatar for Eric Jang, Google Brain Robotics

Eric Jang, Google Brain Robotics

Research Engineer , Google Brain Robotics
Eric is a research engineer on the Google Brain team, working on robotic grasping and manipulation. He is interested in meta-learning for robotics, deep generative models, and Artificial Life. He received his M.Sc. in CS and Bachelors in Math/CS at Brown University in 2016.


Thursday January 24, 2019 11:45am - 12:05pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:45am

Breaking Through Challenges in Industry Series: Challenges in Recommendation Systems at Twitter Scale
Twitter has amazing and unique content that is generated at an enormous velocity internationally. A constant challenge is how to find the relevant content for users so that they can engage in the conversation. Approaches span collaborative filtering and content based recommendation systems for different use cases. This talk gives insight into unique recommendation system challenges at Twitter’s scale and what makes this a fun and challenging task.

Speakers
avatar for Ashish Bansal, Twitter

Ashish Bansal, Twitter

Senior Engineering Manager, Twitter
Ashish manages the Explore and Trends engineering teams at Twitter. He focusses on building scalable ML & recommendation systems. Prior to that, he was a Senior Director of Data Science at Capital One. He used AI/ML to generate insights from vast amounts of data and build interesting... Read More →


Thursday January 24, 2019 11:45am - 12:15pm
Pacific I-K Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

12:00pm

Building Customer Service Virtual Agents Faster and Smarter by Analyzing Human-to-human Interactions with ML
Innovative companies are modernizing their contact centers by adopting AI-powered virtual agents to improve customer satisfaction by providing helpful service 24/7, globally. But for brands building a virtual agent, the critical questions are:
  • What are the best use cases for the virtual agent?
  • What questions do customers ask and how do they phrase them (including follow-ups)?
  • How to ensure virtual agents responds helpfully?
  • What is the optimal time to do a hand-off to a live agent?
Particularly for companies with large customer service operations, answering the questions above manually is slow, based on guesswork, and creates gaps that put customer satisfaction at risk. In this session, attendees will learn how machine learning techniques can unlock actionable insights from human-to-human interactions in contact center chat and call logs -- making development much faster, and virtual agents much smarter.

Speakers
avatar for Ofer Ronen, Chatbase

Ofer Ronen, Chatbase

General Manager, Chatbase
Ofer Ronen is the general manager of Chatbase, a conversational analytics service brought to you by Area 120 (a products incubator operated by Google). Previously, he was CEO of Pulse.io, an app performance monitoring service (acquired by Google), and CEO of ad network Sendori (acquired... Read More →



Thursday January 24, 2019 12:00pm - 12:25pm
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

12:05pm

Recent Advances From OpenAI
Speakers
avatar for Ilya Sutskever, OpenAI

Ilya Sutskever, OpenAI

Co-Founder & Chief Scientist, OpenAI
Ilya Sutskever received his PhD in 2012 from the University of Toronto working with Geoffrey Hinton. After completing his PhD, he cofounded DNNResearch with Geoffrey Hinton and Alex Krizhevsky which was acquired by Google. He is interested in all aspects of neural networks and their... Read More →


Thursday January 24, 2019 12:05pm - 12:30pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

12:15pm

Breaking Through Challenges in Industry Closing Panel
Speakers
avatar for Thomas Berg, Dropbox

Thomas Berg, Dropbox

Machine Learning Engineer, Dropbox
Thomas Berg is a Machine Learning Engineer at Dropbox, where he's worked on image classification, OCR, and user activity prediction. He has a PhD from Columbia University, where he worked on face recognition and fine-grained image classification in Peter Belhumeur's lab.
avatar for Prakhar Mehrotra, Walmart Labs

Prakhar Mehrotra, Walmart Labs

Senior Director of Machine Learning, Walmart Labs
Prakhar Mehrotra currently is Senior Director of Machine Learning for Retail Data Science at Walmart Labs, based out of Sunnyvale CA. He overseas research and development of pricing, assortment, replenishment and planning algorithms to help merchants take smarter decisions. Prior... Read More →
avatar for Ashish Bansal, Twitter

Ashish Bansal, Twitter

Senior Engineering Manager, Twitter
Ashish manages the Explore and Trends engineering teams at Twitter. He focusses on building scalable ML & recommendation systems. Prior to that, he was a Senior Director of Data Science at Capital One. He used AI/ML to generate insights from vast amounts of data and build interesting... Read More →


Thursday January 24, 2019 12:15pm - 12:45pm
Pacific I-K Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

12:20pm

LUNCH
Thursday January 24, 2019 12:20pm - 1:20pm
Atrium Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:20pm

Compère Welcome - Environment & Sustainability Stage
Speakers
avatar for Mark Crowley, University of Waterloo

Mark Crowley, University of Waterloo

Assistant Professor, University of Waterloo
Mark Crowley is an Assistant Professor in the Department of Electrical and Computer Engineering and the Waterloo Artificial Intelligence Institute at the University of Waterloo. He did a postdoc at Oregon State University with Tom Dietterich's machine learning group researching computational... Read More →


Thursday January 24, 2019 1:20pm - 1:30pm
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:20pm

Artificial Training Data: How to Automate Your Bot Training
One of the main problems with the current generation of chatbots is that they require large amounts of training data. If you want your chatbot to recognize a specific intent, you need to provide it with a large number of sentences that express that intent. Until now, these large training corpora had to be generated manually, with one or more people writing many different sentences for each intent, vertical and language that needed to be recognized in your chatbot. Bitext Artificial Training Data technology (also called Natural Language Generation) automatically generates many different sentences with the same meaning as the original one, in order to automate the most resource-intensive part of the bot creation process.

Speakers
avatar for Antonio Valderrábanos, Bitext

Antonio Valderrábanos, Bitext

Founder & CEO, Bitext
Antonio has a long experience on how to use Deep Linguistic Analysis to solve business problems in the area of text analysis.His current focus is on how to exploit linguistic knowledge to improve machine learning and AI engines, to make them smarter and easier to train. Chatbots are... Read More →


Thursday January 24, 2019 1:20pm - 1:45pm
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:20pm

Curiosity Driven Learning, a promising strategy in Deep Reinforcement Learning
Curiosity Driven Learning is one of the most exciting and promising strategy in deep reinforcement learning: we create agents that are able to produce rewards and learn from them. In this workshop, you’ll learn what is curiosity, how it works, and understand the process of how an agent generates this intrinsic reward using a trained agent in a video game environment. By the end of this workshop, you'll be able to understand how curiosity driven learning agents work and the main elements needed to implement them.

Speakers
avatar for Thomas Simonini, Deep Reinforcement Learning Course

Thomas Simonini, Deep Reinforcement Learning Course

Deep Learning Engineer, Deep Reinforcement Learning Course
Thomas Simonini is a Deep Learning Engineer specialized in Deep Reinforcement Learning. After a Bachelor Degree of French Law and Political Sciences in 2016, he decided to change career by learning AI. He graduated from Deep Learning Foundations and Artificial Intelligence Nanodegree... Read More →


Thursday January 24, 2019 1:20pm - 2:00pm
Pacific G-H Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:30pm

Computer Vision and Deep Learning for Coral Ecology
While coral reefs occupy less than 0.2% of the ocean bottom, they harbor 25% of the marine life and protect shorelines occupied by 200 million people. Globally, coral reefs are in rapid decline, and scientists, reef managers, and policy makers need accurate data about the state (species, coverage) and change of individual reefs. Photographic surveys are the primary source of raw data, and it is becoming cheaper and easier to acquire massive quantities of digital images with autonomous robotic underwater vehicles. Yet even for surveys conducted by scuba divers, manual image analysis is error prone and has become a time consuming and costly bottleneck.  Our work using computer vision and machine learning is breaking this bottleneck. 
 
Research from the UCSD Computer Vision for Coral Ecology Project has lead to new cameras, algorithms, software, and services. We have developed a series of methods for automatic annotation of benthic images and created CoralNet (coralnet.ucsd.edu) as a public, open source, hosted tool for scientists to upload their photo surveys and perform annotation using deep nets trained on their data. Through a comparative study published on PLOS ONE, CoralNet is as accurate at estimating coral coverage as human experts. To date CoralNet is being used by a thousand scientists who have uploaded over 750,000 images with over 27 million expert annotations. To increase accuracy further, we looked for stronger signals for classifying corals.  Using our wide field fluorescence imaging (Fluoris) camera, the error rate of deep nets applied to registered 5-channel RGB-Fluoro images decreased by 22%.

Speakers
avatar for David Kriegman, UCSD

David Kriegman, UCSD

Professor of Computer Science & Engineering, UCSD
David Kriegman is a Professor of Computer Science & Engineering at the University of California, San Diego. His core research is in computer vision and machine learning, which he has applied to face recognition, robotics, coral ecology, medical imaging, microscopy, and computer graphics... Read More →


Thursday January 24, 2019 1:30pm - 1:50pm
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:30pm

Probabilistic Deep Ensembles for Predictive Uncertainty Estimation
Quantifying predictive uncertainty in deep learning is a challenging and yet unsolved problem. Predictive uncertainty estimates are important to know when to trust the model's predictions, especially in real-word applications, where the train and test distributions can be very different. Bayesian neural networks are currently the state-of-the-art for estimating predictive uncertainty; however these require significant modifications to the training procedure and can be computationally expensive. I'll talk about our recent work on "Probabilistic Deep Ensembles", an alternative to Bayesian neural networks, that is simple to implement, readily parallelizable, requires very little hyperparameter tuning, and yields high quality predictive uncertainty estimates. I'll discuss experiments that show that our method produces well-calibrated uncertainty estimates and is robust to dataset shift, and also highlight how we used this method in a challenging healthcare problem.

Speakers
avatar for Balaji Lakshminarayanan, DeepMind

Balaji Lakshminarayanan, DeepMind

Senior Research Scientist, DeepMind
Balaji Lakshminarayanan is a senior research scientist at Google DeepMind. He's interested in scalable probabilistic machine learning and its applications. Most recently, his research has focused on probabilistic deep learning, specifically, uncertainty estimation and deep generative... Read More →


Thursday January 24, 2019 1:30pm - 1:55pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:35pm

Systems for Feedback and Novelty in Deep Learning: A Case Study From Coursera
As industries and occupations are being transformed by AI and other emerging technologies, there is a growing need to retrain existing workers and ensure those entering the labor force have the requisite skills to succeed in the new job market. At Coursera our mission is to provide everyone, anywhere access to the high quality education that will become necessary for this. Scaling in course help that assists learners through difficult course material, keeping them motivated, will require high levels of personalization to make the interventions relevant and timely. Through our work we have created automated feedback loops that utilize deep learning to serve the optimal help messages in our courses at the right time to drive positive learner outcomes. These learnings are relevant to anyone looking to add product value through automated systems powered by deep learning.

Speakers
avatar for Vinod Bakthavachalam, Coursera

Vinod Bakthavachalam, Coursera

Senior Data Scientist, Coursera
Vinod Bakthavachalam is a data scientist working with the Content Strategy and Enterprise teams where his work has recently focused on developing ways to measure the learning outcomes from taking Coursera classes, especially in the context of company sponsored training. Prior to Coursera... Read More →


Thursday January 24, 2019 1:35pm - 2:05pm
Pacific I-K Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:45pm

Adding Structure to Spoken Language Understanding
Typically spoken language understanding(SLU) systems factor the language understanding problem into intent classification and slot tagging.
This presents an inherent limitation for more complex linguistic phenomenon like coordination where the  user expresses multiple intents in a statement.
In this talk we present 2 ways in which we can add structure to SLU. First, we talk about incorporating an external parser to solve coordination if we want to extend a legacy system.
Second we pose SLU as a shallow semantic parsing problem which is also able to handle tasks like Question answering. We also talk about solving the data sparsity issue by doing transfer learning between domains and by using techniques like delexicalization and copy mechanism.

Speakers
avatar for Rahul Goel, Alexa AI

Rahul Goel, Alexa AI

Machine Learning Scientist, Alexa AI
Rahul Goel is a machine learning scientist at Alexa AI where he works on improving spoken language understanding and dialog systems. Many of his contributions are currently deployed in Alexa. His research interests include dialog systems, language understanding, deep learning, and... Read More →


Thursday January 24, 2019 1:45pm - 2:10pm
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:50pm

Oscar, AI for Zero Waste
Majority of global waste, especially from developed countries, can be recycled however only 2% actually remains clean enough to be processed by material recovery facilities. Intuitive has developed Oscar, an AI module that is designed to reduce contamination at the source of disposal and increase the amount of waste diverted away from landfills, oceans or third world countries. This engaging user-nudging AI has been trained using deep learning algorithms to enable accurate object detection for a large variety of waste items to enable smarter zero waste spaces.

Speakers
avatar for Hassan Murad, Intuitive AI

Hassan Murad, Intuitive AI

CEO & Co-Founder, Intuitive AI
Hassan Murad is the CEO & Co-Founder of Intuitive AI where they are developing AI to empower a zero waste world. He was driven by the world’s massive waste problem to begin creating solutions along with co-founder, Vivek Vyas, and divert waste away from landfills, oceans or incineration... Read More →


Thursday January 24, 2019 1:50pm - 2:10pm
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:55pm

Applying ML & NLP in Google Ads
Building and deploying machine-learning (ML) models at Google comes with interesting challenges. For example, some models have to handle massive amounts of training data, while some supervised tasks have insufficient amount of training labels. Or, even when the model quality is good enough for a product requirement, it may not meet other requirements (e.g., serving latency, memory footprint). In this talk we will discuss some of these challenges and share our experiences from deploying ML models for quality improvements in Search Ads products via some case studies. One particular case study I will discuss in detail is a recent paper where we use deep neural networks to understand ad performance and attribute it to particular parts of ad text. This is an interesting research problem in Natural Language Processing (NLP) -- we will outline our key results related to this problem, and discuss interesting areas of future research.

Speakers
avatar for Sugato Basu, Google

Sugato Basu, Google

Senior Staff Research Scientist/Tech Lead of AdsAI, Google
Dr. Sugato Basu is currently the Tech Lead of the AdsAI team in Google, which applies state-of-the-art machine learning (ML) and natural language processing (NLP) technology to challenging problems in Search Ads at Google. He joined Google in 2007 and has worked for more than a decade... Read More →


Thursday January 24, 2019 1:55pm - 2:20pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

2:00pm

Panel: Industry or Academia - Helping Students Decide What Next 
Speakers
avatar for Bonnie Li, The Knowledge Society (TKS)

Bonnie Li, The Knowledge Society (TKS)

Research Intern & Machine Learning Developer, The Knowledge Society (TKS)
Bonnie Li is a Machine Learning researcher who is passionate about pushing the current boundaries of the field. At 17 year old, Bonnie is working on fundamental research in Reinforcement Learning at Mila under Yoshua Bengio. Bonnie holds a Deep Reinforcement Learning nanodegree from... Read More →
avatar for Vivek Thakral, GE

Vivek Thakral, GE

Director, Artificial Intelligence, GE
Digital Technology leadership program and MBA graduate with over 16 years of experience. Driving productivity benefits across Finance, Supply Chain, Commercial Operations, and Human Resource Operations by executing strategic programs, improving processes, and deploying artificial... Read More →
avatar for Joshua Jones, QuantHub

Joshua Jones, QuantHub

Co-Founder, QuantHub
As the co-founder of QuantHub, Joshua Jones has 15+ years of experience recruiting top tier talent from schools like Harvard, Stanford, Princeton and Columbia, while building a global portfolio of big data clients, including companies like Southern Company, Toshiba, Samsung, and Chick-Fil-A.His... Read More →
avatar for Lubomir Bourdev, WaveOne

Lubomir Bourdev, WaveOne

Co-Founder & CEO, WaveOne
Lubomir Bourdev is a co-founder and the CEO of WaveOne, Inc., a startup focusing on video compression with deep learning. He is also a founding member of Facebook AI Research and he founded and led the Facebook AML Computer Vision team responsible for the image and video content recognition... Read More →


Thursday January 24, 2019 2:00pm - 2:30pm
Pacific G-H Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

2:05pm

Bringing Research And Production Together With PyTorch 1.0
Artificial intelligence is continuing to advance rapidly, with breakthroughs in areas from reinforcement learning to generative adversarial networks holding the potential to transform how we go about our day-to-day. Learn how PyTorch 1.0 enables you to take state-of-the-art research and deploy it quickly at scale in areas from autonomous vehicles to medical imaging. We'll deep dive on the latest updates to the PyTorch framework including TorchScript and the JIT compiler, deployment support, the C++ interface, and distributed training. We will also cover how PyTorch 1.0 is utilized at Facebook to power AI across a variety of products.

Speakers
avatar for Dmytro Dzhulgakov, Facebook

Dmytro Dzhulgakov, Facebook

AI Software Engineering Manager, Facebook
Dmytro Dzhulgakov is an Engineering Manager and Technical Lead in AI Infrastructure at Facebook. He currently leads the core development of PyTorch 1.0, an open source deep learning platform, and is one of the co-creators of ONNX, a joint initiative aimed at making AI development... Read More →


Thursday January 24, 2019 2:05pm - 2:45pm
Pacific I-K Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

2:10pm

Adaptation Through Learning:Using Machine Learning to Improve Forest Wildfire Management
Deep learning algorithms are being applied daily in ever more challenging domains, however in areas of huge societal importance such as ecology, sustainable resource management and environmental modelling, the analytical methods being used have not always caught up with the recent Deep Learning revolution. This is not surprising new methods are hard to master but also because these domains place very high demands on confidence and robustness that AI researchers rarely face with simpler validation domains. In this talk I will provide a window into this situation by looking at forest wildfire management as a case study of a rich domain where some work has been done but huge opportunities remain. Existing forest wildfire spread models are complex manual constructions that are struggling to adapt to changing climate as well as changing attitudes towards forests. What is needed are more adaptive models which fuse human experience, experimental data as well current satellite, aerial, weather and other data. Given the recent phase shift in the intensity of forest wildfires around the world, the urgency is increasing for more responsive predictive models and more powerful decision making tools. I will review the few machine learning approaches that have been applied to this important task and present some of our own work on using Deep Reinforcement Learning to learn fire spread prediction models directly from satellite imagery and simulations by treating fire as the agent that is choosing where to spread. This "learning of an agent-based model" approach could also apply to prediction and decision making for other instances of spatially spreading processes such as infectious disease and invasive species. Sustainability and environmental domains provide a great opportunity for the AI/ML community to step up and find solutions that will make a real difference to the lives of many people and the health of ecosystems.

Speakers
avatar for Mark Crowley, University of Waterloo

Mark Crowley, University of Waterloo

Assistant Professor, University of Waterloo
Mark Crowley is an Assistant Professor in the Department of Electrical and Computer Engineering and the Waterloo Artificial Intelligence Institute at the University of Waterloo. He did a postdoc at Oregon State University with Tom Dietterich's machine learning group researching computational... Read More →


Thursday January 24, 2019 2:10pm - 2:30pm
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

2:10pm

Chatbots: The (Long) Tail Wags the Dog
Give a customer a chatbot meant to help them track packages, and they’ll ask it to change their delivery address, send them proof of delivery and cook them dinner. In general, customers expect chatbots to handle a large quantity of very specific tasks, and each task requires custom, time consuming, hard coded API integrations. That’s not scalable. In this talk, I’ll go over the novel AI and UX techniques that Eloquent Labs uses to tackle this problem -- and how we’re using our approach to make chatbots work in customer facing environments.

Speakers
avatar for Arun Chaganty, Eloquent Labs

Arun Chaganty, Eloquent Labs

Head of Artificial Intelligence, Eloquent Labs
Arun Chaganty is the Head of AI at Eloquent Labs and recently graduated with a PhD from the Stanford NLP group. He is interested in making it easier for people to scale up the information they are able to access, process and comprehend through robust machine learning systems with... Read More →


Thursday January 24, 2019 2:10pm - 2:35pm
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

2:20pm

On-device Neural Networks for Natural Language Processing
Deep neural networks reach state-of-the-art performance for wide range of Natural Language Processing, Computer Vision and Speech applications. Yet, one of the biggest challenges is running these complex networks on devices with tiny memory footprint and low computational capacity such as mobile phones, smart watches and Internet of Things. In this talk, I will introduce novel on-device Self-Governing Neural Networks (SGNNs), which learn compact projection vectors with local sensitive hashing. The key advantage of SGNNs over existing work is that they surmount the need for pre-trained word embeddings and complex networks with huge parameters. I will showcase results from extensive evaluations on wide range of natural language tasks such as dialog act classification and user intent prediction. Our findings show that SGNNs are effective at capturing low-dimensional semantic text representations, while maintaining high accuracy and improving over state-of-the-art results.

Speakers
avatar for Zornitsa Kozareva, Google

Zornitsa Kozareva, Google

Manager, Google
Dr. Zornitsa Kozareva is a Manager at Google, leading and managing the Natural Language Understanding group and efforts in Google Apps Intelligence. Prior to that, Dr. Kozareva was Manager of Amazon’s AWS Deep Learning group that built and launched the Natural Language Processing... Read More →


Thursday January 24, 2019 2:20pm - 2:40pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

2:30pm

Opportunities and Challenges: AI for the Environment & Sustainability
Speakers come together in this panel discussion to share their thoughts on the opportunities and limitations impacting the future of their progress in solving challenges for the planet.

Speakers
avatar for Hassan Murad, Intuitive AI

Hassan Murad, Intuitive AI

CEO & Co-Founder, Intuitive AI
Hassan Murad is the CEO & Co-Founder of Intuitive AI where they are developing AI to empower a zero waste world. He was driven by the world’s massive waste problem to begin creating solutions along with co-founder, Vivek Vyas, and divert waste away from landfills, oceans or incineration... Read More →
avatar for David Kriegman, UCSD

David Kriegman, UCSD

Professor of Computer Science & Engineering, UCSD
David Kriegman is a Professor of Computer Science & Engineering at the University of California, San Diego. His core research is in computer vision and machine learning, which he has applied to face recognition, robotics, coral ecology, medical imaging, microscopy, and computer graphics... Read More →
avatar for Mark Crowley, University of Waterloo

Mark Crowley, University of Waterloo

Assistant Professor, University of Waterloo
Mark Crowley is an Assistant Professor in the Department of Electrical and Computer Engineering and the Waterloo Artificial Intelligence Institute at the University of Waterloo. He did a postdoc at Oregon State University with Tom Dietterich's machine learning group researching computational... Read More →


Thursday January 24, 2019 2:30pm - 3:00pm
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

2:30pm

Panel: How do we Encourage Women to Join Careers in STEM and What are the Next Steps? 
Speakers
avatar for Dora Jambor

Dora Jambor

Machine Learning Engineer, Shopify
Dora Jambor is a machine learning engineer at Shopify where she builds large-scale recommender systems for personalization and search problems to help Shopify merchants run their businesses. She is passionate about machine learning, and has worked on a number of research projects... Read More →
avatar for Alicia Kavelaars, OffWorld

Alicia Kavelaars, OffWorld

Co-Founder and CTO, OffWorld
Alicia is Co-Founder and Chief Technology Officer at OffWorld Inc. She brings over 15 years of experience in the aerospace industry developing and successfully launching systems for NASA, NOAA and the Telecommunications industry. In 2015, Alicia made the jump to New Space to work... Read More →
avatar for Sonja Reid, OMGitsfirefoxx

Sonja Reid, OMGitsfirefoxx

Independent, OMGitsfirefoxx
Sonja Reid is a gaming and tech personality - with an honor in Forbes 30 under 30, as well as a Guinness World Record title for most followed female streamer. An interest in AI, VR & gaming technologies has lead her to host and interview at conventions such as SXSW, E3, IDF, CES... Read More →
avatar for Maithra Raghu, Google Brain/Cornell University

Maithra Raghu, Google Brain/Cornell University

Research Scientist, Google Brain/Cornell University
Maithra Raghu is a PhD Candidate in Computer Science at Cornell University, and a Research Scientist at Google Brain. Her research interests are in developing principled tools to empirically study the representational properties of deep neural networks, and apply these insights to... Read More →
avatar for Catherine Lu, Spike Ventures

Catherine Lu, Spike Ventures

Principal, Spike Ventures
Catherine is an entrepreneur-turned-investor. She is currently a Principal at Spike Ventures, a VC firm that invests in Stanford alum-led companies. Previously, she was Director of Product at NEA-backed Datavisor, an enterprise company offering an unsupervised machine learning fraud... Read More →


Thursday January 24, 2019 2:30pm - 3:20pm
Pacific G-H Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

2:35pm

Open-Ended Challenges in Dialog Systems
Dialog Systems have come a long way, especially with advancements brought by assistants such as Alexa. However, there are several open-ended challenges which makes it hard to build fully Conversational Dialog Systems. In this talk, I will go over some of these open-ended challenges and discuss how to address them.

Speakers
avatar for Chandra Khatri, Uber AI Labs

Chandra Khatri, Uber AI Labs

Senior AI Scientist, Uber AI Labs
Chandra Khatri is a Senior AI Scientist at Uber AI driving Conversational AI efforts at Uber. Prior to Uber, he was the Lead AI Scientist at Alexa and was driving the Science for the Alexa Prize Competition, which is a $3.5 Million university competition for advancing the state of... Read More →


Thursday January 24, 2019 2:35pm - 3:00pm
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

2:40pm

Continuous Object Detection for Conversational Vision
Object detection is a core computer vision task, where a machine learning (ML) model is trained to identify objects from a pre-specified set of object categories. In a real-life scenario, e.g., when an object detector is used to process the picture taken by a mobile phone camera, not all object categories are known to the ML model in advance since new objects of interest appear constantly in a user environment. As a result, it is important for object detection models to be continually learning -- they need to learn how to recognize new objects without suffering from the phenomenon of catastrophic forgetting, where the ML model forgets about old objects while learning about new ones. In this work, we discuss a new technology we have developed that can effectively do incremental learning for object detection in near-real time. We discuss the underlying mathematical framework of a novel loss function that enabled us to achieve state-of-the-art performance on benchmark datasets. We will also outline our efficient training and inference framework, which enabled our prototype system to successfully recognize objects in a real-world live demo scenario. We also discuss extensions of our incremental object detection work, where we can use auxiliary unlabeled data to get better models or use AutoML methods to automatically learn the best neural network architecture in the continuous learning mode. We next give a brief overview of a novel recurrent neural network model with attention that we have developed for the task of Visual Dialogue, where the user initiates a dialogue with the system regarding a picture. We conclude by discussing how incremental object detection, improved visual dialogue, and other novel research contributions form the cornerstones of a new framework of Conversational Vision, which is an active computer vision technology at the intersection of Natural Language Processing, Dialogue Understanding and Computer Vision.

Speakers
avatar for Shalini Ghosh, Samsung Research America

Shalini Ghosh, Samsung Research America

Director of AI Research, Samsung Research America
Dr. Shalini Ghosh is the Director of AI Research at the Artificial Intelligence Center of Samsung Research America, where she leads a group working on Situated AI and Multi-modal Learning (i.e., learning from computer vision, language, and speech). She has extensive experience and... Read More →


Thursday January 24, 2019 2:40pm - 3:00pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

2:45pm

Taming the Deep Learning Workflow
Despite enormous excitement about the potential of deep learning, building practical applications powered by deep learning remains an enormous challenge: the necessary expertise is scarce, the hardware requirements can be prohibitive, and current software tools are immature and limited in scope. In this talk, we will first describe how deep learning workflows are supported by existing software tooling. We will then describe several promising opportunities to drastically improve these workflows via novel algorithmic and software solutions, including application aware GPU cluster management and state of the art resource-aware hyperparameter optimization methods. This talk draws on academic work done at CMU, UC Berkeley, and UCLA, as well as our experiences at Determined AI, a startup that builds software to make deep learning engineers dramatically more productive.

Speakers
avatar for Neil Conway, Determined AI

Neil Conway, Determined AI

CTO, Determined AI
Neil Conway is co-founder and CTO of Determined AI, a startup that builds software to dramatically accelerate deep learning model development. Neil was previously a technical lead at Mesosphere and a major developer of both Apache Mesos and Postgres. Neil earned a PhD in Computer... Read More →


Thursday January 24, 2019 2:45pm - 3:00pm
Pacific I-K Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

3:00pm

Advancing State-of-the-art Image Recognition with Deep Learning on Hashtags
At Facebook everyday hundreds of millions of users interact with billions of visual contents. By understanding what's in an image, our systems can help connect users with the things that matter most to them. To improve our recognition system, I will talk about two main research challenges: how we train models at the scale of billions, and how we improve the reliability of the model prediction. Since current models are typically trained on data that are individually labeled by human annotators, scaling up to billions is non-trivial. We solve the challenge by training image recognition networks on large sets of public images with user-supplied hashtags as labels. By leveraging weakly supervised pretraining, our best model achieved a record-high 85.4% accuracy on ImageNet dataset.

Speakers
avatar for Yixuan Li, Facebook AI (Computer Vision Group)

Yixuan Li, Facebook AI (Computer Vision Group)

Research Scientist, Facebook AI (Computer Vision Group)
Yixuan Li is a Research Scientist at Facebook AI, Computer Vision Group. She leads the research effort on large-scale visual learning with high dimensional label space. Before joining Facebook, she obtained her PhD from Cornell University in 2017. Yixuan's research interests are in... Read More →


Thursday January 24, 2019 3:00pm - 3:20pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

3:00pm

With Great Dialog Comes Great Responsibility
Conversations have extraordinary power. They can harm or heal, obfuscate or enlighten, generate confusion or clarity. They can condition us to subtly alter our behavior, and they even shape how we perceive our own inner emotions. So as we teach our devices to converse with us, how can we wield that power responsibly? And how do we teach our algorithms to do the same?

Speakers
avatar for Deborah Harrison, Microsoft

Deborah Harrison, Microsoft

Senior Conversational UI Design Manager, Microsoft
Deborah Harrison (writer, Microsoft) is one of the original architects of the personality for Microsoft's digital assistant, Cortana. She crafted the core principles that define Cortana's approach to communication and now helps shepherd those principles as Cortana lights up on other... Read More →


Thursday January 24, 2019 3:00pm - 3:25pm
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

3:20pm

Data Science & Business Strategy Alignment – How to Ensure your Killer Tech Delivers Real Value
Your data science efforts aren't all that in synch with your overall business strategy.  Don’t fret – it seemingly happens to everyone.  But how do you spot it?  What should you do about it?  In this session, we’ll briefly address how to spot the issue and a few techniques to achieve much improved alignment and, thus, a better business outcome.  Hint, we may suggest that’s a bit crazy to try and find a single person with knowledge and expertise in math, statistics, programming, data wrangling, modeling AND exceptional business knowledge!

Speakers
avatar for Matt Cowell, QuantHub

Matt Cowell, QuantHub

CEO, QuantHub
Matt serves as CEO at QuantHub, responsible for leading the company’s strategy, growth, and operations. Matt has a passion for developing authentic relationships with customers to truly understand what drives them, and then crafting creative solutions to their most critical problems... Read More →



Thursday January 24, 2019 3:20pm - 3:35pm
Pacific G-H Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

3:20pm

COFFEE BREAK 
Thursday January 24, 2019 3:20pm - 4:05pm
Grand Ballroom Foyer Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

3:55pm

Empathy Training 101
What is empathy?  What are some characteristics of empathy in human conversations, and how can we train virtual assistants to exhibit these properties?  We will explore the nature of empathic communication and explore various NLP and machine learning techniques for imbuing a feeling of compassion in your agents.  These approaches help users feel understood and can be used to improve the user experience of nearly any type of AI assistant.


Speakers
avatar for Casey Sackett, Woebot Labs

Casey Sackett, Woebot Labs

CTO, Woebot Labs
I am a hands-on engineering leader who enjoys being involved in all aspects of technical innovation and delivery, from vision to product design to team management to coding and execution. I have strong interests in health technology and social networking and in ways of using math... Read More →


Thursday January 24, 2019 3:55pm - 4:15pm
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

4:00pm

Deeper Things: How Netflix Leverages Deep Learning in Recommendations and Search
In this talk, we will provide an overview of Deep Learning methods applied to personalization and search at Netflix. We will set the stage by describing the unique challenges faced at Netflix in the areas of recommendations and information retrieval. Then we will delve into how we leverage a blend of traditional algorithms and emergent deep learning methods to address these challenges. We will conclude with a note on future directions we plan on pursuing at Netflix.

Speakers
avatar for Aish Fenton, Netflix

Aish Fenton, Netflix

Research Manager, Netflix
Aish is a Research Manager at Netflix. He leads the machine learning research team there for recommender systems and search algorithms. Aish has over 22 years of experience at the intersection of mathematics and software engineering. Prior to Netflix, Aish headed data science at Opentable... Read More →
avatar for Sudeep Das, Netflix

Sudeep Das, Netflix

Senior Researcher, Netflix
Sudeep Das is a Senior Researcher at Netflix, where his main focus is on developing the next generation of machine learning algorithms to drive the personalization, discovery and search experience in the product. Apart from algorithmic work, he also takes a keen interest in data visualizations... Read More →


Thursday January 24, 2019 4:00pm - 4:20pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

4:05pm

Talent & Talk and Skill Swap
The popular Talent & Talk session at RE•WORK Summits returns. You might be keen to share vacancies in your organization, looking for a new role, or you'd just like to share a skill you have with fellow attendees in exchange for a skill you're looking for to develop yourself or your business. If any of the above are relevant to you, then you won't want to miss this session. If you'd like to share, attendees will have 1 minute each to speak and so be ready! Everyone is welcome to attend to simply listen in and make some new connections! Contact hello@re-work.co to register your spot!

Thursday January 24, 2019 4:05pm - 5:00pm
Pacific G-H Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

4:15pm

Building Neural Conversational Machines at Scale
Advances in deep learning have enabled us to build intelligent systems capable of perceiving and understanding real world from text, speech and images. Yet, building real-world Conversational AI systems at scale and from “scratch” remains a daunting challenge as it requires us to deal with ambiguity, data sparsity and solve complex language, dialog and generation problems.
In this talk, I will present powerful neural structured learning frameworks that tackle the above challenges by leveraging the power of deep learning combined with graphs which allow us to model the structure inherent in language and visual data. Our neural graph learning approach handles massive graphs with billions of vertices and trillions of edges and has been successfully used to power real-world applications such as Smart Reply, image recognition and multimodal experiences in many Google products both on Cloud and on-device. Finally, I will describe our recent work on reinforcement learning for controllable dialog generation, where we train a neural network that produces conversational responses conforming to specific semantic attributes such as sentiment, emotion and personality.

Speakers
avatar for Sujith Ravi, Google

Sujith Ravi, Google

Senior Staff Research Scientist, Google
Dr. Sujith Ravi is a Senior Staff Research Scientist and Senior Manager at Google, where he leads the company’s large-scale graph-based machine learning platform and on-device machine learning efforts that power natural language understanding and image recognition for products used... Read More →


Thursday January 24, 2019 4:15pm - 4:35pm
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

4:20pm

5 Lessons for Improving Training Performance
Learn the best practices for performance analytics and maintenance of a deep learning system. As GPU technology continues to advance, the demand for faster data continues to grow. In deep learning, input pipelines are responsible for a complex chain of actions that ultimately feed data into GPU memory, including reading from storage and pre-processing data. These pipelines bring together multiple hardware systems—networking, CPUs, and storage—along with sophisticated software systems to drive the data movement and transformation.

We'll use results of TensorFlow benchmarking on V100 DGX-1s to highlight ways that overall performance is impacted by various components of the pipeline, and we'll share key ways to keep an end-to-end system highly performant over time.

Speakers
avatar for Emily Watkins, Pure Storage

Emily Watkins, Pure Storage

Solution Architect, Pure Storage
Emily Watkins is a Solution Architect at Pure Storage. She helps companies streamline their data pipeline to help scale as their AI Projects grow from infancy to delivering significant outcomes for the business. Emily's background is in research, real-time analytics tools, and artificial... Read More →


Thursday January 24, 2019 4:20pm - 4:40pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

4:35pm

Can an AI Assistant be as Important as the Web or as Mobile?
AI Assistants are used billions of times each week and have been baked into more than a billion consumer devices.  People talk to them to accomplish functions like playing songs, sending text messages, setting timers, and more.  However, while these Assistants are useful, today they are not a global paradigm like the Web or like Mobile, which impact every connected user and every connected business.  In this talk, we will discuss what it might take for an Assistant to make the leap to global paradigm, and then illustrate the unique architecture and approach being taken by Samsung’s Bixby Assistant with the goal of doing just that.

Speakers
avatar for Adam Cheyer, Viv Labs/Samsung

Adam Cheyer, Viv Labs/Samsung

Co-Founder and VP Engineering/VP of R&D, Viv Labs/Samsung
Adam Cheyer is co-Founder and VP Engineering of Viv Labs, and after acquisition in 2016, a VP of R&D at Samsung. Previously, Mr. Cheyer was co-Founder and VP Engineering at Siri, Inc. In 2010, Siri was acquired by Apple, where he became a Director of Engineering in the iPhone/iOS... Read More →


Thursday January 24, 2019 4:35pm - 5:00pm
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

4:40pm

The Myth of the interpretable, Robust, Compact and High Performance Deep Neural Network
Most progress in machine learning has been measured according to gains in test-set accuracy on tasks like image recognition. However, test-set accuracy appears to be poorly correlated with other design objectives such as interpretability, robustness to adversarial attacks or training compact networks that can be used in resource constrained environments. This talk will ask whether it is possible to have it all, and more importantly how do we measure progress when we want to train model functions that fulfill multiple criteria.

Speakers
avatar for Sara Hooker, Google

Sara Hooker, Google

Artificial Intelligence Resident, Google
Sara Hooker is Artificial Intelligence Resident at Google Brain doing deep learning research on model compression and reliable explanations of model predictions for black-box models. Her main research interests gravitate towards interpretability, model compression and security. In... Read More →


Thursday January 24, 2019 4:40pm - 5:00pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

5:00pm

CONVERSATION & DRINKS
Thursday January 24, 2019 5:00pm - 6:00pm
Grand Ballroom Foyer Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA
 
Friday, January 25
 

8:00am

DOORS OPEN
Friday January 25, 2019 8:00am - 9:00am
Grand Ballroom Foyer Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:00am

Compère Welcome - Deep Learning Stage
Our compère for the Deep Learning Stage today will be Alicia Kavelaars, Co-Founder and CTO at OffWorld.

Speakers
avatar for Alicia Kavelaars, OffWorld

Alicia Kavelaars, OffWorld

Co-Founder and CTO, OffWorld
Alicia is Co-Founder and Chief Technology Officer at OffWorld Inc. She brings over 15 years of experience in the aerospace industry developing and successfully launching systems for NASA, NOAA and the Telecommunications industry. In 2015, Alicia made the jump to New Space to work... Read More →


Friday January 25, 2019 9:00am - 9:10am
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:00am

Compère Welcome - Ethics & Social Responsibility Stage
Speakers
avatar for Fiona McEvoy, YouTheData.com

Fiona McEvoy, YouTheData.com

Tech Ethics Researcher and Founder, YouTheData.com
Fiona J McEvoy holds a graduate degree in Philosophy, with a special focus on ethics and technology. She recently presented her work to the International Association for Computing and Philosophy (IACAP) at Stanford University, and her latest paper on Big Data and the future of autonomy... Read More →


Friday January 25, 2019 9:00am - 9:10am
Pacific I-K Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:10am

Learned Video Compression
We present an algorithm for video coding, learned end-to-end for the low-latency mode. In this setting, our approach outperforms all standard video codecs across nearly the entire bitrate range. To our knowledge, this is the first ML-based method to do so. We propose a novel architecture for video compression which generalizes motion estimation to perform any learned compensation beyond simpler translations. Our architecture allows for joint compression of motion and residual and can dynamically trade-off between them. It is also able to model multiple flow fields in the same frame. We propose an ML-based spatial rate control, which allows or model to adaptively change the bitrate across space for each frame. For the same quality traditional codecs achieve up to 60% larger code.

Speakers
avatar for Lubomir Bourdev, WaveOne

Lubomir Bourdev, WaveOne

Co-Founder & CEO, WaveOne
Lubomir Bourdev is a co-founder and the CEO of WaveOne, Inc., a startup focusing on video compression with deep learning. He is also a founding member of Facebook AI Research and he founded and led the Facebook AML Computer Vision team responsible for the image and video content recognition... Read More →


Friday January 25, 2019 9:10am - 9:25am
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:10am

Three Principles for the Responsible Use of AI
Cutting edge machine learning and AI technologies make increasingly consequential decisions, leading regulators, journalists, and the public to demand that they be built responsibly and ethically while protecting security and privacy. AI technologies undercut traditional data governance and compliance approaches, even as businesses that field data driven systems of all sorts - from the simplest descriptive analytics to the most sophisticated deep learning models - face a thicket of requirements and stakeholder demands. This workshop presents three actionable principles for building AI responsibly. These principles provide practical approaches to building AI systems that embody the right values, such as responsibility, fairness, ethics, and privacy, while still meeting their business goals and product requirements.

Speakers
avatar for Joshua Kroll, UC Berkeley School of Information

Joshua Kroll, UC Berkeley School of Information

Postdoctoral Research Scholar & Computer Scientist, UC Berkeley School of Information
Joshua A. Kroll, PhD, is a computer scientist and leading expertrecognized internationally for his work on responsibility andaccountability in computer systems, especially automateddecision-making systems and systems that use data science, machinelearning, and artificial intelligence... Read More →


Friday January 25, 2019 9:10am - 9:40am
Pacific I-K Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:10am

Building Scalable Framework and Environment of Reinforcement Learning
Deep Reinforcement Learning (DRL) has made strong progress in many tasks that are traditionally considered to be difficult, such as complete information games, navigation, architecture search, etc. Although the basic principle of DRL is quite simple and straightforward, to make it work often requires substantial efforts, compared to traditional supervised training. In this talk, we introduce our recent open-sourced ELF platform: efficient, lightweight and flexible frameworks to facilitate DRL research. We show the scalability of our platforms by reproducing and open sourcing AlphaGoZero/AlphaZero framework using 2000 GPUs and 1.5 weeks, achieving super-human performance of Go AI that beats 4 top-30 professional players with 20-0. We also show usability of our platform by training agents in real-time strategy games with only a small amount of resource. The trained agent develops interesting tactics and is able to beat rule-based AIs by a large margin. On the environment side, we propose House3D that makes multi-room navigation easy with fast frame rate. With House3D, we show that model-based agent that plans ahead with uncertain information navigate in unseen environments more successfully.

Speakers
avatar for Yuandong Tian, Facebook AI Research (FAIR)

Yuandong Tian, Facebook AI Research (FAIR)

Research Scientist and Manager, Facebook AI Research (FAIR)
Yuandong Tian is a Research Scientist and Manager in Facebook AI Research, working on deep reinforcement learning and its applications in games, and theoretical analysis of deep models. He is the lead scientist and engineer for ELF Platform for Reinforcement Learning, OpenGo and DarkForest... Read More →


Friday January 25, 2019 9:10am - 9:55am
Pacific G-H Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:25am

Using AI to Transform Informational Videos and Our Watching Behavior
Videos account for about 75% of the internet traffic and enterprises are increasingly using videos for various informational purposes, including training of customers, partners and employees, marketing and internal communication. However, most viewers do not have the patience to watch these videos end-to-end and our video watching experience has not evolved much in over a decade. We present an AI-based approach to automatically index videos in the form of a table-of-contents, a phrase cloud and a searchable transcript, which helps summarize the key topics in a video and lets viewers navigate directly to the topics of interest. We use a combination of visual classification, object detection, automated speech recognition, text summarization, and domain classification, and show the results achieved on a range of informational videos. We conclude with some thoughts on the promise of transforming how informational videos are consumed as well as open problems and future directions.

Speakers
avatar for Manish Gupta, VideoKen

Manish Gupta, VideoKen

CEO & Co-Founder, VideoKen
Dr. Manish Gupta is the co-founder and CEO of VideoKen Inc., a video technology startup. He has served as the Vice President and Director of Xerox Research Centre India and has held various leadership positions with IBM, including that of Director, IBM Research - India and Chief Technologist... Read More →



Friday January 25, 2019 9:25am - 9:40am
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:40am

DNA of an AI Powered Robotic Workforce for Extreme Environments
As practical applications of AI emerge in industrial robotics, we are starting to realize the potential of highly autonomous robotic systems not only capable of performing AI driven tasks in simulation or structured environments, but out in the field and even in extreme environments. However, there are optimum solutions that do not require the use of deep reinforcement learning or other Machine Learning methodologies. What is the right balance between powerful implementations of AI and traditional automation control to achieve a highly autonomous robotic system that can operate in remote unforgiving locations? Is there a right DNA for an AI powered robotic workforce for extreme environments?

Speakers
avatar for Alicia Kavelaars, OffWorld

Alicia Kavelaars, OffWorld

Co-Founder and CTO, OffWorld
Alicia is Co-Founder and Chief Technology Officer at OffWorld Inc. She brings over 15 years of experience in the aerospace industry developing and successfully launching systems for NASA, NOAA and the Telecommunications industry. In 2015, Alicia made the jump to New Space to work... Read More →


Friday January 25, 2019 9:40am - 9:55am
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:40am

How AI Can Empower the Blind Community 
Speakers
avatar for Anirudh Koul, Aira

Anirudh Koul, Aira

Head of AI & Research, Aira
Anirudh Koul is the Head of AI & Research at Aira (Visual interpreter for the blind), and upcoming author of 'Practical Deep Learning for Cloud and Mobile'. Previously at Microsoft AI & Research, he founded Seeing AI App - often considered the defacto app in the blind and low vision... Read More →


Friday January 25, 2019 9:40am - 10:10am
Pacific I-K Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

9:55am

Deep Robotic Learning
Deep learning has been demonstrated to achieve excellent results in a range of passive perception tasks, from recognizing objects in images to recognizing human speech. However, extending the success of deep learning into domains that involve active decision making has proven challenging, because the physical world presents an entire new dimension of complexity to the machine learning problem. Machines that act intelligently in open-world environments must reason about temporal relationships, cause and effect, and the consequences of their actions, and must adapt quickly, follow human instruction, and remain safe and robust. Although the basic mathematical building blocks for such systems -- reinforcement learning and optimal control -- have been studied for decades, such techniques have been difficult to extend to real-world control settings. For example, although reinforcement learning methods have been demonstrated extensively in settings such as games, their applicability to real-world environments requires new and fundamental innovations: not only does the sample complexity of such methods need to be reduced by orders of magnitude, but we must also study generalization, stability, and robustness. In this talk, I will discuss how deep learning and reinforcement learning methods can be extended to enable real-world robotic control, with an emphasis on techniques that generalize to situations, objects, and tasks. I will discuss how model-based reinforcement learning can enable sample-efficient control, how model-free reinforcement learning can be made efficient, robust, and reliable, and how meta-learning can enable robotic systems to adapt quickly to new tasks and new situations.

Speakers
avatar for Sergey Levine, UC Berkeley

Sergey Levine, UC Berkeley

Assistant Professor, UC Berkeley
Sergey Levine received a BS and MS in Computer Science from Stanford University in 2009, and a Ph.D. in Computer Science from Stanford University in 2014. He joined the faculty of the Department of Electrical Engineering and Computer Sciences at UC Berkeley in fall 2016. His work... Read More →


Friday January 25, 2019 9:55am - 10:15am
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

10:10am

Compère Welcome - Investors & Startups Stage
Speakers
avatar for Jeroen Vanhoutte,11.2 Capital

Jeroen Vanhoutte,11.2 Capital

Principal, 11.2 Capital
Jeroen is passionate about technological paradigm shifts, especially smart hardware, robotics, quantum computing, and new space technologies. Before joining 11.2 Capital, he worked on deals across the investment value chain: traditional private equity at Sofina, search funds at NextGen... Read More →


Friday January 25, 2019 10:10am - 10:20am
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

10:10am

COFFEE BREAK 
Friday January 25, 2019 10:10am - 10:45am
Grand Ballroom Foyer Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

10:20am

Playing for Keeps: High Stakes vs Low Stakes
The history of AI is one of boom-bust cycles. Are we nearing an AI winter? I think the answer is both yes and no: yes for what I call high stakes AI, and no for low-stakes AI. I'll share our perspective as both practitioners and investors in AI driven companies.

Speakers
avatar for Ilya Kirnos, Signalfire

Ilya Kirnos, Signalfire

Managing Director & CTO, Signalfire
Prior to co-founding SignalFire, Ilya was a Software Engineer at Google (2004-2012). During his time at Google, Ilya held several technical leadership positions. He was a Technical Lead for Gmail Ads and was responsible for predicting consumer purchase intent and consumer Gmail monetization... Read More →


Friday January 25, 2019 10:20am - 10:45am
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

10:30am

Building On-prem GPU Training Infrastructure
You'll learn how to provide your team with GPU training infrastructure at a variety of scales, from a single shared multi-GPU system to a cluster for distributed training.

Speakers
avatar for Stephen Balaban, Lambda Labs

Stephen Balaban, Lambda Labs

Co-Founder & CEO, Lambda Labs
Stephen Balaban, is the co-founder and CEO of Lambda. Lambda provides GPU servers, workstations and cloud services for training neural networks. Lambda customers include Apple, Tencent, Intel, Microsoft, Harvard, Princeton, Stanford, and the U.S. Federal Government. Prior to Lambda... Read More →



Friday January 25, 2019 10:30am - 11:15am
Pacific G-H Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

10:35am

Compère Welcome - Futurescaping Stage
Speakers
avatar for Nina D'Amato, The San Francisco Department of Technology

Nina D'Amato, The San Francisco Department of Technology

Chief of Staff, The San Francisco Department of Technology
Nina D’Amato is the Chief of Staff at the San Francisco Department of Technology, The San Francisco Department of Technology is an enterprise information and technology services organization that supports approximately 35,000 employees and 56 departments of the City and County of... Read More →


Friday January 25, 2019 10:35am - 10:45am
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

10:45am

Control Algorithms for Imitation Learning from Observation
Imitation learning is a paradigm that enables autonomous agents to capture behaviors that are demonstrated by people or other agents. Effective approaches, such as Behavioral Cloning and Inverse Reinforcement Learning, tend to rely on the learning agent being aware of the low-level actions being demonstrated.  However, in many cases, such as videos or demonstrations from people (or any agent with a different morphology), the learning agent only has access to observed state transitions.  This talk introduces two novel control algorithms for imitation learning from observation: Behavioral Cloning from Observation (BCO) and Generative Adversarial Imitation from Observation (GAIfO).


Speakers
avatar for Peter Stone, University of Texas

Peter Stone, University of Texas

Founder & Director of the Learning Agents Research Group, University of Texas
I am the founder and director of the Learning Agents Research Group (LARG) within the Artificial Intelligence Laboratory in the Department of Computer Science at The University of Texas at Austin, as well as associate department chair and chair of the University's Robotics Portfolio... Read More →


Friday January 25, 2019 10:45am - 11:05am
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

10:45am

Human-Centric AI: Interpreting and Adjusting to Human Needs in Human-Machine Collaboration 
Speakers
avatar for Mark Bergen, Bloomberg News

Mark Bergen, Bloomberg News

Reporter, Bloomberg News
Mark Bergen, who will be covering Google and some other related companies, has reported on business and policy since 2010, most recently at Advertising Age where he covered mobile operators, device makers and media. Before that, Mark reported from Bangalore, India, writing about economics... Read More →
avatar for Vinod Bakthavachalam, Coursera

Vinod Bakthavachalam, Coursera

Senior Data Scientist, Coursera
Vinod Bakthavachalam is a data scientist working with the Content Strategy and Enterprise teams where his work has recently focused on developing ways to measure the learning outcomes from taking Coursera classes, especially in the context of company sponsored training. Prior to Coursera... Read More →
avatar for Dimitri Kanevsky, Google

Dimitri Kanevsky, Google

Researcher, Google
Dimitri Kanevsky started his career at Google working on speech recognition algorithms. Prior to joining Google, Dimitri was a Research staff member in the Speech Algorithms Department at IBM. Prior to IBM, he worked at a number of centers for higher mathematics, including Max Planck... Read More →
avatar for Dorsa Sadigh, Stanford University

Dorsa Sadigh, Stanford University

Assistant Professor, Stanford University
Dorsa Sadigh is an assistant professor in Computer Science and Electrical Engineering at Stanford University. Her research interests lie in the intersection of robotics, learning and control theory, and algorithmic human-robot interaction. Specifically, she works on developing efficient... Read More →


Friday January 25, 2019 10:45am - 11:25am
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

10:45am

Quick Pitch 
Quick Pitch is your chance as a startup to present or demo your work, with 3 minutes to pitch and 2 minutes for Q&A. Time is short so come prepared! You are welcome to bring a laptop to present (HDMI connection available). Email hello@re-work.co to register your presentation spot in advance to the event. From the 24th January, please register your interest with a member of the RE•WORK team.

Friday January 25, 2019 10:45am - 11:45am
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

10:45am

Reimaging the News: How can AI/ML be used to assure open and credible news platforms? 
Join SignalFire Head of Communities, Michael Martin, and three industry experts to reimagine how platforms can use to AI/ML/Deep Learning to assure that information is credible while remaining open. During this workshop you will have the opportunity to work closely in small groups with other attendees to develop bluesky solutions to one of the most pervasive challenges facing democratic societies.

Speakers
avatar for Mike Tamir, Uber ATG

Mike Tamir, Uber ATG

Head of Data Science, Uber ATG
Mike serves as Head of Data Science at Uber ATG, UC Berkeley Data Science faculty, and Director of Phronesis ML Labs. He has led teams of Data Scientists in the bay area as Chief Data Scientist for InterTrust and Takt, Director of Data Sciences for MetaScale/Sears, and CSO for Galvanize... Read More →
avatar for Ilya Kirnos, Signalfire

Ilya Kirnos, Signalfire

Managing Director & CTO, Signalfire
Prior to co-founding SignalFire, Ilya was a Software Engineer at Google (2004-2012). During his time at Google, Ilya held several technical leadership positions. He was a Technical Lead for Gmail Ads and was responsible for predicting consumer purchase intent and consumer Gmail monetization... Read More →
avatar for Michael Martin, Signalfire

Michael Martin, Signalfire

Director of Communities, Signalfire
Michael is the Director of Communities at SignalFire, an AI-driven VC firm that focuses on seed and growth-stage investments. He joined the firm in 2018, where he is building the firm’s communities programs, which includes developing content and events that provide value to portfolio... Read More →


Friday January 25, 2019 10:45am - 12:15pm
Pacific I-K Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:05am

Meta-Learning Deep Networks
Deep learning has enabled significant advances in a variety of domains; however, it relies heavily on large labeled datasets. I will discuss how we can use meta-learning, or learning to learn, to enable us to adapt deep models to new tasks with tiny amounts of data, by leveraging data from other tasks. By using these meta-learning techniques, I will show how we can build better unsupervised learning algorithms, build agents that can adapt online to changing environments, and build robots that can interact with a new object by watching a single demonstration.

Speakers
avatar for Chelsea Finn, Google Brain & Berkeley AI Research

Chelsea Finn, Google Brain & Berkeley AI Research

Research Scientist & Post-doctoral Scholar, Google Brain & Berkeley AI Research
Chelsea Finn is a research scientist at Google Brain and post-doctoral scholar at Berkeley AI Research. Starting in 2019, she will join the faculty in CS at Stanford University. She is interested in how learning algorithms can enable machines to acquire general notions of intelligence... Read More →


Friday January 25, 2019 11:05am - 11:30am
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:15am

End-to-End Continuous Machine Learning in Production with PipelineAI, Spark ML, TensorFlow AI, PyTorch, Kafka, TPUs, and GPUs
Traditional machine learning pipelines end with life-less models sitting on disk in the research lab.  These traditional models are typically trained on stale, offline, historical batch data. Static models and stale data are not sufficient to power today's modern, AI-first Enterprises that require continuous model training, continuous model optimizations, and lightning-fast model experiments directly in production. Through a series of open source, hands-on demos and exercises, we will use PipelineAI to breathe life into these models using 4 new techniques that we’ve pioneered:
* Continuous Validation (V)
* Continuous Optimizing (O)
* Continuous Training (T)
* Continuous Explainability (E).

The Continuous "VOTE" techniques has proven to maximize pipeline efficiency, minimize pipeline costs, and increase pipeline insight at every stage from continuous model training (offline) to live model serving (online.)
Attendees will learn to create continuous machine learning pipelines in production with PipelineAI, TensorFlow, and Kafka.

A laptop is required for this session. 

Speakers
avatar for Chris Fregly, PipelineAI

Chris Fregly, PipelineAI

Founder, PipelineAI
Chris Fregly is Founder at PipelineAI, a Real-Time Machine Learning and Artificial Intelligence Startup based in San Francisco. He is also an Apache Spark Contributor, a Netflix Open Source Committer, founder of the Global Advanced Spark and TensorFlow Meetup, author of the O’Reilly... Read More →


Friday January 25, 2019 11:15am - 12:15pm
Pacific G-H Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:25am

Growth Across Borders: Navigating International Expansion for AI Companies
In an industry market by rapid innovation and business opportunity, AI and Deep Learning companies need to anticipate and capitalize upon growth opportunities abroad. In this session, an executive panel will lead audience members to a better understanding of the risks, rewards, and thought processes around international expansion for AI companies. Audience members will walk away with a more complete awareness of business considerations for developing a global workforce, including the rationale for globalizing, ecosystem selection, working with strategic partners, navigating labor markets and more.

Session led by the Canadian Trade Commissioner Service:
As part of Global Affairs Canada, the Canadian Trade Commissioner Service helps Canadian companies and organizations succeed globally. The Canadian Trade Commissioner Service has trade offices across Canada and in 161 offices around the world. We can provide Canadian businesses with on-the-ground intelligence, qualified contacts, partnership opportunities and practical advice on foreign markets to help you make better, timelier and more cost-effective decisions in order to achieve your goals abroad. If you’re looking to do business in Canada, the TCS global network of trade professionals can assist foreign companies in making Canada their next investment destination.

Speakers
avatar for Jon French

Jon French

Senior Director of Global Recruitment, Community & Alumni, NEXT Canada
Jon joined The Next 36 (now NEXT Canada) in April 2011 and is responsible for marketing, communications and recruitment with an emphasis on attracting high potential entrepreneurs to the organization's three programs. Jon manages relationships with prospective applicants, student... Read More →
avatar for Ram Shanmugam, AutonomIQ

Ram Shanmugam, AutonomIQ

Co-founder, CEO and President, AutonomIQ
Ram Shanmugam is the co-founder and CEO of AutonomIQ, a company focusing on using AI, machine learning and deep learning innovations to deliver autonomous testing and dev-ops solutions. Ram is a serial entrepreneur, and most recently, he was the co-founder and CEO of appOrbit. Previously... Read More →
avatar for Lloyed Lobo, Boast.AI

Lloyed Lobo, Boast.AI

Co-Founder, Boast.AI
Lloyed is the co-founder of Boast.AI which helps businesses automate the complicated process of claiming R&D incentives from the government. At Boast, Lloyed is responsible for growth, go-to-market and new product strategy. Lloyed is also the cofounder of Traction which brings together... Read More →
avatar for Thomas Hamilton, Ross Intelligence

Thomas Hamilton, Ross Intelligence

VP, Legal Strategy, Ross Intelligence
Thomas Hamilton is the VP Strategy and Operations at ROSS Intelligence, where he co-ordinates efforts across the company to ensure that sole practitioners, legal aid groups, law firms, government agencies, corporate law departments, state bar associations and law faculties are able... Read More →



Friday January 25, 2019 11:25am - 12:25pm
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:30am

Latent Structure in Deep Robotic Learning
Traditionally, deep reinforcement learning has focused on learning one particular skill in isolation and from scratch. This often leads to repeated efforts of learning the right representation for each skill individually, while it is likely that such representation could be shared between different skills. In contrast, there is some evidence that humans reuse previously learned skills efficiently to learn new ones, e.g. by sequencing or interpolating between them.
In this talk, I will demonstrate how one could discover latent structure when learning multiple skills concurrently. In particular, I will present a first step towards learning robot skill embeddings that enable reusing previously acquired skills. I will show how one can use these ideas for multi-task reinforcement learning, sim-to-real transfer and imitation learning.

Speakers
avatar for Karol Hausman, Google Brain

Karol Hausman, Google Brain

Research Scientist, Google Brain
Karol Hausman is a Research Scientist at Google Brain in Mountain View, California working on robotics and machine learning. He is interested in enabling robots to autonomously acquire general-purpose skills with minimal supervision in real-world environments. His current research... Read More →


Friday January 25, 2019 11:30am - 11:50am
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

11:50am

Applying Multimodal Integrated Learning Behavioral Analysis and Virtual Personalized Assistant to Adaptive Education
Summary, in this talk, Dr. Edgar Kalns who is the lead researcher on the SRI - Squirrel AI Joint Lab will discuss two exciting AI and Machine Learning applications for adaptive education. He will illustrate the theoretical foundation, technical approach, and research findings from the MILBA and VPA projects.

Speakers
avatar for Edgar Kalns, Squirrel AI

Edgar Kalns, Squirrel AI

Director of SRI-Squirrel AI Joint Collaboration, Squirrel AI
Edgar Kalns, Ph.D., is leading SRI’s Studio on Aging, an institute-wide initiative to help seniors live independent and fulfilled lives, simultaneously addressing the widening caregiver gap. The Studio's goal is to create world-changing interdisciplinary solutions by fusing technologies... Read More →


Friday January 25, 2019 11:50am - 12:10pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

12:10pm

Brand is Beyond Logos – Understanding Visual Brand
Logos come to mind when we think about iconic brands. However, a spectrum of visual cues is used to establish the signature of a brand. This includes color, pattern, shape. We train deep neural network to predict a variety of fashion brand and analyze visual representations using strength and extent of neuron activations. Logo is demonstrated to be at one end of the spectrum. Study of versatility of neurons shows that they are diverse in nature and contain specialists and generalists. Potential applications of making neural network explainable include personalization, elimination of bias in prediction, model improvement.

Speakers
avatar for Robinson Piramuthu, eBay

Robinson Piramuthu, eBay

Chief Scientist for Computer Vision, eBay
Robinson Piramuthu joined eBay in 2011 and is currently the Chief Scientist for Computer Vision. He has over 20 years of experience in computer vision which includes large scale visual search, coarse and fine-grained visual recognition, object detection, computer vision for fashion... Read More →


Friday January 25, 2019 12:10pm - 12:30pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

12:15pm

LUNCH
Friday January 25, 2019 12:15pm - 1:15pm
Atrium Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:00pm

Understanding the limitations of AI: When Algorithms Fail
Automated decision making tools are currently used in high stakes scenarios. From natural language processing tools used to automatically determine one’s suitability for a job, to health diagnostic systems trained to determine a patient’s outcome, machine learning models are used to make decisions that can have serious consequences on people’s lives. In spite of the consequential nature of these use cases, vendors of such models are not required to perform specific tests showing the suitability of their models for a given task. Nor are they required to provide documentation describing the characteristics of their models, or disclose the results of algorithmic audits to ensure that certain groups are not unfairly treated. I will show some examples to examine the dire consequences of basing decisions entirely on machine learning based systems, and discuss recent work on auditing and exposing the gender and skin tone bias found in commercial gender classification systems. I will end with the concept of an AI datasheet to standardize information for datasets and pre-trained models, in order to push the field as a whole towards transparency and accountability.

Speakers
avatar for Timnit Gebru, Ethical AI Team at Google

Timnit Gebru, Ethical AI Team at Google

Research Scientist, Ethical AI Team,Google
Timnit Gebru is a research scientist in the Ethical AI team at Google and just finished her postdoc in the Fairness Accountability Transparency and Ethics (FATE) group at Microsoft Research, New York. Prior to that, she was a PhD student in the Stanford Artificial Intelligence Laboratory... Read More →


Friday January 25, 2019 1:00pm - 1:30pm
Pacific I-K Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:00pm

Imagination-Based AI: Envision the Future Beyond DL 
In this workshop, we explore an emerging frontier of AI and machine learning research that goes beyond correlational data mining approaches, such as deep learning. In a large variety of challenging business and societal problems, from combating traffic congestion in urban metropolises, and delivering better quality healthcare and education, to improving the success rate of digital marketing and online campaigns, and modeling interventions that combat climate change, what is fundamentally necessary is integrating three types of reasoning by combining correlational, causal, and imagination-based models. Participants in this workshop will be introduced to a powerful class of modeling languages that extend deep learning through a three layer architecture that combines correlational (layer one), causal and interventional decisions (layer two), as well as counterfactual and imagination-based reasoning (layer three).

Most of deep learning is currently restricted to producing a statistical summarization of data, that is, they answer “What is” queries. For example, generative adversarial networks (GANs) can be trained to produce new samples from a given fixed distribution (e.g, new face images given a dataset of face images). We introduce novel and powerful new methods that can also answer “What-if” queries, as well as “Why” queries. Integrating the three fundamental modes of reasoning, from “What is” to “What if” and “Why”, will enable the next generation of AI systems to be far more powerful than current deep learning architectures, like GANs. The workshop presentation will include a detailed overview of the underlying modeling languages, as well as hands-on demonstrations of how to use these new emerging tools in a diverse range of practical real-world problems.

Speakers
avatar for Sridhar Mahadevan, Adobe Research

Sridhar Mahadevan, Adobe Research

Director of Data Science, Adobe Research
Sridhar Mahadevan is currently Director of Data Science at Adobe Research in San Jose, and holds faculty appointments at Stanford Univeristy (visiting professor in the School of Engineering) and a Full Professor at the College of Information and Computer Sciences at the University... Read More →


Friday January 25, 2019 1:00pm - 3:00pm
Pacific G-H Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:15pm

Applying Deep Learning to Article Embedding for Fake News Evaluation
In this talk we explore real world use case applications for automated “Fake News” evaluation using contemporary deep learning article vectorization and tagging. We begin with the use case and an evaluation of the appropriate context applications for various deep learning applications in fake news evaluation. Technical material will review several methodologies for article vectorization with classification pipelines, ranging from traditional to advanced deep architecture techniques. We close with a discussion on troubleshooting and performance optimization when consolidating and evaluating these various techniques on active data sets.

Speakers
avatar for Mike Tamir, Uber ATG

Mike Tamir, Uber ATG

Head of Data Science, Uber ATG
Mike serves as Head of Data Science at Uber ATG, UC Berkeley Data Science faculty, and Director of Phronesis ML Labs. He has led teams of Data Scientists in the bay area as Chief Data Scientist for InterTrust and Takt, Director of Data Sciences for MetaScale/Sears, and CSO for Galvanize... Read More →


Friday January 25, 2019 1:15pm - 1:40pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:15pm

Adopting a Machine Learning Mindset: How to Discover, Develop, and Deliver Automation Solutions Company-Wide 
As Machine Learning becomes a core component of any forward-looking company, how can we engage the entire workforce to help with ML and automation initiatives? This talk will cover how at Square we have adopted a "machine learning mindset" by 1. providing training to all employees (both technical and non-technical folks) on what ML is and how it works, including current applications and ethical considerations, 2. conducting structured brainstorming sessions to elicit automation opportunities, where everyone can contribute what ML could mean for their team or their customers, and 3. implementing a subset of those ideas by partnering with infrastructure, operations, and product teams, resulting in improved risk management, more efficient internal operations, and novel customer-facing product features.

Speakers
avatar for Marsal Gavalda, Square

Marsal Gavalda, Square

Head of Machine Learning, Square
Marsal Gavalda is a senior R&D executive with deep expertise in speech, language, and machine learning technologies. Marsal currently heads the Commerce Platform Machine Learning team at Square, where he applies machine learning and automation for Square's overarching purpose of economic... Read More →


Friday January 25, 2019 1:15pm - 1:45pm
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:20pm

Investing in Startups Panel – Part 1 : Current landscape and the Do’s & Don’ts for Entrepreneurs
Speakers
avatar for Ashish Aggarwal, Grishin Robotics

Ashish Aggarwal, Grishin Robotics

Principal, Grishin Robotics
Ashish invests in early-stage companies in Robotics, Connected hardware, AI/ML, and consumer sector at Grishin Robotics. Before that, Ashish led strategic corporate acquisitions, investments, and divestitures for Opera Software where he oversaw transactions worth hundreds of millions... Read More →
avatar for Ashu Garg, Foundation Capital

Ashu Garg, Foundation Capital

General Partner, Foundation Capital
Ashu Garg is a General Partner at Foundation Capital, focusing on startups in enterprise software, marketing technology (MarTech), AI-enabled business applications, data platforms, data center infrastructure, and online video. Before joining Foundation Capital in 2008, Ashu was the... Read More →
avatar for Albert Wang, Qualcomm Ventures

Albert Wang, Qualcomm Ventures

Director, Qualcomm Ventures
Albert Wang is a Director at Qualcomm Ventures. His current investment areas are mobile, cloud, internet of things (IoT), and artificial intelligence (AI). Albert led the investments and currently serves as a board observer for AnyVision, AttackIQ, Avalanche Technology, BlueStacks... Read More →
avatar for Chris Neumann, Commonwealth Ventures

Chris Neumann, Commonwealth Ventures

Early-Stage Investor, Commonwealth Ventures
Chris Neumann is an early-stage investor who works with enterprise software companies in the US, Canada, and the UK.  Chris was formerly a Venture Partner at 500 Startups, where he launched the 500 Startups Data Track, a specialized program focused on accelerating enterprise data... Read More →


Friday January 25, 2019 1:20pm - 1:50pm
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:30pm

Panel: Ethical AI - Harnessing Automation for a Just World
With the inevitable proliferation of AI-based automation, ethical considerations become of paramount importance. How do we ensure that AI-powered technologies do not propagate unfair biases in a fully automated way? In this session, panelists will discuss potential pitfalls of automation, processes that businesses should implement to avoid these pitfalls, definitions of fairness, and the incredible opportunity we have as a society, to instill fairness as a first class construct into the systems we build.

Speakers
avatar for Shubha Nabar, Salesforce Einstein

Shubha Nabar, Salesforce Einstein

Senior Director of Data Science, Salesforce Einstein
Shubha Nabar is a Senior Director of Data Science at Salesforce Einstein where she and her team make machine learning technologies accessible to the hundreds of thousands of businesses that use Salesforce every day. In 2017, she was featured as one of 20 Incredible Women Advancing... Read More →
avatar for Anna Bethke, Intel

Anna Bethke, Intel

Head of AI for Social Good, Intel
Anna Bethke is the Head of AI for Social Good of Intel's Artificial Intelligence Products Group where she is establishing partnerships with social impact organizations; enabling their missions with Intel's technologies and AI expertise. She is also actively involved in the AI Ethics... Read More →
avatar for Chandra Khatri, Uber AI Labs

Chandra Khatri, Uber AI Labs

Senior AI Scientist, Uber AI Labs
Chandra Khatri is a Senior AI Scientist at Uber AI driving Conversational AI efforts at Uber. Prior to Uber, he was the Lead AI Scientist at Alexa and was driving the Science for the Alexa Prize Competition, which is a $3.5 Million university competition for advancing the state of... Read More →
avatar for Londa Schiebinger, Stanford University

Londa Schiebinger, Stanford University

Professor of History of Science, Stanford University
Londa Schiebinger is the John L. Hinds Professor of History of Science at Stanford University and directs the EU/US Gendered Innovations in Science, Health & Medicine, Engineering, and Environment project. She is a leading international expert on gender in science and technology and... Read More →


Friday January 25, 2019 1:30pm - 2:10pm
Pacific I-K Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:40pm

Applying Deep Learning To Airbnb Search
Searching for homes is the primary mechanism guests use to find the place they want to book at Airbnb. The goal of search ranking is to find guests the best possible options while rewarding the most deserving hosts. Ranking at Airbnb is a quest to understand the needs of the guests and the quality of the hosts to strike the best match possible. Applying machine learning to this challenge is one of the biggest success stories at Airbnb. Much of the initial gains were driven by a gradient boosted decision tree model. The gains, however, plateaued over time. This talk discusses the work done in applying neural networks in an attempt to break out of that plateau. The talk focuses on the elements we found useful in applying neural networks to a real life product. To other teams embarking on similar journeys, we hope this account of our struggles and triumphs will provide some useful pointers. Bon voyage!

Speakers
avatar for Malay Haldar, Airbnb

Malay Haldar, Airbnb

Machine Learning Engineer, Airbnb
Malay is a machine learning engineer working on search ranking at Airbnb. Prior to Airbnb, Malay worked on applying machine learning to Google Play search with the goal of understanding the functionality of each app. Before machine learning, Malay worked on web-scale infrastructure... Read More →


Friday January 25, 2019 1:40pm - 2:00pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:45pm

Panel: Should you be Hiring a Chief AI Officer? 
Speakers
avatar for Pavan Arora, Aramark

Pavan Arora, Aramark

Chief AI Officer, Aramark
Pavan recently joined Aramark as Chief AI Officer, leading innovation in data and AI. Prior to Aramark, Pavan served as Chief Data Officer at IBM Watson, responsible for making Watson smarter. He began his career as a banker at JP Morgan, then founded six tech startups which eventually... Read More →
avatar for Robinson Piramuthu, eBay

Robinson Piramuthu, eBay

Chief Scientist for Computer Vision, eBay
Robinson Piramuthu joined eBay in 2011 and is currently the Chief Scientist for Computer Vision. He has over 20 years of experience in computer vision which includes large scale visual search, coarse and fine-grained visual recognition, object detection, computer vision for fashion... Read More →
avatar for George Lawton, Independent

George Lawton, Independent

Technology Journalist, Independent
George Lawton is a freelance technology journalist based near San Francisco, Calif. Over the last 25 years he has written over 3,000 stories for publications about computers, communications, AI, big data, and the Internet of Things. Before that, he sailed a Chinese junk to Antarctica... Read More →
avatar for Alan Lee, Kohl's

Alan Lee, Kohl's

VP of Data Science and Data Science Engineering, Kohl's
Alan Lee is VP of Data Science and Data Science Engineering at Kohl's whose teams are leveraging AI and ML to transform the retail space. He has been in the Data Science field for over 15 years working on AI and Advanced ML applications in industry after graduating from Stanford with... Read More →
avatar for Marsal Gavalda, Square

Marsal Gavalda, Square

Head of Machine Learning, Square
Marsal Gavalda is a senior R&D executive with deep expertise in speech, language, and machine learning technologies. Marsal currently heads the Commerce Platform Machine Learning team at Square, where he applies machine learning and automation for Square's overarching purpose of economic... Read More →


Friday January 25, 2019 1:45pm - 2:30pm
Pacific D-F Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

1:50pm

Investing in Startups Panel – Part 2 : Moonshot Ideas and Applications That Excite a VC 
Speakers
avatar for Veronica Mittal, Trifecta Capital

Veronica Mittal, Trifecta Capital

Founder & Managing Director, Trifecta Capital
Veronica previously apprenticed in venture at S-Cubed Capital under Mark Stevens, former Managing Partner at Sequoia Capital. While at S-Cubed, Veronica sourced deals in Secret, Second Spectrum and Embark (acq. by APPL). She served attended board meetings for Elemental Technologies... Read More →
avatar for Upal Basu, NGP Capital

Upal Basu, NGP Capital

Partner, NGP Capital
Upal has worked in the mobile and software technology industry for over 20 years. At NGP Capital, Upal leads the global Connected Enterprise investing theme, where he focuses on mobile enterprise and Internet of Things investments. In addition he is responsible for managing NGP’s... Read More →
avatar for Catherine Lu, Spike Ventures

Catherine Lu, Spike Ventures

Principal, Spike Ventures
Catherine is an entrepreneur-turned-investor. She is currently a Principal at Spike Ventures, a VC firm that invests in Stanford alum-led companies. Previously, she was Director of Product at NEA-backed Datavisor, an enterprise company offering an unsupervised machine learning fraud... Read More →
avatar for Ajay Singh, Samsung NEXT Ventures

Ajay Singh, Samsung NEXT Ventures

Director, Samsung NEXT Ventures
Ajay Singh is a Director at Samsung NEXT Ventures. Based in Silicon Valley, Ajay focuses on early stage investments in software and services, particularly in artificial intelligence and emerging tech areas such as augmented reality and virtual reality. Ajay has over 12 years of investment... Read More →


Friday January 25, 2019 1:50pm - 2:20pm
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

2:00pm

End-to-End Conversational System for Customer Service Application
Goal-oriented conversational systems are typically multi-turn, relying on the entire conversation thus far to generate a response to user input. Many of these systems use dialog state tracking or belief tracking, to either rank candidate responses from a pool of templates or generate responses directly while others are end-to-end. End-to-end models for goal-oriented conversational systems have become an increasingly active area of research.
In this talk, I will present our recent efforts to build end-to-end conversational models for customer service application. We use historical chat transcripts and customer profile data to build models, and test with live customers using a human-in-the-loop research platform. We experiment with sequence-to-sequence model that generates responses word by word, and multi-encoder based ranking model to score template responses. I will compare these approaches as they apply to customer service domain.

Speakers
avatar for Manisha Srivastava, Amazon Customer Service

Manisha Srivastava, Amazon Customer Service

Machine Learning Scientist, Amazon Customer Service
Manisha Srivastava is a machine learning scientist at Amazon Customer Service, working to improve the customer experience using NLP techniques. Prior to Amazon she worked at TripAdvisor, focusing on using machine learning to improve the quality of business listings. She received her... Read More →


Friday January 25, 2019 2:00pm - 2:20pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

2:10pm

Extended Q&A: Practical Next Steps Towards Ethical AI
A 'town-hall' session format where attendees will have the opportunity to ask experts their questions and practical concerns, and to offer some key takeaways and best practice for attendees to apply in their own work.

Speakers
avatar for Ali Shah, BBC

Ali Shah, BBC

BBC Head of Emerging Technology and Strategic Direction, BBC
Ali helps the BBC make sense of the technologies and trends that will shape society and impact the BBC. He has a particular focus on AI, and is leading on the development of the BBC's AI capability - ensuring AI services developed by the BBC are done so under an ethical framework... Read More →
avatar for Deborah Harrison, Microsoft

Deborah Harrison, Microsoft

Senior Conversational UI Design Manager, Microsoft
Deborah Harrison (writer, Microsoft) is one of the original architects of the personality for Microsoft's digital assistant, Cortana. She crafted the core principles that define Cortana's approach to communication and now helps shepherd those principles as Cortana lights up on other... Read More →
avatar for Ben Roome, Ethical Resolve

Ben Roome, Ethical Resolve

Founder & Artificial Intelligence Ethicist, Ethical Resolve
As a data ethicist and responsible AI consultant at Ethical Resolve, Ben focuses on responsible AI strategy, quantitative and qualitative analysis and the future of technology. Ben is also the founder of an ed tech start up called Badge List. In this role Ben faces many of the same... Read More →
avatar for David Gunkel, Northern Illinois University

David Gunkel, Northern Illinois University

Distinguished Teaching Professor, Northern Illinois University
David J. Gunkel is an award-winning educator and scholar, specializing in the ethics of new and emerging technology. He is the author of over 70 scholarly articles and has published nine books, including Thinking Otherwise: Philosophy, Communication, Technology (Purdue University... Read More →


Friday January 25, 2019 2:10pm - 3:00pm
Pacific I-K Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

2:20pm

Human and Artificial Intelligence in Healthcare
The combination of breakthroughs in AI and Machine Learning and increasing amounts of digitized medical data have generated significant excitement about the potential to automate medical decision making processes. Among these, there are significant opportunities in designing solutions for settings where AI and ML systems can work seamlessly with human experts to provide more efficient and accurate patient care. In this talk, I outline one such problem, that of medical expert disagreement. We study the application of machine learning to predict patient cases which are likely to give rise to maximal expert disagreement. We show one can develop and train AI models to predict an uncertainty score for a patient, identifying cases where large disagreements ensue, and flagging that patient for a medical second opinion. Methodologically, we formalize the importance of doing direct prediction of these uncertainty scores, instead of a two step process of diagnosis and postprocessing, evaluating on a  gold-standard adjudicated dataset.

Speakers
avatar for Maithra Raghu, Google Brain/Cornell University

Maithra Raghu, Google Brain/Cornell University

Research Scientist, Google Brain/Cornell University
Maithra Raghu is a PhD Candidate in Computer Science at Cornell University, and a Research Scientist at Google Brain. Her research interests are in developing principled tools to empirically study the representational properties of deep neural networks, and apply these insights to... Read More →


Friday January 25, 2019 2:20pm - 2:40pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

2:20pm

Meet the Investors 
Speakers
avatar for Vijay Reddy, Intel Capital

Vijay Reddy, Intel Capital

Investment Director, Intel Capital
Vijay Reddy leads investments in Artificial Intelligence platforms and applications. Vijay is a board observer and/or has responsibility for several portfolio companies including Matroid, MightyAI, AEYE, Avaamo, Foghorn, Zumigo, Paperspace, Cognitive Scale etc. Previously Vijay sourced... Read More →
avatar for Ashu Garg, Foundation Capital

Ashu Garg, Foundation Capital

General Partner, Foundation Capital
Ashu Garg is a General Partner at Foundation Capital, focusing on startups in enterprise software, marketing technology (MarTech), AI-enabled business applications, data platforms, data center infrastructure, and online video. Before joining Foundation Capital in 2008, Ashu was the... Read More →
avatar for Upal Basu, NGP Capital

Upal Basu, NGP Capital

Partner, NGP Capital
Upal has worked in the mobile and software technology industry for over 20 years. At NGP Capital, Upal leads the global Connected Enterprise investing theme, where he focuses on mobile enterprise and Internet of Things investments. In addition he is responsible for managing NGP’s... Read More →
avatar for Catherine Lu, Spike Ventures

Catherine Lu, Spike Ventures

Principal, Spike Ventures
Catherine is an entrepreneur-turned-investor. She is currently a Principal at Spike Ventures, a VC firm that invests in Stanford alum-led companies. Previously, she was Director of Product at NEA-backed Datavisor, an enterprise company offering an unsupervised machine learning fraud... Read More →
avatar for Ajay Singh, Samsung NEXT Ventures

Ajay Singh, Samsung NEXT Ventures

Director, Samsung NEXT Ventures
Ajay Singh is a Director at Samsung NEXT Ventures. Based in Silicon Valley, Ajay focuses on early stage investments in software and services, particularly in artificial intelligence and emerging tech areas such as augmented reality and virtual reality. Ajay has over 12 years of investment... Read More →
avatar for Albert Wang, Qualcomm Ventures

Albert Wang, Qualcomm Ventures

Director, Qualcomm Ventures
Albert Wang is a Director at Qualcomm Ventures. His current investment areas are mobile, cloud, internet of things (IoT), and artificial intelligence (AI). Albert led the investments and currently serves as a board observer for AnyVision, AttackIQ, Avalanche Technology, BlueStacks... Read More →
avatar for Chris Neumann, Commonwealth Ventures

Chris Neumann, Commonwealth Ventures

Early-Stage Investor, Commonwealth Ventures
Chris Neumann is an early-stage investor who works with enterprise software companies in the US, Canada, and the UK.  Chris was formerly a Venture Partner at 500 Startups, where he launched the 500 Startups Data Track, a specialized program focused on accelerating enterprise data... Read More →


Friday January 25, 2019 2:20pm - 3:00pm
Pacific B-C Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

2:40pm

A Deep Learning Model for Early Prediction of the Diagnosis of Alzheimer Disease from 18F-FDG PET scan of the Brain
Over 5 million Americans are affected by Alzheimer's disease and have cost over 200 billion dollars in direct and indirect costs . Early and accurate diagnosis of Alzheimer's disease is important because it opens the possibility of therapeutic intervention to slow or halt the disease progression. Unfortunately, Alzheimer disease (AD) remains a diagnosis based on clinical grounds and most diagnosis gets established at a late stage when too many neurons have been lost. Much research effort has been made on biochemical and imaging tests
to improve our early diagnostic capability but most have met with mild to moderate accuracy. 18F-FDG PET scans of the brain utilize radioactive glucose to image the energy uptake pattern in various parts of the brain, which has recently been implicated to change in subtle ways in Alzheimer's disease. In this study, we develop and validate a deep learning algorithm that predicts the final diagnosis of Alzheimer disease (AD), mild cognitive impairment, or neither, approximately 6 years before the final diagnosis from these PET scans.

Prospective 18F-FDG PET brain images from the Alzheimer's Disease Neuroimaging Initiative (ADNI) (2109 imaging studies from 2005 to 2017, 1002 patients) and retrospective independent test set (40 imaging studies from 2006 to 2016, 40 patients) were collected. Final clinical diagnosis at follow-up was recorded. Convolutional neural network of Inception architecture was trained on 90% of ADNI data set and tested on the remaining 10%, as well as the independent test set, with performance compared to radiologic readers. Model was analyzed with sensitivity, specificity, receiver operating characteristic (ROC), saliency map, and t-distributed stochastic neighbor embedding. The algorithm achieved area under the ROC curve of 0.98 (95% confidence interval: 0.94, 1.00) when evaluated on predicting the final clinical diagnosis of AD in the independent test set (82% specificity at 100% sensitivity), an average of 75.8 months prior to the final diagnosis, which in ROC space outperformed reader performance (57% [four of seven] sensitivity, 91% [30 of 33] specificity; P < .05). Saliency map demonstrated attention to known areas of interest but with focus on the entire brain.

By using fluorine 18 fluorodeoxyglucose PET of the brain, a deep learning algorithm developed for early prediction of Alzheimer disease achieved 82% specificity at 100% sensitivity, an average of 75.8 months prior to the final diagnosis.


Speakers
avatar for Jae Ho Sohn, UCSF Medical Center

Jae Ho Sohn, UCSF Medical Center

Radiology Resident, UCSF Medical Center
Jae Ho Sohn, MD, MS is a radiology resident at UCSF Medical Center. As a physician with engineering background, his research focuses on the intersection of big data and radiology. He and his team has been working on a number of computer vision and natural language processing algorithms... Read More →


Friday January 25, 2019 2:40pm - 3:00pm
Grand Ballroom Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA

3:00pm

END OF SUMMIT
Friday January 25, 2019 3:00pm - 3:00pm
Grand Ballroom Foyer Hyatt Regency San Francisco, 5 Embarcadero Center, San Francisco, CA 94111, USA