Put AI to work
June 26-27, 2017: Training
June 27-29, 2017: Tutorials & Conference
New York, NY

Sessions

O’Reilly Artificial Intelligence Conference sessions take place Wednesday, June 28 and Thursday, June 29.

Wednesday, June 28

11:05am11:45am Wednesday, June 28, 2017
Location: Grand Ballroom West
Secondary topics:  Deep Learning
Richard Socher (Salesforce)
Average rating: ****.
(4.60, 5 ratings)
Deep learning has made great progress in a variety of language tasks. However, there are still many practical and theoretical problems and limitations. Richard Socher shares some solutions. Read more.
11:05am11:45am Wednesday, June 28, 2017
Location: Beekman Level: Non-technical
Jana Eggers (Nara Logics)
Average rating: ***..
(3.20, 5 ratings)
AI has infinite possibilities, but to be adopted by businesses beyond R&D, these solutions must show results. The challenge is that AI often presents new opportunities that aren't easily quantified. Jana Eggers shares lessons learned while taking AI from ideas to results-delivering production solutions at various organizations, including Global 500 enterprises, tech companies, and nonprofits. Read more.
11:05am11:45am Wednesday, June 28, 2017
Location: Sutton South/Regent Parlor
Secondary topics:  Financial services, Natural Language
Jennifer Chu-Carroll (Elemental Cognition)
Average rating: ****.
(4.25, 4 ratings)
Why is reading comprehension hard? Jennifer Chu-Carroll offers an overview of current approaches, explaining where they fall short and what our ultimate expectations should be. Read more.
11:05am11:45am Wednesday, June 28, 2017
Location: Murray Hill E/W Level: Intermediate
Risto Miikkulainen (Sentient.ai)
Average rating: ****.
(4.50, 2 ratings)
Risto Miikkulainen explains how to use massively distributed evolutionary algorithms to evolve the actual architectures of deep networks. Read more.
11:05am11:45am Wednesday, June 28, 2017
Location: Gramercy East/West Level: Intermediate
Secondary topics:  Deep Learning, Financial services
Eric Greene (Think Big Analytics)
Average rating: **...
(2.67, 3 ratings)
Eric Greene compares different approaches to creating models that predict payment amounts, time, and recipient for recurring expenses such as rent, loans, utilities, and services, outlining the data requirements, feature modeling, and neural network architectures that work best, as well as common issues in training and deploying deep learning networks. Read more.
11:05am11:45am Wednesday, June 28, 2017
Location: Sutton Center
Hanlin Tang (Intel)
Average rating: ****.
(4.00, 1 rating)
Hanlin Tang offers an overview of the Intel Nervana deep learning stack and shares lessons learned from building deep learning solutions for multiple industries. Read more.
11:05am11:45am Wednesday, June 28, 2017
Location: Sutton North
Ryan Olson (NVIDIA)
Ryan Olson explores the role of accelerated GPU computing in modern deep neural networks and explains how it will enable the technologies of the future. Read more.
11:55am12:35pm Wednesday, June 28, 2017
Location: Grand Ballroom West
Matthew Ocko (Data Collective), Coco Krumme (Haven | UC Berkeley), Friederike Schuur (Fast Forward Labs), Gloria Lau (Unity Medical)
Join Matt Ocko in conversation with entrepreneurs Hilary Mason, Gloria Lau, and Coco Krumme for a "not your typical" VC panel. They'll discuss how to build disruptive companies that solve real problems with hard AI technologies, digging into the practicalities of getting started, raising money, landing that first big customer, and everything in between. Read more.
11:55am12:35pm Wednesday, June 28, 2017
Location: Gramercy East/West Level: Intermediate
Secondary topics:  Financial services
Aida Mehonic (The Alan Turing Institute)
Average rating: ****.
(4.67, 3 ratings)
Deploying AI across business functions brings benefits that range from the prosaic to game changers, which in turn also depend on the overall digital and data maturity of the organization. Aida Mehonic shares a case study of an investment firm undergoing an AI transformation across several business units, including trading, reporting, and marketing. Read more.
11:55am12:35pm Wednesday, June 28, 2017
Location: Beekman Level: Beginner
Christoph Peylo (Bosch Center for Artificial Intelligence)
Average rating: ***..
(3.00, 3 ratings)
Generating commercial value from AI in a highly sophisticated industrial environment is a challenge. So far, AI accomplishments in this field stem mostly from marketing rather than systematic application to product lifecycles. Christoph Peylo shares examples of meaningful commercial IoT deployments and discusses obstacles that still have to be overcome. Read more.
11:55am12:35pm Wednesday, June 28, 2017
Location: Sutton South/Regent Parlor
Secondary topics:  Media, Natural Language
Delip Rao (AI Foundation)
Average rating: ****.
(4.00, 5 ratings)
Not a single day goes by without a mention of "fake news" or the problems it causes. Delip Rao offers a nonpartisan overview of fake news, briefly exploring the technology landscape surrounding the content verification and validation problem and diving deeper into the Fake News Challenge and the stance detection problem. Read more.
11:55am12:35pm Wednesday, June 28, 2017
Location: Murray Hill E/W Level: Beginner
Secondary topics:  Machine Learning
Ben Vigoda (Gamalon)
Average rating: ***..
(3.00, 2 ratings)
Ben Vigoda introduces a new approach to machine learning called idea learning—teaching with ideas instead of labeled data—and demonstrates use cases with state-of-the-art performance in data applications involving structuring of product information, customer feedback, and AI/digital assistant requests. Read more.
11:55am12:35pm Wednesday, June 28, 2017
Location: Sutton Center
Damion Heredia (IBM Watson and Cloud Platform ), Bjorn Austraat (IBM)
Average rating: ***..
(3.67, 3 ratings)
Damion Heredia and Bjorn Austraat explore how augmented intelligence is helping companies disrupt industries and enabling them to make better decisions. Read more.
11:55am12:35pm Wednesday, June 28, 2017
Location: Sutton North
Pradeep Dubey (Intel Corporation)
We are witnessing a renewed industry interest in machine learning and artificial intelligence and an unprecedented convergence of massive compute with massive data. This confluence has the potential to significantly impact how we do computing and what computing can do for us. Pradeep Dubey shares some of the research Intel is pursuing to enable this compute industry transformation. Read more.
1:45pm2:25pm Wednesday, June 28, 2017
Location: Grand Ballroom West Level: Intermediate
Secondary topics:  Cloud, Deep Learning
Guy Ernest (Amazon Web Services)
Average rating: **...
(2.00, 1 rating)
AWS is democratizing AI, helping you build deep learning systems in any scale, in any team size and skill, and for every use case. Guy Ernest discusses the state of deep learning, the tools that can take advantage of its power, and best practices for building successful businesses in the cloud, including data handling, models learning, deployment, and integration to other parts of the business. Read more.
1:45pm2:25pm Wednesday, June 28, 2017
Location: Gramercy East/West
Greg Phalin (McKinsey & Company), Chetan Dube (IPsoft), Doug Kim (Cogito), Aida Mehonic (The Alan Turing Institute)
Average rating: ***..
(3.00, 2 ratings)
AI is changing every area of the financial industry, but the promise of improved performance is accompanied by looming challenges. Greg Phalin leads a panel discussion with Chetan Dube, Doug Kim, and Aida Mehonic on the future of the AI industry, the applicability of AI to use cases in financial services, and the headwinds that could slow adoption of AI at scale. Read more.
1:45pm2:25pm Wednesday, June 28, 2017
Location: Beekman
Kathryn Hume (integrate.ai)
Average rating: ****.
(4.33, 3 ratings)
Kathryn Hume explores the potential advantages and disadvantages of the AI hype bubble and offers practical tips on how to navigate between real innovation and total nonsense. Read more.
1:45pm2:25pm Wednesday, June 28, 2017
Location: Sutton South/Regent Parlor Level: Intermediate
Secondary topics:  Media, Natural Language
Kristian Hammond (Northwestern Computer Science)
Average rating: ***..
(3.83, 6 ratings)
Kristian Hammond offers an overview of advanced natural language generation (NLG), a subfield of artificial intelligence, and the assorted technical systems involved with this emerging technology, along with the mechanisms that drive them. Read more.
1:45pm2:25pm Wednesday, June 28, 2017
Location: Murray Hill E/W Level: Beginner
Secondary topics:  Machine Learning, User interface and experience
Anmol Jagetia (Media.net)
Average rating: **...
(2.33, 3 ratings)
Anmol Jagetia explains how to use OpenAI's Gym and Universe to design bots that can become extremely smart using reinforcement learning. You'll create a bot that uses reinforcement learning to beat games and learn how to reuse code to beat a set of games that includes Atari classics (Pac-Man or Pong), a Candy Crush clone, and a racing game. Read more.
1:45pm2:25pm Wednesday, June 28, 2017
Location: Sutton North
Rene Buest (Arago)
Average rating: **...
(2.33, 3 ratings)
The internet giants are fully embracing AI. The services they offer are all aimed at using data to draw a map of the world, and they are using AI to build disruptive approaches that can't be replicated by established enterprises, which are threatened by these disruptions. However, as Rene Buest explains, most leaders still underestimate the effect this will have on their businesses. Read more.
1:45pm2:25pm Wednesday, June 28, 2017
Location: Sutton Center
Erik Marcade (SAP)
Average rating: *....
(1.00, 1 rating)
Erik Marcade explains why machine learning and artificial intelligence aren't just revolutionizing industry and knowledge-worker jobs. They're also transforming the way enterprise software is designed and delivered to customers. Read more.
2:35pm3:15pm Wednesday, June 28, 2017
Location: Grand Ballroom West Level: Non-technical
Secondary topics:  Machine Learning, User interface and experience, Vision
Rana el Kaliouby (Affectiva)
Average rating: *****
(5.00, 2 ratings)
Emotion AI is a branch of artificial intelligence that brings emotional intelligence to AI systems. Rana el Kaliouby reviews the state of emotion AI, its commercial applications, its underlying deep learning methods, and the research roadmap, which includes multimodal emotion recognition and the idea of an emotion chip. Read more.
2:35pm3:15pm Wednesday, June 28, 2017
Location: Gramercy East/West Level: Intermediate
Secondary topics:  Financial services, Machine Learning
Ron Bodkin (Google), Nadeem Gulzar (Danske Bank Group)
Average rating: ****.
(4.33, 3 ratings)
Fraud in banking is an arms race with criminals using machine learning to improve their attack effectiveness. Ron Bodkin and Nadeem Gulzar explore how Danske Bank uses deep learning for better fraud detection, covering model effectiveness, TensorFlow versus boosted decision trees, operational considerations in training and deploying models, and lessons learned along the way. Read more.
2:35pm3:15pm Wednesday, June 28, 2017
Location: Beekman Level: Beginner
Secondary topics:  Natural Language, User interface and experience
Ben Medlock (Microsoft)
Average rating: *****
(5.00, 1 rating)
Ben Medlock explores the future of AI, explaining why the potential it holds is not at all frightening. Ben argues that the key to achieving elusive human-like AI lies in a central piece of the puzzle: embodiment. Read more.
2:35pm3:15pm Wednesday, June 28, 2017
Location: Sutton South/Regent Parlor Level: Beginner
Secondary topics:  Deep Learning, Natural Language, Speech and Voice, User interface and experience
Yishay Carmiel (IntelligentWire)
There has been a quantum leap in the performance of conversational AI. From speech recognition to machine translation and language understanding, deep learning made its mark. However, scaling and productizing these breakthroughs remains a big challenge. Yishay Carmiel shares techniques and tips on how to take advantage of large datasets, accelerate training, and create an end-to-end product. Read more.
2:35pm3:15pm Wednesday, June 28, 2017
Location: Murray Hill E/W Level: Intermediate
Secondary topics:  Machine Learning
Philipp Moritz (University of California, Berkeley), Robert Nishihara (University of California, Berkeley)
Average rating: *****
(5.00, 2 ratings)
AI applications are increasingly dynamic and interactive and work in real time. These properties impose new requirements on the distributed systems that support them. Philipp Moritz and Robert Nishihara offer an overview of Ray, a new system designed to support these emerging applications. Read more.
2:35pm3:15pm Wednesday, June 28, 2017
Location: Sutton Center
Vijay Reddy (Google Cloud)
Average rating: *****
(5.00, 2 ratings)
Vijay Reddy offers a brief overview of TensorFlow, explaining why it's so popular and how to leverage it to build machine learning applications. Vijay walks you through an end-to-end example using TensorFlow for data ingestion, training, and prediction and the Google Cloud Platform to supercharge training and prediction and remove pain from the development and operational workflows. Read more.
2:35pm3:15pm Wednesday, June 28, 2017
Location: Sutton North
Karthik Lalithraj (Kinetica)
Karthik Lalithraj explains how a GPU-accelerated database helps you deploy an easy-to-use, scalable, cost-effective, and future-proof AI solution that enables data science teams to develop, test, and train simulations and algorithms while making them directly available on the same systems used by end users. Read more.
4:00pm4:40pm Wednesday, June 28, 2017
Location: Grand Ballroom West Level: Intermediate
Secondary topics:  Cloud, Deep Learning
Yufeng Guo (Google)
Average rating: ****.
(4.00, 2 ratings)
Moving the heavy lifting of machine learning to the cloud is a great way to get large speed-ups. Yufeng Guo walks you through this process in detail so that you'll be ready to scale your own training and prediction services. Read more.
4:00pm4:40pm Wednesday, June 28, 2017
Location: Gramercy East/West Level: Intermediate
Secondary topics:  Hardware, Machine Learning
Qirong Ho (Petuum, Inc.)
Average rating: **...
(2.00, 1 rating)
Petuum, Inc. builds software that lets enterprises develop AI solutions in multiple programming languages and deploy them at scale and with high performance to internal, private computing resources that include a heterogeneous mix of workstations, clusters, CPUs, and GPUs. Qirong Ho outlines the architectural design choices and technical foundation needed to achieve these targets. Read more.
4:00pm4:40pm Wednesday, June 28, 2017
Location: Beekman Level: Intermediate
Secondary topics:  Ethics, Governance, and Privacy
Chuck Howell (MITRE), Lashon Booker (MITRE)
Lack of confidence in the fairness of an AI-based system will limit support for its use and likely preclude adoption, even if that adoption could provide significant benefits. Chuck Howell and Lashon Booker explore tools, techniques, and best practices from the safety-critical software community that can be adapted to provide a “fairness case” framework to address fairness concerns effectively. Read more.
4:00pm4:40pm Wednesday, June 28, 2017
Location: Sutton South/Regent Parlor Level: Beginner
Secondary topics:  Deep Learning, Natural Language
Mohamed Musbah (Maluuba Inc.)
Average rating: ****.
(4.75, 4 ratings)
AI research in comprehension, communication, and modeling human-like thinking skills is heralding the dawn of literate machines. Although there has been a lot of recent hype around bots, we’re only just beginning to see the potential for language understanding. Mohamed Musbah explores key research areas and explains how they will power new products and services in language understanding. Read more.
4:00pm4:40pm Wednesday, June 28, 2017
Location: Murray Hill E/W Level: Beginner
Secondary topics:  Machine Learning
Matthew Taylor (Numenta)
Average rating: ****.
(4.50, 2 ratings)
Today's wave of AI technology is still being driven by the ANN neuron pioneered decades ago. Hierarchical temporal memory (HTM) is a realistic biologically constrained model of the pyramidal neuron reflecting today's most recent neocortical research. Matthew Taylor offers an overview of core HTM concepts, including sparse distributed representations, spatial pooling, and temporal memory. Read more.
4:00pm4:40pm Wednesday, June 28, 2017
Location: Sutton Center
Drew Silverstein (Amper Music), Cole Ingraham (Amper Music)
Drew Silverstein and Cole Ingraham discuss computational creativity. Read more.
4:00pm4:40pm Wednesday, June 28, 2017
Location: Sutton North Level: Beginner
Secondary topics:  Hardware, IoT and its applications
Shaoshan Liu (PerceptIn)
Average rating: *****
(5.00, 1 rating)
It is imperative to make high-profile technologies like AI affordable in order for these technologies to proliferate and to benefit the general public. Shaoshan Liu discusses PerceptIn's road to affordable AI-capable products. Read more.
4:50pm5:30pm Wednesday, June 28, 2017
Location: Grand Ballroom West Level: Beginner
Sharan Narang (Baidu)
Artificial intelligence has had a tremendous impact on various applications at Baidu, including speech recognition and autonomous driving, although the performance requirements for all of these applications are very different. Sharan Narang outlines the challenges in inference for deep learning models and different workloads and performance requirements for various applications. Read more.
4:50pm5:30pm Wednesday, June 28, 2017
Location: Gramercy East/West Level: Intermediate
Secondary topics:  Deep Learning, Financial services
Thomas Wiecki (Quantopian)
Average rating: ***..
(3.67, 3 ratings)
Expressing neural networks as a Bayesian model naturally instills uncertainty in its predictions. Thomas Wiecki demonstrates how to embed deep learning in the probabilistic programming framework PyMC3 to address uncertainty and nonstationarity. Read more.
4:50pm5:30pm Wednesday, June 28, 2017
Location: Beekman Level: Non-technical
Secondary topics:  Ethics, Governance, and Privacy, Financial services, Natural Language
Tim Estes (Digital Reasoning)
Average rating: ****.
(4.50, 2 ratings)
As AI moves from concept to reality, debates about ethics are evolving into excitement and the desire to learn more about AI and its promise of a better world. Tim Estes discusses two customer use cases: Nasdaq, which found a way to use AI to help safeguard financial markets, and Thorn, which found a way to use AI to combat human trafficking and rescue children. Read more.
4:50pm5:30pm Wednesday, June 28, 2017
Location: Sutton South/Regent Parlor Level: Beginner
Secondary topics:  Financial services, Machine Learning, Natural Language
Francisco Webber (Cortical.io)
Average rating: *****
(5.00, 1 rating)
Financial industries are under increased pressure due to regulations that demand extended information management capabilities. Information largely consists of text data, which forces companies to increase headcount to keep up with the growing workload. Francisco Webber demonstrates how Cortical.io’s semantic folding, a neuroscience-based approach to NLU, helps automate these uses cases. Read more.
4:50pm5:30pm Wednesday, June 28, 2017
Location: Murray Hill E/W Level: Intermediate
Secondary topics:  Cloud, Speech and Voice, User interface and experience
Cathy Pearl (Google)
Average rating: *....
(1.25, 4 ratings)
Brad Abrams explores the latest design and development techniques for building natural language interfaces and draws on the Google Assistant, Actions on Google, and API.AI as examples to explore conversational UI best practices. Read more.
4:50pm5:30pm Wednesday, June 28, 2017
Location: Sutton North Level: Non-technical
Katy George (McKinsey & Company)
Average rating: *****
(5.00, 2 ratings)
The speed with which automation technologies are emerging today and the extent to which they could disrupt the world of work are largely without precedent. How big could the impact be on the world of work, and how rapidly will it be felt? Katy George explores these questions, drawing on a major new report from the McKinsey Global Institute. Read more.
4:50pm5:30pm Wednesday, June 28, 2017
Location: Sutton Center Level: Non-technical
Madeleine Elish (Data & Society)
Average rating: ****.
(4.50, 2 ratings)
When we worry about the Terminator or superintelligence, we miss the social implications of AI that are already beginning to take shape. Madeleine Elish outlines the core challenges to the responsible design and deployment of AI systems and reviews current trends in the ways in which designers and engineers are addressing these challenges across sectors. Read more.

Thursday, June 29

11:05am11:45am Thursday, June 29, 2017
Location: Grand Ballroom West
Russ Salakhutdinov (Carnegie Mellon University)
Average rating: ****.
(4.67, 6 ratings)
Russ Salakhutdinov discusses some of the key challenges to making machines more intelligent, focusing on the Gated-Attention (GA) Reader model, which integrates a multihop architecture with a novel attention mechanism, along with extensions that make use of external linguistic knowledge. Read more.
11:05am11:45am Thursday, June 29, 2017
Location: Gramercy East/West Level: Beginner
Secondary topics:  Health care, Machine Learning, Natural Language
Michael Nova (Pathway Genomics)
Average rating: *****
(5.00, 1 rating)
Precision medicine is largely a big data and systems problem, especially with many different types of "siloed" healthcare information, such as lab results, genetic tests, IoT and wearables data, and insurance information. Michael Nova explains why cognitive computing and artificial intelligence that can dynamically learn using any healthcare data will dramatically impact precision healthcare. Read more.
11:05am11:45am Thursday, June 29, 2017
Location: Beekman Level: Beginner
Alberto Rizzoli (Aipoly)
Average rating: *****
(5.00, 1 rating)
Alberto Rizzoli explains how Aipoly began running convolutional neural networks locally on smartphones, eventually reaching a level of performance that made it a better option than cloud services, in the process unlocking new possibilities for making phones contextually aware. Read more.
11:05am11:45am Thursday, June 29, 2017
Location: Sutton South/Regent Parlor Level: Beginner
Secondary topics:  Machine Learning, Transportation and Logistics, Vision
Matt Shobe (Mighty AI)
Average rating: ****.
(4.00, 1 rating)
Autonomous vehicles must recognize objects in context, no matter the weather, time of day, or season. What does a cat in the road look like on a sunny summer day? How about on a snow-covered road at night? Matt Shobe shares lessons Mighty AI has learned while creating a training dataset for autonomous driving, including workflow tips and guidance for engineers building computer vision models. Read more.
11:05am11:45am Thursday, June 29, 2017
Location: Murray Hill E/W Level: Intermediate
amir banifatemi (Xprize), Balazs Kegl (CNRS)
Amir Banifatemi and Balazs Kegl discuss the XPRIZE Foundation, which has launched the largest global AI competition to use AI for impact, outlining the foundation's goals, what the prize entails, and what the 146 teams from 22 countries are working on. One of the teams will share its project and explore various methods and practical ways to interact with AI. Read more.
11:05am11:45am Thursday, June 29, 2017
Location: Sutton Center/North Level: Intermediate
Secondary topics:  Machine Learning
Adam Marcus (B12)
Average rating: *****
(5.00, 2 ratings)
AI has a way to go before it replaces the jobs we know today. But long before AI automates away jobs, it will elevate expertise. B12 is building infrastructure that celebrates humans where they’re best while bringing machines in for the rest. Adam Marcus offers an overview of human-assisted AI and demonstrates how it is already changing creative (and fundamentally human) fields like design. Read more.
11:55am12:35pm Thursday, June 29, 2017
Location: Grand Ballroom West Level: Beginner
Secondary topics:  Deep Learning, Media
Soumith Chintala (Facebook)
Average rating: ***..
(3.00, 3 ratings)
Soumith Chintala discusses paradigm shifts in cutting-edge AI research and applications such as self-driving cars, robots, and game playing. Read more.
11:55am12:35pm Thursday, June 29, 2017
Location: Gramercy East/West
Abe Heifets (Atomwise)
Abe Heifets offers an overview of AtomNet, a structure-based deep convolutional neural network designed to predict the bioactivity of small molecules for drug discovery applications. Abe discusses training AtomNet on millions of training examples derived from ChEMBL and the PDB and explains how autonomously discovered filters can outperform previous docking approaches and existing DNN techniques. Read more.
11:55am12:35pm Thursday, June 29, 2017
Location: Beekman Level: Beginner
Secondary topics:  Deep Learning, Hardware, IoT and its applications
Michael B. Henry (Mythic)
Breakthroughs in deep learning and new analog-domain computation methods to deploy trained neural networks will deliver exciting new capabilities. Michael B. Henry explains why the combination of human-like levels of recognition and massive computation capabilities in a tiny package will enable products with true awareness and understanding of the user and environment. Read more.
11:55am12:35pm Thursday, June 29, 2017
Location: Sutton South/Regent Parlor
Anca Dragan (UC Berkeley)
Average rating: *****
(5.00, 3 ratings)
As AI agents become more capable of optimizing their objective functions, it's becoming increasingly important to make sure that we give them the right objectives in the first place. Anca Dragan explains why agents should have uncertainty about their objectives and use human input as valuable observations to improve their estimates. Read more.
11:55am12:35pm Thursday, June 29, 2017
Location: Murray Hill E/W Level: Beginner
Yarin Gal (University of Cambridge)
Average rating: ***..
(3.43, 7 ratings)
Yarin Gal shares a new theory linking Bayesian modeling and deep learning and demonstrates the practical impact of the framework with a range of real-world applications. Yarin also explores open problems for future research—problems that stand at the forefront of this new and exciting field. Read more.
11:55am12:35pm Thursday, June 29, 2017
Location: Sutton Center/North Level: Intermediate
Secondary topics:  Machine Learning, Natural Language
Jason Laska (Clara Labs)
Average rating: *****
(5.00, 1 rating)
Clara Labs is fusing machine learning (ML) with distributed human labor for natural language tasks. The result is a virtuous cycle: ML predictions improve workers’ efficiency, and workers help improve prediction models. Jason Laska explores the challenges of building a real-time(ish) knowledge workforce, how to integrate automation, and key strategies Clara Labs learned that enable scale. Read more.
1:45pm2:25pm Thursday, June 29, 2017
Location: Grand Ballroom West Level: Beginner
Secondary topics:  Deep Learning, Vision
Timothy Hazen (Microsoft)
Dramatic progress has been made in computer vision: deep neural networks (DNNs) trained on tens of millions of images can now recognize thousands of different object types. These DNNs can also be easily customized to new use cases. Timothy Hazen shares simple methods and tools that enable you to adapt Microsoft's state-of-the-art DNNs for use in your own computer vision solutions. Read more.
1:45pm2:25pm Thursday, June 29, 2017
Location: Gramercy East/West Level: Intermediate
Secondary topics:  Health care
Garrett Goh (Pacific Northwest National Lab)
Garrett Goh demonstrates how to use deep learning to construct computational chemistry models that compare favorably to existing state-of-the-art models developed by expert practitioners—with virtually no expert knowledge—proving the potential of AI assistance to accelerate the scientific discovery process from a typical span of years to a matter of months. Read more.
1:45pm2:25pm Thursday, June 29, 2017
Location: Beekman Level: Beginner
Secondary topics:  Hardware, IoT and its applications, Machine Learning
Xiaofan Xu (Intel), Cormac Brick (Intel)
Data is the “oxygen” of the AI revolution, but access to data on a large scale remains a luxury of an elite group of tech companies, effectively creating a “data wall” blocking smaller companies. Cormac Brick and Xiaofan Xu explore the problem of the data wall and offer a solution: synthetic datasets. Read more.
1:45pm2:25pm Thursday, June 29, 2017
Location: Sutton South/Regent Parlor Level: Intermediate
Secondary topics:  Cloud, Deep Learning, Vision
Reza Zadeh (Matroid | Stanford)
Providing customized computer vision solutions to a large number of users is a challenge. Matroid allows the creation and serving of computer vision models and algorithms, model sharing between users, and serving infrastructure at scale. Reza Zadeh offers an overview of Matroid's pipeline, which uses TensorFlow, Kubernetes, and Amazon Web Services. Read more.
1:45pm2:25pm Thursday, June 29, 2017
Location: Murray Hill E/W
Jun-Yan Zhu (Berkeley AI Research Lab)
Average rating: *****
(5.00, 2 ratings)
Jun-Yan Zhu explains how to learn natural image statistics directly from large-scale data and explores a class of image-generation and editing operations that constrain their output to look realistic according to the learned image statistics. Read more.
1:45pm2:25pm Thursday, June 29, 2017
Location: Sutton Center/North Level: Intermediate
Secondary topics:  IoT and its applications, Machine Learning
Mark Hammond (Microsoft)
Average rating: ****.
(4.00, 1 rating)
As interactive and autonomous systems make their way into nearly every aspect of our lives, it is crucial to gain more trust in intelligent systems. Mark Hammond explores the latest techniques and research in building explainable AI systems. Join in to learn approaches for building explainability into control and optimization tasks, including robotics, manufacturing, and logistics. Read more.
2:35pm3:15pm Thursday, June 29, 2017
Location: Grand Ballroom West Level: Intermediate
Secondary topics:  Cloud, Deep Learning, Machine Learning, Vision
Matt Zeiler (Clarifai)
Average rating: *....
(1.33, 3 ratings)
AI-powered machine learning technologies bring a higher and more complex level of technical debt to applications. Matt Zeiler shares best practices for companies hoping to build AI into their businesses and explores how machine learning increases technical debt, the key contributors, and how to avoid or reduce technical debt related to machine learning. Read more.
2:35pm3:15pm Thursday, June 29, 2017
Location: Gramercy East/West
Secondary topics:  Health care
Kavya Kopparapu (GirlsComputingLeague)
Average rating: *****
(5.00, 3 ratings)
Artificial intelligence is revolutionizing medicine through computer-aided diagnostic systems. High school student Kavya Kopparapu presents the Eyeagnosis system, which utilizes artificial intelligence techniques and a smartphone camera to automatically screen for diabetic retinopathy, the leading cause of preventable blindness worldwide. Read more.
2:35pm3:15pm Thursday, June 29, 2017
Location: Beekman Level: Non-technical
David Rogers (Sight Machine)
Average rating: ***..
(3.50, 2 ratings)
Join David Rogers to learn how AI can make your operations more efficient and profitable. David explains how existing technologies like the digital twin approach, advanced decision making, and downtime cause detection have primed manufacturing for a profitable and efficient future. Read more.
2:35pm3:15pm Thursday, June 29, 2017
Location: Sutton South/Regent Parlor Level: Intermediate
Secondary topics:  Cloud, Deep Learning
Joseph Bradley (Databricks), Xiangrui Meng (Databricks)
Joseph Bradley and Xiangrui Meng share best practices for integrating popular deep learning libraries with Apache Spark, covering cluster setup, data ingest, configuring clusters, and monitoring jobs. Joseph and Xiangrui then demonstrate these techniques using Google’s TensorFlow library. Read more.
2:35pm3:15pm Thursday, June 29, 2017
Location: Murray Hill E/W Level: Intermediate
Secondary topics:  Machine Learning, Media, Retail and e-commerce
Nikita Lytkin (Facebook)
Average rating: *****
(5.00, 2 ratings)
Nikita Lytkin offers an overview of personalized digital advertising and explains how Facebook uses modern supervised machine learning methods, such as factorization machines and deep neural networks, to recommend ecommerce products to nearly two billion people. Read more.
2:35pm3:15pm Thursday, June 29, 2017
Location: Sutton Center/North Level: Non-technical
Secondary topics:  Media, Natural Language
Codruta Gamulea (Bakken & Bæck)
Average rating: ***..
(3.00, 1 rating)
The promise of AI in the newsroom is contradictory: NLG revolutionizes news writing, but robot journalists threaten jobs; NLP improves fact-checking but requires investments that slimmed-down newsrooms cannot afford. Drawing on Norwegian AI startup Orbit’s experience, Codruta Gamulea explains how AI can help solve the industry resource constraints and improve the quality of journalism. Read more.
4:00pm4:40pm Thursday, June 29, 2017
Location: Grand Ballroom West Level: Intermediate
Secondary topics:  Cloud, Deep Learning, Vision
Yonghua Lin (IBM Research)
Yonghua Lin leads a deep dive into AI Vision, a deep learning system from IBM for image and video analysis in both edge and cloud environments, exploring its system design, performance optimization, and large-scale capability for training and inference. Read more.
4:00pm4:40pm Thursday, June 29, 2017
Location: Gramercy East/West Level: Intermediate
Secondary topics:  Deep Learning, Media, Natural Language, Speech and Voice, User interface and experience
Jan Neumann (Comcast), Ferhan Ture (Comcast), Shahin Sefati (Comcast)
AI plays an essential role in creating the Comcast X1 entertainment experience and is how millions of its customers access their content on the TV. Jan Neumann, Ferhan Ture, and Shahin Sefati explain how AI enables Comcast to understand what you are looking for when you talk to the X1 voice remote and how Comcast scaled the voice interface to answer millions of voice queries every single night. Read more.
4:00pm4:40pm Thursday, June 29, 2017
Location: Beekman Level: Intermediate
Suman Roy (Betaworks)
Machine learning is empowering, but a critical drawback in the current ecosystem is the lack of tactical verification tools that can guarantee its fidelity in real-world applications. Suman Roy explores the tools and best practices during training, implementation, and postdeployment that can help explain what exactly we are teaching these machines. Read more.
4:00pm4:40pm Thursday, June 29, 2017
Location: Sutton South/Regent Parlor Level: Beginner
Rakesh Chada (x.ai)
Rakesh Chada introduces x.ai's Amy, an AI assistant that schedules meetings via email. Rakesh discusses Amy's architecture and the various challenges the team faced during its design and shares several machine learning approaches for intent classification. Rakesh concludes by exploring a novel method for error optimization in a conversational agent that exploits customer error tolerance. Read more.
4:00pm4:40pm Thursday, June 29, 2017
Location: Murray Hill E/W Level: Intermediate
Secondary topics:  Deep Learning, Fashion, Retail and e-commerce, Vision
Pau Carre (Gilt)
Pau Carré explains how Gilt is reshaping the fashion industry by leveraging the power of deep learning and GPUs to automatically detect similar products and identify facets in dresses. Read more.
4:00pm4:40pm Thursday, June 29, 2017
Location: Sutton Center/North Level: Non-technical
Secondary topics:  Ethics, Governance, and Privacy
Aileen Nielsen (Skillman Consulting)
Average rating: *****
(5.00, 1 rating)
While the commercial use of AI in everything from hiring to medical diagnosis to work scheduling is exploding, legislation and case law alike have yet to make major statements about how AI will be treated by the American legal system. Aileen Nielsen offers a historical overview of how the law has dealt with decision-making technologies in the past and what this suggests about AI's legal future. Read more.
4:50pm5:30pm Thursday, June 29, 2017
Location: Grand Ballroom West Level: Beginner
Lindsey Zuloaga (HireVue)
Lindsey Zuloaga explains how machine learning from video interviews is disrupting the human resources space, bringing top candidates to the attention of recruiters and drastically reducing the time and energy companies spend finding and assessing potential employees. Read more.
4:50pm5:30pm Thursday, June 29, 2017
Location: Gramercy East/West Level: Non-technical
Secondary topics:  Machine Learning, Media, Natural Language
Paco Nathan (derwen.ai)
Paco Nathan explains how O'Reilly employs AI, from the obvious (chatbots, case studies about other firms) to the less so (using AI to show the structure of content in detail, enhance search and recommendations, and guide editors for gap analysis, assessment, pathing, etc.). Approaches include vector embedding search, summarization, TDA for content gap analysis, and speech-to-text to index video. Read more.
4:50pm5:30pm Thursday, June 29, 2017
Location: Beekman Level: Intermediate
Patrick Hall (bnh.ai | H2O.ai), SriSatish Ambati (H2O.ai)
Average rating: *****
(5.00, 1 rating)
Interpreting deep learning and machine learning models is not just another regulatory burden to be overcome. People who use these technologies have the right to trust and understand AI. Patrick Hall and Sri Satish share techniques for interpreting deep learning and machine learning models and telling stories from their results. Read more.
4:50pm5:30pm Thursday, June 29, 2017
Location: Sutton South/Regent Parlor Level: Intermediate
Secondary topics:  Machine Learning, Natural Language
Jonathan Mugan (DeepGrammar)
Average rating: *****
(5.00, 1 rating)
Jonathan Mugan surveys the field of natural language processing (NLP), both from a symbolic and a subsymbolic perspective, arguing that the current limitations of NLP stem from computers having a lack of grounded understanding of our world. Jonathan then outlines ways that computers can achieve that understanding. Read more.
4:50pm5:30pm Thursday, June 29, 2017
Location: Murray Hill E/W Level: Intermediate
Secondary topics:  Machine Learning, Retail and e-commerce, User interface and experience
Rupert Steffner (WUNDER)
70% of consumers do NOT feel that online offers resonate with their personal interests and needs. Rupert Steffner explains how cognitive AI can help create deep shopping bots based on true personal relevance. This shift in the shopping paradigm is built upon deep symbolic reinforcement learning, the psychometry of shopping, a new breed of playful UI, and cognified product metadata. Read more.
4:50pm5:30pm Thursday, June 29, 2017
Location: Sutton Center/North
Patrick Hebron (New York University)
Is it possible to simplify design tools without limiting their expressivity? Patrick Hebron investigates how recent advances in machine learning and artificial intelligence will enable a new generation of tools that help novice and expert designers alike develop deeply nuanced and original ideas without committing to a steep learning curve or ceding creative control to the machine. Read more.