Artificial intelligence is changing every business.
Don't be left behind.

March 27-28, 2017
St. Regis Hotel
San Francisco, CA

About

AI already impacts every industry, and human-machine interaction is becoming increasingly natural and intuitive. Yet, it’s difficult to discern facts from hype. EmTech Digital does just that–giving you the business intelligence you need in this rapidly shifting landscape. Together, we’ll forge ahead on the discussions started at the conference last spring: What are the key developments of the past year? How will their commercialization affect you? What can you do right now to stay ahead?

At EmTech Digital you’ll:

Learn how to harness new technologies to build a competitive business advantage: increase revenue, ensure security, make the best hires in a changing workforce.

Gain clear business insights that help you cut through the noise around artificial intelligence and big data in order to chart your strategy.

Meet the sharpest minds in the technology, engineering, academic, startup, and management communities–the people leading the next wave of intelligent technologies.

This Year's Themes

EmTech Digital examines established and emerging artificial-intelligence techniques and explores how every industry will feel the impact of these developments.

- The State of AI
Artificial intelligence technologies already automate many of our day-to-day experiences. We’ll explore lessons learned from early applications and look ahead at ground-breaking research into natural language recognition and robots that learn from and teach each other.

- Business in the Age of AI
As artificial intelligence moves into commercial environments, expectations of the systems we interact with each day are changing quickly. Leading experts explain the impact that AI already makes in business and predict how we can expect it to change the face of industries like health care, manufacturing, transportation, enterprise IT, and the creative arts around the world.

Speakers

The innovators at the heart of the next wave of the digital revolution are here.

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  • George
    Babu

    Cofounder and Chief Product Officer, Kindred

    How a Human-Machine Mind Meld Could Make Robots Smarter

    George Babu is a tech entrepreneur, investor, and former venture capitalist fascinated by technology's impact on our lives, iconic blockbuster products that once seemed like science fiction, and teams that overcome insurmountable odds to bring products and technologies to market that impact the lives of billions around the world.
  • John
    Ball

    SVP & GM, Salesforce Einstein

    AI in the Enterprise

    John Ball has deep expertise in analytics and CRM applications and a proven track record of success in driving rapid growth at highly innovative companies. As general manager of Salesforce Einstein, John oversees the innovation and product direction of delivering AI to the Customer Success Platform. Prior to his current role, John was the CEO of KXEN for four years; he was instrumental in leading its transition from a tools company to a predictive applications company. Before joining KXEN, John served in several executive roles at Salesforce, including vice president and general manager for analytics and reporting products and vice president and general manager for Service Cloud. Before Salesforce, John was also the founder and CEO of Netonomy, the leading provider of customer self-service solutions for the telecommunications industry, and also held a number of executive roles at Business Objects, including general manager for Web products. He has master's degrees in electrical engineering from Georgia Tech and Ecole Supérieure de l'Electricité.
  • Elizabeth
    Bramson-Boudreau

    Chief Operating Officer, MIT Technology Review

    Elizabeth Bramson-Boudreau is the Chief Operating Officer of MIT Technology Review, a digitally oriented media company founded by MIT whose analysis, features, reviews, interviews, and live events explain the commercial, social, and political impact of new technologies.

    At MIT Technology Review Elizabeth has overall operational responsibility for new and existing programs and integrated product development efforts, providing leadership for the strategic planning process.

    Elizabeth has a nearly 20-year background building and running teams in world-leading media companies. She has specialized knowledge about how media companies are commercializing content in new ways to appeal to discerning, demanding consumer and B2B audiences.

    Prior to joining MIT Technology Review, Elizabeth was the global managing director of the Economist Corporate Network (whose parent company publishes The Economist magazine), where she led editorial content creation, sales, marketing, and event operations. She spent a decade working as a consultant.

    Elizabeth has presented to corporate audiences of all different types and has chaired conferences in front of audiences as large as 500 people.

    Elizabeth holds an Executive MBA from the London Business School, an MSc from the London School of Economics, and a Bachelor’s degree from Swarthmore College.
  • Adam
    Bry

    CEO, Skydio

    Autonomous Drones as Airborne Assistants

    Adam Bry is cofounder and CEO of Skydio, a venture-backed drone startup based in the Bay Area. Prior to Skydio he helped start Project Wing at Google[x], where he worked on the flight algorithms and software. He holds an SM in aero/astro from MIT and a BS in mechanical engineering from Olin College. Adam grew up flying radio-controlled airplanes and is a former national champion in precision aerobatics

    Adam was honored as one of MIT Technology Review’s Innovators Under 35 for 2016. Read more about his honor.
  • Adam
    Coates

    Director, Silicon Valley AI Lab, Baidu

    AI for 100 million people with Deep Learning

    Adam Coates is director of the Silicon Valley AI Lab at Baidu.

    Adam was a post-doctoral researcher at Stanford University in Computer Science.

    His research interests include deep learning and feature learning, HPC systems for ML, perception and vision, and reinforcement learning.
  • Pedro
    Domingos

    Professor, University of Washington

    Building Machines That Will Learn, Discover, and Adapt

    Pedro Domingos is a professor of computer science at the University of Washington and the author of The Master Algorithm. He is a winner of the SIGKDD Innovation Award, the highest honor in data science, and a fellow of the Association for the Advancement of Artificial Intelligence. He has received a Fulbright Scholarship, a Sloan Fellowship, the National Science Foundation’s CAREER Award, and numerous best-paper awards. His research spans a wide variety of topics in machine learning, artificial intelligence, and data science, including scaling learning algorithms to big data, maximizing word of mouth in social networks, unifying logic and probability, and deep learning.
  • Douglas
    Eck

    Senior Staff Research Scientist, Google Brain

    Creative Machines

    Douglas Eck is a Research Scientist at Google working in the areas of music and machine learning. Currently, he is leading the Magenta Project, a Google Brain effort to generate music, video, images, and text using deep learning and reinforcement learning. One of the primary goals of Magenta is to better understand how machine learning algorithms can learn to produce more compelling media based on feedback from artists, musicians, and consumers. Doug led the Search, Recommendations, and Discovery team for Play Music from the product's inception as Music Beta by Google through its launch as a subscription service. Before joining Google in 2010, Doug was an Associate Professor in Computer Science at University of Montreal (MILA lab) where he worked on rhythm and meter perception, machine learning models of music performance, and automatic annotation of large audio data sets.
  • Dario
    Gil

    Vice President, Science & Solutions, IBM Research

    The Future of Discovery

    Dr. Gil is Vice President of Science and Solutions at IBM Research. He has direct responsibility for IBM’s science agenda, spanning the physical, mathematical, and life sciences and for IBM’s cognitive solutions research agenda, which aims to incubate future businesses. Prior to his current role, Dr. Gil was the Director of Symbiotic Cognitive Systems, where he led the creation of the Cognitive Environments Laboratory, the IBM Research THINK Lab and the IBM Watson Experience Center. Dr. Gil is also the creator and Founding Director of two research consortia: the IBM Research Frontiers Institute and the Smarter Energy Research Institute. An expert in the field of nanofabrication, he led the team that built the world's first microprocessor with immersion lithography. Dr. Gil is a frequent speaker at business events, conferences (including TED), and research universities. He received his Ph.D. in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology.
  • Noah
    Goodman

    Associate Professor of Psychology and Computer Science, Stanford University

    Abstract, Uncertain, Social: The Keys to Intelligence

    Noah D. Goodman studies the computational basis of natural and artificial intelligence, merging behavioral experiments with formal methods from statistics and programming languages. His research topics include language understanding, social reasoning, concept learning, probabilistic programming languages, and applications. Professor Goodman received his PhD in mathematics from the University of Texas at Austin in 2003. In 2005 he entered cognitive science, working as a postdoc and research scientist at MIT. In 2010 he moved to Stanford, where he runs the Computation and Cognition Lab. Professor Goodman has published more than 150 papers in fields including psychology, linguistics, computer science, and mathematics. His work has been recognized by the James S. McDonnell Foundation Scholar Award, the Roger N. Shepard Distinguished Visiting Scholar Award, the Alfred P. Sloan Research Fellowship in Neuroscience, and six computational modeling prizes from the Cognitive Science Society. He is a fellow of the Uber AI Labs, academic cofounder and advisor of Gamalon Labs, and advisor to several other startups.
  • Maya
    Gupta

    Machine Learning Researcher, Google

    Fairness and ML

    Gupta founded and runs the GlassBox ML R&D team in Google Research, focused on making machine learning systems more transparent, more predictable, and easier to control. GlassBox collaborates with product groups across Google to solve practical machine learning problems and deliver state-of-the art machine learning solutions. Before joining Google in 2012, Gupta was professor at the University of Washington for ten years (tenured in 2009). Gupta holds a PhD in Electrical Engineering from Stanford University. Notable awards include the PECASE award from Pres. G.W. Bush for her work in classifying random signals in 2007, the 2007 Office of Naval Research YIP Award, and a National Science Foundation Graduate Fellowship. She has also worked for Ricoh's California Research Lab, NATO's Undersea Research Center, Hewlett Packard R&D, and AT&T Labs, and founded and runs Artifact Puzzles.
  • Andy
    Hickl

    Chief Product Officer, Saffron AI Solutions Group, Intel

    Presented by Saffron Technology, an Intel Company

    Andy Hickl is the Chief Product Officer at Intel’s Saffron AI Solutions Group. Prior to Intel, Andy was a Senior Director for Innovation at Vulcan Inc., where he led development in artificial intelligence and natural language processing. Andy has also co-founded three startups around natural language technology: A.R.O. Inc. (Vulcan Ventures, Paul Allen), Swingly, and Extractiv. He also served as CEO of Language Computer Corporation, a natural language processing company. His work can be found in the proceedings of AAAI, ACL, SIGIR, and NIPS.
  • Eric
    Horvitz

    Technical Fellow and Managing Director, Microsoft Research

    The Long View: AI Directions, Challenges, and Futures

    Eric is a technical fellow and the managing director of the Microsoft Research lab at Redmond, balancing lab-wide responsibilities with ongoing research on machine intelligence and on opportunities to leverage the complementarities of human and machine intelligence. Eric’s ongoing research builds on representations of probability and utility, focusing on identifying ideal actions under conditions of uncertainty and bounded informational, computational, and cognitive resources. Beyond curiosity-driven research on foundations of machine perception, learning, and reasoning, he is excited about building real-world systems that provide value to people, organizations, and society, working in areas including human-computer interaction, information retrieval, health care, transportation, operating systems, and aerospace. Microsoft is a founding member of the Partnership on Artificial Intelligence to Benefit People and Society. Eric serves as its interim co-chair.
  • Will
    Knight

    Senior Editor for AI, MIT Technology Review

    Will Knight is a senior editor at MIT Technology Review, covering artificial intelligence, machine learning, robotics, self-driving cars, and human-machine collaboration. Will grew up in London, and was previously an editor at New Scientist magazine in the UK.
  • Peter
    Lee

    Corporate Vice President, Microsoft Research

    Lab to Market: Machine Learning in Practice

    Peter Lee, corporate vice president at Microsoft, brings research into the world through mission-focused technology projects, spanning deep neural networks, speech translation, FPGA-powered clouds, quantum computing, undersea data centers, augmented reality, DNA storage, and AI chatbots. Previously, he led the DARPA Network Challenge, mobilizing millions to hunt for weather balloons—a groundbreaking experiment in open innovation. He was also formerly head of Carnegie Mellon’s computer science department. As a thought leader in technology innovation, Dr. Lee has led studies on the effect of research on economic growth for the National Research Council and testified before the House Science and Technology Committee and Senate Commerce Committee on the impact of research on the nation’s competitiveness. In 2016, he was appointed to the President’s Cybersecurity Commission. Dr. Lee has been widely quoted on technology innovation by the New York Times, MIT Technology Review, Wired, Fast Company, the Economist, Ars Technica, CNN, and more.
  • Vikram
    Mahidhar

    SVP, Artificial Intelligence Solutions, RAGE Frameworks

    Presented by RAGE Frameworks

    Vikram heads up the semantic intelligence business at RAGE Frameworks. He is responsible for establishing go-to-market strategy, building strategic relationships, shaping products, and managing P&L for the business. He is passionate about solving big business transformation problems using semantic intelligence, big data, machine learning, analytics, and automation. Prior to joining RAGE Frameworks, Vikram was a director at Deloitte.
  • Gary
    Marcus

    Professor of Psychology and Neural Science, NYU; Founder, Geometric Intelligence (acquired by Uber)

    Artificial General Intelligence: Why Aren’t We There Yet?

    Gary Marcus, a scientist, best-selling author, and entrepreneur, is a professor of psychology and neural science at NYU and the founder of Geometric Intelligence (acquired by Uber). His research on language, computation, artificial intelligence, and cognitive development has been published widely, in leading journals such as Science and Nature. He is also the author of four books, including The Algebraic Mind, Kluge: The Haphazard Evolution of the Human Mind, and the New York Times best-seller Guitar Zero. He contributes frequently to the New Yorker and the New York Times.
  • Jason
    Pontin

    Editor in Chief and Publisher, MIT Technology Review

    As editor in chief, Jason Pontin is responsible for the editorial direction, media platforms, and business strategy of MIT Technology Review, including the rapidly expanding U.S. and international websites, the award-winning print magazine, videos, newsletters, business reports, and live events such as EmTech, the company’s annual conference focused on emerging technologies. He also serves as chairman of its international entrepreneurial network, MIT Enterprise Forum. Mr. Pontin joined MIT Technology Review in 2004 as its editor and was named publisher in August 2005. Mr. Pontin was born in London and raised in Northern California. He was educated in England, at Harrow School and Oxford University.
  • Kimberly
    Powell

    Senior Director of Deep Learning, Nvidia

    AI-Driven Health Care

    Kimberly Powell is the senior director of deep learning at Nvidia, where she leads global business development and strategic alliance strategies to bring deep learning, data analytics, and AI to every industry.
  • Toni
    Reid

    Vice President of Alexa, Amazon

    The Evolution of Alexa

    Toni Reid oversees the product development teams for Echo devices and Alexa customer experience. Reid joined Amazon in 1998 as a recruiter and has worked on several Amazon teams since then, including Amazon Fresh, IMDb, and Amazon Media Group. She earned her bachelor’s degree in anthropology from the University of North Texas.
  • Carol
    Reiley

    President, Drive.ai

    Robots on the Road: AI in Autonomous Vehicles

    Carol is the cofounder and president of Drive.ai, a startup using deep learning to develop the software that will power the autonomous transportation of the future. She has studied human-robot interaction extensively and worked in surgical and underwater robotics. She is also an active advocate for diversity and education in tech.
  • Lior
    Ron

    Cofounder and President, Otto

    The Future of Transportation

    Lior Ron, cofounder and president of Otto, has been at the helm of some of the most exciting technological developments of the past decade. He began his career as the CTO for Israeli Army Intelligence before joining Google in 2007. There he became the product lead for Google Maps, helping to scale the business from 10 million to one billion users and to launch products including My Maps, Google Map Maker, and Google Local. After Google acquired Motorola in 2011, Lior was the first Googler recruited to transform Motorola products, launching the award-winning Moto X and Moto 360 product lines. Before leaving Google in late 2015, Lior served as an advisor to Alphabet. He has a BS and MS from Technion and an MBA from Stanford.
  • Francesca
    Rossi

    Distinguished Research Staff Member, IBM Research; Professor of Computer Science, University of Padova

    AI and the Art of Social Responsibility

    Francesca Rossi is a research scientist at the IBM T.J. Watson Research Center and a professor of computer science at the University of Padova, Italy, currently on leave. Her research interests focus on artificial intelligence, specifically constraint reasoning, preferences, multi-agent systems, computational social choice, and collective decision making. She is also interested in ethical issues in the development and behavior of AI systems. She has published over 170 scientific articles in journals and conference proceedings, and as book chapters. She is editor in chief of the Journal of Artificial Intelligence Research, co-chairs the AAAI committee on AI and ethics, and is a member of the scientific advisory board of the Future of Life Institute. She is on the executive committee of the IEEE global initiative on ethical considerations in the development of autonomous and intelligent systems, and she belongs to the World Economic Forum Council on AI and robotics. She has given several media interviews about the future of AI and AI ethics to the Wall Street Journal, the Washington Post, Motherboard, Science, the Economist, CNBC, Eurovision, Corriere della Sera, and La Repubblica and has delivered three TEDx talks on these topics.
  • Ruslan
    Salakhutdinov

    Associate Professor, CMU; Director of AI Research, Apple

    Testing the Limitations of Machine Learning

    Ruslan Salakhutdinov received his PhD in computer science from the University of Toronto in 2009. After spending two postdoctoral years at the Massachusetts Institute of Technology Artificial Intelligence Lab, he joined the University of Toronto as an assistant professor in the Departments of Statistics and Computer Science. In 2016 he joined the Machine Learning Department at Carnegie Mellon University as an associate professor. Ruslan's primary interests lie in deep learning, machine learning, and large-scale optimization. His main research goal is to understand the computational and statistical principles required for discovering structure in large amounts of data. He is an action editor of the Journal of Machine Learning Research and served on the senior program committee of several learning conferences, including NIPS and ICML. He is an Alfred P. Sloan Research Fellow, a Microsoft Research Faculty Fellow, a Canada Research Chair in Statistical Machine Learning, a senior fellow of the Canadian Institute for Advanced Research, and a recipient of the Early Researcher Award, Connaught New Researcher Award, Google Faculty Award, and Nvidia's Pioneers of AI award.
  • Tom
    Simonite

    San Francisco Bureau Chief, MIT Technology Review

    Tom Simonite is MIT Technology Review's San Francisco bureau chief. He leads coverage of new computing and Internet technologies emerging from Silicon Valley and has been reporting on the development of Bitcoin and blockchain technologies since 2011.
  • Richard
    Socher

    Chief Scientist, Salesforce

    AI in the Enterprise

    Richard Socher is chief scientist at Salesforce. He leads the company’s research efforts and works on bringing state-of-the-art artificial-intelligence solutions to Salesforce. Previously, Socher was the CEO and founder of MetaMind, a startup acquired by Salesforce in April 2016. MetaMind’s deep-learning AI platform analyzes, labels, and makes predictions on image and text data so businesses can make smarter, faster, and more accurate decisions. Socher was awarded the Distinguished Application Paper Award at the International Conference on Machine Learning (ICML) in 2011, the 2011 Yahoo Key Scientific Challenges Award, a Microsoft Research PhD Fellowship in 2012, a 2013 "Magic Grant" from the Brown Institute for Media Innovation, and the 2014 GigaOM Structure Award. He obtained his PhD from Stanford, working on deep learning with Chris Manning and Andrew Ng, and won the best Stanford CS PhD thesis award.
  • Martin
    Stumpe

    Technical Lead Manager, Google Research

    AI in Medical Diagnostics

    Martin leads the Pathology project at Google Research. Before that, he worked on Google Street View for automatically building maps using machine learning. Prior to joining Google, Martin worked on NASA's Kepler Mission to detect extrasolar planets, and started a business with a computer vision tracking software, AnTracks. His background is in Physics, in which he graduated with a PhD at the Max-Planck-Institute in Goettingen, Germany, researching the molecular mechanisms of protein folding and stability, a topic that he continued during his postdoc research at Stanford University.
  • Ilya
    Sutskever

    Cofounder and Research Director, OpenAI

    The State of AI

    Ilya Sutskever is Cofounder and Research Director of OpenAI. Prior to OpenAI, he was a Research Scientist on the Google Brain Team. Before that, he was a cofounder of DNNresearch.

    Ilya was a student in the Machine Learning group at the University of Toronto and a postdoc at Stanford University.
  • Sameep
    Tandon

    Cofounder and CEO, Drive.ai

    Robots on the Road: AI in Autonomous Vehicles

    Sameep is the Chief Executive Officer and Cofounder of Drive.ai. He was previously a PhD candidate at Stanford’s Artificial Intelligence Lab, where he led research in Deep Learning for Self Driving Vehicles. He is a recipient of the Stanford School of Engineering Fellowship and the Mark D. Weiser Excellence in Computing Scholarship.
  • Ben
    Vigoda

    Founder & CEO/CTO, Gamalon

    When Machines Have Ideas

    Before founding Gamalon Machine Intelligence, Ben was the technical co-founder and CEO of Lyric Semiconductor, a startup that created the first integrated circuits and processor architectures for statistical machine learning and signal processing. Ben also co-founded Design That Matters, a not-for-profit that for the past decade has helped solve engineering and design problems in under-served communities.

    Ben completed his PhD at MIT developing circuits for implementing machine learning algorithms natively in hardware. He has won entrepreneurship competitions at MIT and Harvard, fellowships from Intel and the Kavli Foundation/National Academy of Sciences, and has held research appointments at MIT, HP, Mitsubishi, and the Santa Fe Institute. He has authored over 120 patents and academic publications. He recently served on the DARPA Information Science and Technology (ISAT) steering committee.

  • Jianxiong
    Xiao

    CEO, AutoX, Inc.

    Democratizing Autonomous Driving

    Jianxiong Xiao (a.k.a., Professor X) is the Founder and CEO of AutoX, Inc., a high-tech startup currently in stealth mode. Previously, he was an Assistant Professor in the Department of Computer Science at Princeton University and the founding director of the Princeton Computer Vision and Robotics Labs from 2013 to 2016. He received his Ph.D. from the Computer Science and Artificial Intelligence Laboratory (CSAIL) at the Massachusetts Institute of Technology (MIT) in 2013. Before that, he received a BEng. and MPhil. in Computer Science from the Hong Kong University of Science and Technology in 2009. His research focuses on bridging the gap between computer vision and robotics by building extremely robust and dependable computer vision systems for robot perception. In particular, he is a pioneer in the fields of 3D Deep Learning, Autonomous Driving, RGB-D Recognition and Mapping, Big Data, Large-scale Crowdsourcing, and Deep Learning for Robotics.
  • Matthew
    Zeiler

    Founder/CEO, Clarifai

    Next-Generation Computer Vision at Work

    Matthew Zeiler is an artificial-intelligence expert with a PhD in machine learning from NYU. His groundbreaking research in visual recognition, conducted alongside renowned machine-learning pioneers Geoff Hinton and Yann LeCun, has propelled the image recognition industry from theory to real-world practice. As the founder of Clarifai, Matt is applying his award-winning research to create the best visual recognition solutions for businesses and developers and power the next generation of intelligent apps. Reach him @MattZeiler.

Who Should Attend

EmTech Digital is for senior executives responsible for information, technology, security, strategy, and marketing–those charged with driving innovation and product development across industries and sectors within their business.

EmTech Digital is a must-attend for:
- C-Level Executives
- Heads of Innovation
- VC/Investors
- VPs of Strategy
- VPs of Product Planning
- R&D Specialists
- IT Decision Makers

EmTech Digital 2017 Schedule

It’s not another lecture … it’s an invitation to join the conversation.

Monday, March 27, 2017

  • 8:00
    Registration & Breakfast
  • 9:00
    Opening Remarks

    A welcome from MIT Technology Review’s editor in chief and publisher, our EmTech Digital emcee.

    Jason Pontin Editor in Chief and Publisher, MIT Technology Review
  • 9:10
    The State of AI
    Ilya Sutskever Cofounder and Research Director, OpenAI
    The State of AI
    Adam Coates Director, Silicon Valley AI Lab, Baidu
    AI for 100 million people with Deep Learning
    Gary Marcus Professor of Psychology and Neural Science, NYU; Founder, Geometric Intelligence (acquired by Uber)
    Artificial General Intelligence: Why Aren’t We There Yet?
  • 10:30
    Break & Networking
  • 11:00
    The Road to Autonomous Vehicles

    Autonomous vehicles will change the way we get around town, but they will also transform the shipping industry. Hear from the companies at the heart of automating vehicles, from cars to big rigs.

    Lior Ron Cofounder and President, Otto
    The Future of Transportation
    Carol Reiley President, Drive.ai
    Robots on the Road: AI in Autonomous Vehicles
    Sameep Tandon Cofounder and CEO, Drive.ai
    Robots on the Road: AI in Autonomous Vehicles
    Jianxiong Xiao CEO, AutoX, Inc.
    Democratizing Autonomous Driving
  • 12:30
    Lunch & Networking

    Lunchtime Programming: Is AI ready today to solve enterprise business problems?
    This session will explore what areas of business enterprise are effectively able to use AI. What are the success stories? What are the challenges? What business/knowledge processes are delivering results? The discussion will continue into extraction, classification, and interpretation of unstructured data, and why automation componentry is critical for the success of AI projects.

    Vikram Mahidhar SVP, Artificial Intelligence Solutions, RAGE Frameworks
    Presented by RAGE Frameworks
  • 2:00
    AI in the Enterprise

    The commercialization of artificial intelligence has implications for every industry.

    Peter Lee Corporate Vice President, Microsoft Research
    Lab to Market: Machine Learning in Practice
  • 2:30
    AI in the Enterprise

    A lab-to-market examination of intelligent solutions, from lab research to deployment, in enterprises around the world.

    Richard Socher Chief Scientist, Salesforce
    AI in the Enterprise
    John Ball SVP & GM, Salesforce Einstein
    AI in the Enterprise
  • 3:00
    The Future of Discovery

    Working with Watson to accelerate the discovery of new materials with AI.

    Dario Gil Vice President, Science & Solutions, IBM Research
    The Future of Discovery
  • 3:30
    Break & Networking
  • 4:00
    AI’s Next Leap Forward

    AI-Driven Health Care.

    Hosted by Tom Simonite, MIT Technology Review

    Kimberly Powell Senior Director of Deep Learning, Nvidia
    AI-Driven Health Care
    Tom Simonite San Francisco Bureau Chief, MIT Technology Review
  • 4:30
    AI at Home

    The Evolution of Alexa: Insights from the rollout of Amazon’s widely adopted virtual assistant.

    Toni Reid Vice President of Alexa, Amazon
    The Evolution of Alexa
  • 5:15
    EmTech Digital Reception

Tuesday, March 28, 2017

  • 8:00
    Registration & Breakfast
  • 9:00
    Opening Remarks

    Day Two opens with a preview of the day from MIT Technology Review’s editor in chief and publisher, our EmTech emcee.

    Jason Pontin Editor in Chief and Publisher, MIT Technology Review
  • 9:10
    Learning Machines: A View from the Labs

    Leading academics provide insights gleaned from ongoing research that will ultimately lead to more natural collaboration between humans and machines.

    Pedro Domingos Professor, University of Washington
    Building Machines That Will Learn, Discover, and Adapt
    Noah Goodman Associate Professor of Psychology and Computer Science, Stanford University
    Abstract, Uncertain, Social: The Keys to Intelligence
    Ruslan Salakhutdinov Associate Professor, CMU; Director of AI Research, Apple
    Testing the Limitations of Machine Learning
  • 10:30
    Break & Networking
  • 11:00
    When Machines Have Ideas

    A lab-to-market examination of AI solutions putting corporate data to work.

    Hosted by Will Knight, MIT Technology Review

    Ben Vigoda Founder & CEO/CTO, Gamalon
    When Machines Have Ideas
    Will Knight Senior Editor for AI, MIT Technology Review
  • 11:20
    Technology Spotlight: Machine Vision

    The next frontier in machine vision promises some of the most practical uses for AI.

    Hosted by Tom Simonite, MIT Technology Review

    Martin Stumpe Technical Lead Manager, Google Research
    AI in Medical Diagnostics
    Matthew Zeiler Founder/CEO, Clarifai
    Next-Generation Computer Vision at Work
    Tom Simonite San Francisco Bureau Chief, MIT Technology Review
  • 12:00
    Lunch & Networking

    Lunchtime Programming: Managing Implicit Bias in AI Systems
    Intelligent systems can mimic human performance on many tasks, from playing video games to reasoning about situations in the real world. Whether it’s predicting failures in complex industrial environments or identifying the latest way crooks try to launder money, AI systems have learned a tremendous amount from their human creators in a very short time. This talk will focus on another thing that AI systems are inadvertently learning from us: implicit sources of bias and prejudice. Hear some of the ways in which bias can be integrated into supervised learning systems and see how explanation and interactivity – two hallmarks of Intel’s memory-based reasoning platform, Saffron – can be used to build more impartial expert systems.

    Andy Hickl Chief Product Officer, Saffron AI Solutions Group, Intel
    Presented by Saffron Technology, an Intel Company
    Elizabeth Bramson-Boudreau Chief Operating Officer, MIT Technology Review
  • 1:30
    Technology Spotlight: Autonomous Drones

    2016 Innovator Under 35 Adam Bry shares an update on his vision for autonomous drones as airborne assistants.

    Adam Bry CEO, Skydio
    Autonomous Drones as Airborne Assistants
  • 2:00
    Intelligent Machines

    How a human-machine mind meld could make robots smarter.

    George Babu Cofounder and Chief Product Officer, Kindred
    How a Human-Machine Mind Meld Could Make Robots Smarter
  • 2:30
    Creative Machines

    Can machines make music and art?

    Douglas Eck Senior Staff Research Scientist, Google Brain
    Creative Machines
  • 3:00
    Break & Networking
  • 3:30
    Ethics in AI

    An update from industry leaders at the forefront of examining the societal impact of AI and the efforts to ensure the development of ethical machines.

    Francesca Rossi Distinguished Research Staff Member, IBM Research; Professor of Computer Science, University of Padova
    AI and the Art of Social Responsibility
    Maya Gupta Machine Learning Researcher, Google
    Fairness and ML
    Eric Horvitz Technical Fellow and Managing Director, Microsoft Research
    The Long View: AI Directions, Challenges, and Futures
  • 5:00
    Closing Toast

St. Regis Hotel

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News + Views

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It’s Easy to Slip Toxic Language Past Alphabet’s Toxic-Comment Detector

Machine-learning algorithms are no match for the creativity of human insults.

Computing

For Hospitals That Can’t Afford a Surgical Robot, This $500 Device Could Fit the Bill

A tool that mounts to a surgeon’s arm could help with precise medical procedures at small or remote hospitals.

Computing

What Happens When Robots Become Role Models

Children can find their behavior shaped by robotic companions—so let’s not screw them up.

Machine learning

Playtime’s Over

Getting computers to beat humans at games is impressive. But now the real work begins.

A Tradition in Technology

For more than 115 years, MIT Technology Review has been identifying important new technologies and deciphering their practical impact.

We've brought that mission and our journalism to life through EmTech since 1999, gathering the sharpest minds in the technology, engineering, academic, startup, and management communities to provide insight into the innovations that shape the world and your business.

We host EmTech events in Asia, Brazil, USA, China, Colombia, Dominican Republic, France, Hong Kong, India, Mexico, and Spain.

Venue + Travel

March 27-28, 2017
St. Regis Hotel
San Francisco

St. Regis Hotel

The 5-star St. Regis San Francisco hotel embodies extraordinary hospitality with modern-day sophistication. This luxury hotel features 306 guest rooms and suites, all equipped with rainforest showers, minibars, and several flat-screen TVs (including one in the bathroom). You’ll find yourself in the heart of one of the city's most vibrant neighborhoods with the most exciting galleries, San Francisco attractions, events, restaurants, and shopping. The San Francisco Museum of Modern Art, the new Jewish Contemporary Museum, the financial district, and Union Square's select stores are all minutes away. A brief stroll takes you to the hill-climbing delights of the city's legendary cable cars, and the Golden Gate Bridge leads you to the bucolic charms of wine country.

Booking deadline is February 27, 2017

Hotel information

St. Regis Hotel

Discounted Conference Rate:
$425/night + tax
See more details

You may reserve your stay by calling the St. Regis Central Reservations line at 1-866-225-0397 and mentioning MIT Technology Review EmTech Digital. 

 

Make your reservation online here >>

 

Extending your stay? Please call the hotel directly to inquire about extending the discounted rates on shoulder nights.

 

The group rate is available until February 27, 2017.

Directions

The St. Regis San Francisco enjoys an artful address, just steps from the top things to do in San Francisco. The Museum of the African Diaspora, featuring the rich history of African art and culture, is conveniently located within the hotel. In addition, the renowned San Francisco Museum of Modern Art showcases noteworthy talent directly next door, and the vibrant new Jewish Contemporary Museum stands less than one block from the hotel. The financial district and Union Square's select stores are minutes away, offering a plethora of things to do in San Francisco. A brief stroll takes you to the hill-climbing delights of the city's legendary cable cars, and the Golden Gate Bridge leads you to the bucolic charms of wine country.

Driving from the North Bay

Sausalito, Tiburon, Muir Woods, Sonoma

• Take Highway 101 South over the Golden Gate Bridge.
• Follow signs towards Downtown San Francisco/Lombard Street.
• Continue on Lombard Street approximately 1.5 miles.
• Turn right onto Van Ness Avenue.
• Continue on Van Ness Avenue for 14 blocks, then turn left onto Bush Street.
• Continue on Bush Street for 12 blocks.
• Then turn right onto Montgomery Street.
• Continue on Montgomery Street and cross Market Street.
• Continue 2 more blocks to Howard Street. Turn right onto Howard Street.
• Proceed 1 block to Third Street and turn right.
• The St. Regis Hotel is located on the right side, 0.5 blocks after Howard Street. Immediately after the Museum of Modern Art, turn right onto Minna Street.

Driving from the South Bay

San Francisco International Airport, Santa Clara, San Jose, Monterey, Carmel

• Take Highway 101 North into San Francisco.
• Follow signs towards Bay Bridge onto Interstate 80 East.
• Take the last San Francisco Exit, which is Fourth Street.
• Continue through the light and turn left onto Third Street.
• Proceed along Third Street and continue for 3.5 blocks.
• The St. Regis Hotel is located on the right side, 0.5 blocks after Howard Street. Immediately after the Museum of Modern Art, turn right onto Minna Street.

Driving from Highway 280

• Take Interstate 280 North into San Francisco.
• Stay on the freeway until it ends onto King Street.
• Proceed several blocks to Third Street.
• Turn left onto Third Street
• Continue along Third Street for 6.5 blocks.
• The St. Regis Hotel is located on the right side, 0.5 blocks after Howard Street. Immediately after the Museum of Modern Art, turn right onto Minna Street.

Driving from East Bay

Oakland, Berkeley, Emeryville, Sacramento

• Take Interstate 80 West over the Bay Bridge into San Francisco.
• Take the first right exit, which is Fremont Street.
• Turn left onto Fremont Street. Proceed 0.5 blocks to Howard Street and turn left.
• Continue on Howard Street for 4 long blocks, and turn right onto Third Street.
• The St. Regis Hotel is located on the right side, 0.5 blocks after Howard Street. Immediately after the Museum of Modern Art, turn right onto Minna Street.

Driving from Oakland Airport

• Follow the signs for Interstate 880 North, towards downtown Oakland.
• Follow the signs towards San Francisco, Interstate 80 West.
• Proceed on I-80 West over the Bay Bridge, and follow the "Driving from East Bay" directions.

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