Presented By O’Reilly and Intel AI
Put AI to work
8-9 Oct 2018: Training
9-11 Oct 2018: Tutorials & Conference
London, UK

Schedule

Monday, 8/10/2018

9:00

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9:00–17:00 Monday, 8/10/2018
Training
Location: Hilton Meeting rooms 5/6 Level: Intermediate
Secondary topics:  Deep Learning tools
Robert Schroll (The Data Incubator)
TensorFlow is an increasingly popular tool for deep learning. Robert Schroll offers an overview of the TensorFlow graph using its Python API. You'll start with simple machine learning algorithms and move on to implementing neural networks. Along the way, Robert covers several real-world deep learning applications, including machine vision, text processing, and generative networks. Read more.
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9:00–17:00 Monday, 8/10/2018
Training
Location: Hilton Meeting room 1/2
Secondary topics:  Deep Learning models, Deep Learning tools, Text, Language, and Speech
Brian McMahan (Joostware)
Delip Rao explores natural language processing with deep learning, walking you through neural network architectures and NLP tasks and teaching you how to apply these architectures for those tasks. Read more.
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9:00–17:00 Monday, 8/10/2018
Training
Location: Hilton Meeting room 3/4
Secondary topics:  AI in the Enterprise
Angie Ma (ASI Data Science), Jonny Howell (ASI Data Science), Emanuele Moscato (ASI Data Science)
Average rating: **...
(2.00, 1 rating)
Angie Ma and Jonny Howell offer a condensed introduction to key AI and machine learning concepts and techniques, showing you what is (and isn't) possible with these exciting new tools and how they can benefit your organization. Read more.
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9:00–17:00 Monday, 8/10/2018
Event
Sponsored, TensorFlow at AI
Location: Windsor Suite Level: Beginner
Benoit Dherin (Google)
Average rating: *****
(5.00, 1 rating)
Benoit Dherin leads an introduction to designing and building machine learning models on Google Cloud Platform. Through a combination of presentations, demos, and hand-ons labs, you'll learn machine learning (ML) and TensorFlow concepts and develop skills in developing, evaluating, and productionizing ML models. Read more.

10:30

10:30–11:00 Monday, 8/10/2018
Location: Hilton Meeting Room Foyer and Mezzanine
Morning Break (30m)

12:30

12:30–13:30 Monday, 8/10/2018
Location: Restaurant
Lunch (1h)

15:00

15:00–15:30 Monday, 8/10/2018
Location: Hilton Meeting Room Foyer and Mezzanine
Afternoon Break (30m)

Tuesday, 9/10/2018

9:00

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9:00–12:30 Tuesday, 9/10/2018
Tutorial
Implementing AI
Location: Buckingham Room - Palace Suite Level: Beginner
Secondary topics:  Computer Vision, Deep Learning tools
Mo Patel (Independent)
Average rating: *....
(1.50, 2 ratings)
Computer vision has led the artificial intelligence renaissance, and pushing it further forward is PyTorch, a flexible framework for training models. Mo Patel offers an overview of computer vision fundamentals and walks you through PyTorch code explanations for notable objection classification and object detection models. Read more.
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9:00–12:30 Tuesday, 9/10/2018
Tutorial
Implementing AI
Location: Blenheim Room - Palace Suite Level: Intermediate
Secondary topics:  Deep Learning tools, Platforms and infrastructure
Denis Batalov (Amazon)
Join Denis Batalov for an overview of the Amazon SageMaker machine learning platform. Denis walks you through setting up an Amazon SageMaker notebook (a hosted Jupyter Notebook server), using a built-in SageMaker deep learning algorithm, and building your own neural network architecture using SageMaker's prebuilt TensorFlow containers. Read more.
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9:00–17:00 Tuesday, 9/10/2018
Event
TensorFlow at AI
Location: Windsor Suite Level: Intermediate
Melinda King (ROI Training)
Melinda King walks you through the process of building a complete machine learning pipeline, from ingest and exploration to training, evaluation, deployment, and prediction. Read more.
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9:00–17:00 Tuesday, 9/10/2018
Tutorial
AI Business Summit
Location: King's Suite - Balmoral Level: Beginner
Secondary topics:  AI in the Enterprise
Kristian Hammond (Northwestern Computer Science)
Average rating: ****.
(4.00, 1 rating)
Even as AI technologies move into common use, many enterprise decision makers remain baffled about what the different technologies actually do and how they can be integrated into their businesses. Rather than focusing on the technologies alone, Kristian Hammond provides a practical framework for understanding your role in problem solving and decision making. Read more.
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9:00–17:00 Tuesday, 9/10/2018
Tutorial
Interacting with AI
Location: Park Suite Level: Intermediate
Secondary topics:  Computer Vision, Deep Learning tools
Benoit Dherin (Google)
Benoit Dherin explains how machine learning is applied to image classification, discusses evolving methods and challenges, and walks you through creating increasingly sophisticated image classification models using TensorFlow. Read more.

12:30

12:30–13:30 Tuesday, 9/10/2018
Location: Restaurant
Lunch - sponsored by Intel AI (1h)

13:30

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13:30–17:00 Tuesday, 9/10/2018
Tutorial
Models and Methods
Location: Buckingham Room - Palace Suite Level: Intermediate
Secondary topics:  Deep Learning models, Financial Services, Temporal data and time-series
Yijing Chen (Microsoft), Dmitry Pechyoni (Microsoft), Angus Taylor (Microsoft), Vanja Paunic (Microsoft)
Average rating: ***..
(3.67, 3 ratings)
Buisnesses use forecasting to make better decisions and allocate resources more effectively. Recurrent neural networks (RNNs) have achieved a lot of success in text, speech, and video analysis but are less used for time series forecasting. Join Yijing Chen, Dmitry Pechyoni, Angus Taylor, and Vanja Paunic to learn how to apply RNNs to time series forecasting. Read more.
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13:30–17:00 Tuesday, 9/10/2018
Tutorial
Location: Blenheim Room - Palace Suite
Secondary topics:  Reinforcement Learning, Text, Language, and Speech
Richard Liaw (UC Berkeley RISELab), Eric Liang (UC Berkeley RISELab)
Ion Stoica, Robert Nishihara, Richard Liaw, Eric Liang, and Philipp Moritz lead a deep dive into Ray, a new distributed execution framework for reinforcement learning applications, walking you through Ray's API and system architecture and sharing application examples, including several state-of-the art RL algorithms. Read more.

17:00

17:00–18:30 Tuesday, 9/10/2018
Location: On your own
Break (1h 30m)

18:30

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18:30–22:00 Tuesday, 9/10/2018
Event
Location: Various Locations
Get to know your fellow attendees over dinner. We've made reservations for you at some of the most sought-after restaurants in town. This is a great chance to make new connections and sample some of the great cuisine London has to offer. Read more.

20:00

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20:00–21:30 Tuesday, 9/10/2018
Event
Location: St. James's Sussex Gardens
Join us to hear the fruits of artificial and biological intelligences working together. The evening—both a concert and a demonstration—presents a diverse program of music created with the assistance of a machine learning system trained on folk music from Ireland and the UK. Dessert and refreshments will be served. Read more.

Wednesday, 10/10/2018

8:15

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8:15–8:45 Wednesday, 10/10/2018
Event
Location: King's Suite foyer
Ready, set, network! Meet fellow attendees who are looking to connect at the AI Conference. We'll gather before Wednesday and Thursday keynotes for an informal speed networking event. Be sure to bring your business cards—and remember to have fun. Read more.

9:00

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9:00–9:05 Wednesday, 10/10/2018
Keynote
Location: King's Suite
Ben Lorica (O'Reilly Media), Roger Chen (Computable Labs)
Program cochairs Ben Lorica and Roger Chen open the first day of keynotes. Read more.

9:05

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9:05–9:20 Wednesday, 10/10/2018
Keynote
Location: King's Suite
Jonathan Ballon (Intel)
Artificial intelligence in the future, at least represented in science fiction, can learn, interpret, and take action based on data analysis. AI in production is the present, a present that feels decidedly futuristic. Jonathan Ballon explains why Intel’s leading portfolio of AI and computer vision edge technology will drive advances that improve how we work and live. Read more.

9:20

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9:20–9:30 Wednesday, 10/10/2018
Keynote
Location: King's Suite
Ben Lorica (O'Reilly Media), Roger Chen (Computable Labs)
What technologies are ready for adoption, and how should companies and organizations evaluate automation technologies? Ben Lorica and Roger Chen highlight recent trends in data, compute, and machine learning. Read more.

9:30

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9:30–9:35 Wednesday, 10/10/2018
Keynote
Location: King's Suite
Ian Massingham (Amazon Web Services)
Ian Massingham discusses the application of ML and AI within Amazon, from retail product recommendations to the latest in natural language understanding, and explains how you can use easily accessible services from AWS to include AI features within your applications or build your own custom ML models for your own specific AI use cases. Read more.

9:35

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9:35–9:50 Wednesday, 10/10/2018
Keynote
Location: King's Suite
Secondary topics:  Text, Language, and Speech
Amy Heineike (Primer)
Human-generated knowledge bases like Wikipedia have excellent precision but poor recall. Amy Heineike explains how Primer created a self-updating knowledge base that can track factual claims in unstructured text and describe what it learns in human-readable text. Read more.

9:50

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9:50–10:00 Wednesday, 10/10/2018
Keynote
Location: King's Suite
Secondary topics:  Ethics, Privacy, and Security
Ruchir Puri (IBM)
TBC Read more.

10:00

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10:00–10:15 Wednesday, 10/10/2018
Keynote
Location: King's Suite
Ashok Srivastava (Intuit)
Industry buzz sometimes focuses on an AI future with dire unintended consequences for humanity. Ashok Srivastava draws on his cross-industry experience to paint an encouraging picture of how AI can solve big problems with people, data, and technology to benefit society. Read more.

10:20

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10:20–10:35 Wednesday, 10/10/2018
Keynote
Location: King's Suite
Secondary topics:  Computer Vision, Edge computing and Hardware
Yangqing Jia (Facebook)
Yangqing Jia shares a series of examples to illustrate the uniqueness of AI software and its connections to conventional computer science wisdom. Yangqing then discusses future software engineering principles for AI compute. Read more.

10:35

10:35–11:05 Wednesday, 10/10/2018
Location: Sponsor Pavilion
Morning break - sponsored by Amazon Web Services (30m)

11:05

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11:05–11:45 Wednesday, 10/10/2018
Session
Implementing AI
Location: King's Suite - Sandringham
Secondary topics:  Deep Learning tools, Edge computing and Hardware
Yangqing Jia (Facebook), Dmytro Dzhulgakov (Facebook)
Machine learning sits at the core of many essential products and services at Facebook. Yangqing Jia and Dmytro Dzhulgakov offer an overview of the hardware and software infrastructure that supports machine learning at global scale. Read more.
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11:05–11:45 Wednesday, 10/10/2018
Session
Sponsored, TensorFlow at AI
Location: Buckingham Room - Palace Suite
Sandeep Gupta (Google), Edd Wilder-James (Google)
TensorFlow is one of the world’s biggest open source projects, and it continues to grow in adoption and functionality. Sandeep Gupta and Edd Wilder-James share major recent developments, highlight some future directions, and explain how you can become more involved in the TensorFlow community. Read more.
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11:05–11:45 Wednesday, 10/10/2018
Session
AI Business Summit
Location: Blenheim Room - Palace Suite Level: Intermediate
Secondary topics:  AI in the Enterprise, Financial Services
Ashok Srivastava (Intuit)
Ashok Srivastava explains how to make your organization AI ready, determine the right AI applications for your business and products, and accelerate your AI efforts with speed and scale. Read more.
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11:05–11:45 Wednesday, 10/10/2018
Session
Implementing AI
Location: Windsor Suite
Secondary topics:  Edge computing and Hardware, Platforms and infrastructure
Nigel Toon (Graphcore)
Nigel Toon explains how scaling IPUs will increase the productivity of machine intelligence researchers everywhere. Join in to explore what can we do and expect from the field with vastly more compute. Read more.
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11:05–11:45 Wednesday, 10/10/2018
Session
Implementing AI
Location: King's Suite - Balmoral Level: Intermediate
Secondary topics:  Deep Learning models, Ethics, Privacy, and Security, Text, Language, and Speech
Yishay Carmiel (IntelligentWire)
Average rating: *****
(5.00, 1 rating)
In recent years, there's been a quantum leap in the performance of AI, as deep learning made its mark in areas from speech recognition to machine translation and computer vision. However, as artificial intelligence becomes increasingly popular, data privacy issues also gain traction. Yishay Carmiel reviews these issues and explains how they impact the future of deep learning development. Read more.
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11:05–11:45 Wednesday, 10/10/2018
Session
Implementing AI
Location: Westminster Suite Level: Intermediate
Secondary topics:  Deep Learning tools, Platforms and infrastructure
Jonathan Hung (LinkedIn), Keqiu Hu (LinkedIn), Anthony Hsu (LinkedIn)
Jonathan Hung, Keqiu Hu, and Anthony Hsu offer an overview of TensorFlow on YARN (TonY), a framework to natively run TensorFlow on Hadoop. TonY enables running TensorFlow distributed training as a new type of Hadoop application. Its native Hadoop connector, together with other features, aims to run TensorFlow jobs as reliably and flexibly as other first-class objects on Hadoop. Read more.
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11:05–11:45 Wednesday, 10/10/2018
Session
Location: Hilton Meeting Room 3-6
Secondary topics:  Ethics, Privacy, and Security
Ruchir Puri (IBM), Hilary Kerner (Vice President, IBM Watson Marketing)
Average rating: *****
(5.00, 1 rating)
TBC Read more.
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11:05–11:45 Wednesday, 10/10/2018
Session
AI Business Summit, Impact of AI on Business and Society
Location: Park Suite Level: Beginner
Secondary topics:  AI in the Enterprise
Francesca Lazzeri (Microsoft), Jaya Mathew (Microsoft)
With the growing buzz around data science, many professionals want to learn how to become a data scientist—the role Harvard Business Review called the "sexiest job of the 21st century." Francesca Lazzeri and Jaya Mathew explain what it takes to become a data scientist and how artificial intelligence solutions have started to reinvent businesses. Read more.

11:55

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11:55–12:35 Wednesday, 10/10/2018
Session
Interacting with AI
Location: King's Suite - Sandringham Level: Intermediate
Secondary topics:  Media, Marketing, Advertising, Reinforcement Learning
Danny Lange (Unity Technologies)
Danny Lange discusses the role of intelligence in biological evolution and learning and demonstrates why a game engine is the perfect virtual biodome for AI’s evolution. You'll discover how the scale and speed of simulations is changing the game of AI while learning about new developments in reinforcement learning. Read more.
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11:55–12:35 Wednesday, 10/10/2018
Session
Sponsored, TensorFlow at AI
Location: Buckingham Room - Palace Suite
Amit Patankar (Google)
Building machine learning models is a multistage process. TensorFlow's high-level APIs make this process smooth and easy, whether you are starting small or going big. Amit Patankar walks you through building, training, and debugging a model and then exporting it for serving using these APIs. Read more.
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11:55–12:35 Wednesday, 10/10/2018
Session
AI Business Summit
Location: Blenheim Room - Palace Suite Level: Beginner
Secondary topics:  AI in the Enterprise
Paco Nathan (derwen.ai)
Deep learning works well when you have large labeled datasets, but not every team has those assets. Paco Nathan offers an overview of active learning, an ML variant that incorporates human-in-the-loop computing. Active learning focuses input from human experts, leveraging intelligence already in the system, and provides systematic ways to explore and exploit uncertainty in your data. Read more.
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11:55–12:35 Wednesday, 10/10/2018
Session
Models and Methods
Location: Windsor Suite Level: Advanced
Secondary topics:  Deep Learning models, Ethics, Privacy, and Security
Alan Mosca (nPlan | Birkbeck, University of London)
Alan Mosca shows how any deep learning model can be improved and made more secure with the use of targeted ensemble methods and other similar techniques and demonstrates how to use these techniques in the Toupee deep learning framework to create production-ready models. Read more.
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11:55–12:35 Wednesday, 10/10/2018
Session
Models and Methods
Location: King's Suite - Balmoral Level: Intermediate
Secondary topics:  Deep Learning models, Ethics, Privacy, and Security
Ryan Micallef (Cloudera Fast Forward Labs)
Average rating: ****.
(4.00, 1 rating)
Imagine building a model whose training data is collected on edge devices such as cell phones or sensors. Each device collects data unlike any other, and the data cannot leave the device because of privacy concerns or unreliable network access. This challenging situation is known as federated learning. Ryan Micallef discusses the algorithmic solutions and the product opportunities. Read more.
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11:55–12:35 Wednesday, 10/10/2018
Session
AI in the Enterprise
Location: Westminster Suite Level: Beginner
Secondary topics:  Platforms and infrastructure
Diego Oppenheimer (Algorithmia)
Diego Oppenheimer explains why machine learning is a natural fit for serverless computing, shares a general architecture for scalable ML, discusses issues he ran into when implementing on-demand scaling over GPU clusters at Algorithmia, and provides general solutions and a vision for the future of cloud-based ML. Read more.
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11:55–12:35 Wednesday, 10/10/2018
Session
Sponsored
Location: Hilton Meeting Room 3-6
Julien Simon (Amazon Web Services)
Amazon SageMaker is a fully managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Julien Simon offers a quick overview of SageMaker. Then, using Jupyter notebooks, he dives into the more advanced features of this service. Read more.
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11:55–12:35 Wednesday, 10/10/2018
Session
AI Business Summit, AI in the Enterprise
Location: Park Suite Level: Intermediate
Secondary topics:  Financial Services
Christine Foster (The Alan Turing Institute), Rakshit Kapoor (HSBC)
In 2016, the Alan Turing Institute, the UK’s new national institute for data science and AI, announced a funded strategic multiyear research partnership with HSBC. Christine Foster and Rakshit Kapoor share insights and use cases that emerged while making this ambitious and innovative cross-sector partnership work. Read more.

12:35

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12:35–13:45 Wednesday, 10/10/2018
Event
Location: Sponsor Pavilion
Topic Table discussions are a great way to informally network with people in similar industries or interested in the same topics. Read more.
Add to your personal schedule
12:35–13:45 Wednesday, 10/10/2018
Event
Location: Thames
Join fellow executives, business leaders, and strategists for a networking lunch on Wednesday for AI Business Summit attendees and speakers. Read more.

13:45

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13:45–14:25 Wednesday, 10/10/2018
Session
Location: King's Suite - Sandringham
Secondary topics:  Computer Vision, Deep Learning tools
Dmytro Dzhulgakov (Facebook)
Dmytro Dzhulgakov explores PyTorch 1.0, from its start as a popular deep learning framework for flexible research to its evolution into an end-to-end platform for building and deploying AI models at production scale. Read more.
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13:45–14:25 Wednesday, 10/10/2018
Session
Sponsored, TensorFlow at AI
Location: Buckingham Room - Palace Suite
Ryan Sepassi (Google)
Ryan Sepassi offers an overview of Tensor2Tensor, an open source library of datasets and models and a framework for training, evaluation, and decoding, built on top of TensorFlow. Tensor2Tensor is actively used and maintained by scientists and engineers within Google Brain. Read more.
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13:45–14:25 Wednesday, 10/10/2018
Session
AI Business Summit, AI in the Enterprise
Location: Blenheim Room - Palace Suite Level: Beginner
Secondary topics:  AI in the Enterprise
Diego Saenz (Accenture)
What do the world's most innovative and fastest growing companies have in common? They are in industries with a high level of VC funding. Accenture has analyzed five years of VC investment data to discover the AI use cases and technologies that are attracting the most money and will drive enterprise AI innovation. Diego Saenz explains where the top 10 investors in AI are placing big bets. Read more.
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13:45–14:25 Wednesday, 10/10/2018
Session
Models and Methods
Location: Windsor Suite Level: Intermediate
Secondary topics:  Temporal data and time-series
Business forecasting generally employs machine learning methods for longer and nonlinear use cases and econometrics approaches for linear trends. Pasi Helenius and Larry Orimoloye outline a hybrid approach that combines deep learning and econometrics. This method is particularly useful in areas such as competitive event (CE) forecasting (e.g., in sports events political events). Read more.
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13:45–14:25 Wednesday, 10/10/2018
Session
Implementing AI
Location: King's Suite - Balmoral Level: Intermediate
Secondary topics:  Ethics, Privacy, and Security, Retail and e-commerce
Rupert Steffner (WUNDER)
Average rating: ***..
(3.00, 1 rating)
The increase in automated decision making, along with doubts in the quality of algorithmic decisions, has driven demand for transparency and accountability in AI. Rupert Steffner explains why the shift from black box to white box is a great opportunity to build AI models that create trust with the user and shares Sense-Infer-Act-Learn, a logical AI execution model to enable a more trustworthy AI. Read more.
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13:45–14:25 Wednesday, 10/10/2018
Session
Location: Westminster Suite
Secondary topics:  Deep Learning tools, Edge computing and Hardware, Platforms and infrastructure
Gaurav Kaul (Amazon Web Services), Suneel Marthi (Amazon Web Services), Grigori Fursin (dividiti)
Gaurav Kaul, Grigori Fursin, and Suneel Marthi share trade-offs and design choices that are applicable to deep learning models when training in the cloud, specifically focusing on convergence and numerical stability, which are very important for autonomous driving and medical imaging. They then demonstrate how to optimize cost, performance, and convergence using CPU spot instances in AWS. Read more.
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13:45–14:25 Wednesday, 10/10/2018
Session
Location: Hilton Meeting Room 3-6
Gary Brown (Intel)
Gary Brown explains how the use of AI in the IoT is leading to fascinating growth in various applications from industrial and medical to smart transportation and retail. Gary discusses Intel’s unique vantage point of the platforms paving the way for interesting new AI experiences. Along the way, he shares Intel’s latest IoT innovations. Read more.
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13:45–14:25 Wednesday, 10/10/2018
Session
AI Business Summit, AI in the Enterprise, Impact of AI on Business and Society
Location: Park Suite Level: Intermediate
Secondary topics:  Financial Services
Martin Goodson (Evolution AI), Mark Qualter (RBS)
Martin Goodson and Mark St. John Qualter share the results of a yearlong feasibility study on the introduction of AI into the onboarding process at the Royal Bank of Scotland (RBS). Along the way, Martin and Mark share their experiences in translating this complex business process into a high-performance computational system. Read more.

14:35

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14:35–15:15 Wednesday, 10/10/2018
Session
Implementing AI, Models and Methods
Location: King's Suite - Sandringham Level: Intermediate
Secondary topics:  Deep Learning models, Edge computing and Hardware
Bruno Fernandez-Ruiz details a unified network that jointly performs various mission-critical tasks in real time on a mobile environment, within the context of driving. Along the way, he outlines the challenges that emerge when training a single mobile network for multiple tasks, such as object detection, object attributes recognition, classification, and tracking. Read more.
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14:35–15:15 Wednesday, 10/10/2018
Session
Sponsored, TensorFlow at AI
Location: Buckingham Room - Palace Suite
Joshua Dillon (Google Research), Wolff Dobson (Google)
Joshua Dillon and Wolff Dobson discuss core TensorFlow Probability (TFP) abstractions and demo some of TFP's modeling power and convenience. They also share some of the recent results from Project Magenta, a research project exploring the role of machine learning in the process of creating art and music. Read more.
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14:35–15:15 Wednesday, 10/10/2018
Session
AI Business Summit
Location: Blenheim Room - Palace Suite Level: Beginner
Secondary topics:  AI in the Enterprise
Mariya Yao (Metamaven)
Executives are being asked to "innovate with AI,” but the barriers to successful adoption for most enterprises are organizational, not technical. Mariya Yao explains why effective application of AI requires extended interdisciplinary coordination between executive and functional teams, investments in retraining your workforce, and the cultivation of an open, experimental, data-driven culture. Read more.
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14:35–15:15 Wednesday, 10/10/2018
Models and Methods
Location: Windsor Suite
Secondary topics:  Deep Learning models, Temporal data and time-series
Andrea Pasqua (Uber)
Andrea Pasqua investigates the merits of using deep learning and other machine learning approaches in the area of forecasting and describes some of the machine learning approaches Uber uses to forecast time series of business relevance. Read more.
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14:35–15:15 Wednesday, 10/10/2018
Session
Interacting with AI
Location: King's Suite - Balmoral Level: Beginner
Secondary topics:  Ethics, Privacy, and Security, Interfaces and UX
Rachel Bellamy (IBM Research), Casey Dugan (IBM Research)
Average rating: *....
(1.00, 1 rating)
Data bias is not only an AI problem; it's also a UI problem. Non-AI experts use custom application interfaces to help them make decisions based on predictions from machine learning models. These application interfaces need to be designed so that the decisions made are unbiased. Rachel Bellamy and Casey Dugan explain how to represent model predictions so that people can recognize if they are fair. Read more.
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14:35–15:15 Wednesday, 10/10/2018
Session
Implementing AI
Location: Westminster Suite Level: Intermediate
Secondary topics:  Edge computing and Hardware
Shaoshan Liu (PerceptIn)
Shaoshan Liu explains how PerceptIn built the first FPGA-based computing system for autonomous driving. Read more.
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14:35–15:15 Wednesday, 10/10/2018
Session
Location: Hilton Meeting Room 3-6
Chris Hillman (Teradata)
Christopher Hillman explores the reasons why AI projects fail and why in some cases this is good and in others bad. Chris then explains how to avoid making the same mistakes again. Read more.
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14:35–15:15 Wednesday, 10/10/2018
Session
AI Business Summit, AI in the Enterprise
Location: Park Suite Level: Intermediate
Secondary topics:  Financial Services, Retail and e-commerce
James Crawford (Orbital Insight)
By some estimates, soon it will require eight million people doing nothing but looking at satellite imagery 24/7 in order to ensure every photo taken on a daily basis is viewed. James Crawford explains how artificial intelligence solves this problem of scale, allowing us to accurately analyze reams of satellite imagery and detect patterns of socioeconomic change in a timely fashion. Read more.

15:15

15:15–16:00 Wednesday, 10/10/2018
Location: Sponsor Pavilion
Afternoon break (45m)

16:00

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16:00–16:40 Wednesday, 10/10/2018
Session
Models and Methods
Location: King's Suite - Sandringham Level: Beginner
Secondary topics:  Computer Vision, Deep Learning models, Ethics, Privacy, and Security, Retail and e-commerce
Pin-Yu Chen (IBM Research AI)
Average rating: *****
(5.00, 1 rating)
Neural networks are particularly vulnerable to adversarial inputs. Carefully designed perturbations can lead a well-trained model to misbehave, raising new concerns about safety-critical and security-critical applications. Pin-Yu Chen offers an overview of CLEVER, a comprehensive robustness measure that can be used to assess the robustness of any neural network classifiers. Read more.
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16:00–16:40 Wednesday, 10/10/2018
Session
Sponsored, TensorFlow at AI
Location: Buckingham Room - Palace Suite
Lucio Floretta (Google Cloud)
Cloud AutoML is a suite of machine learning products that enables developers with limited machine learning expertise to train high-quality models specific to their business needs, leveraging Google’s state-of-the-art transfer learning and neural architecture search technology. Lucio Floretta demonstrates the power and ease of use of AutoML Vision, Translate, and Natural Language. Read more.
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16:00–16:40 Wednesday, 10/10/2018
AI Business Summit
Location: Blenheim Room - Palace Suite
Secondary topics:  Computer Vision, Data Networks and Data Markets
Daeil Kim (AI.Reverie)
Daeil Kim delineates the advantages of synthetic data and explains how to avoid traps that lead to dead zones and false positives. He also reviews work on simulations for synthetic data in application verticals in which it is traditionally difficult to manually acquire significant datasets. Read more.
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16:00–16:40 Wednesday, 10/10/2018
Session
Implementing AI
Location: Windsor Suite Level: Beginner
Secondary topics:  Deep Learning models, Financial Services, Temporal data and time-series
Gaurav Chakravorty explains how recommender systems can be utilized for investment management and details how AI and deep learning are used in trading today. Read more.
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16:00–16:40 Wednesday, 10/10/2018
Session
Implementing AI, Models and Methods
Location: King's Suite - Balmoral Level: Intermediate
Secondary topics:  Media, Marketing, Advertising, Text, Language, and Speech
Rahul Dodhia (Microsoft)
Artificial intelligence is mature enough to make substantial contributions to the legal industry. Rahul Dodhia offers an overview of an AI assistant that can perform routine tasks such as contract review and checking compliance with regulations at higher accuracy rates than legal professionals. Read more.
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16:00–16:40 Wednesday, 10/10/2018
Session
Implementing AI, Interacting with AI
Location: Westminster Suite Level: Intermediate
Secondary topics:  Computer Vision, Deep Learning tools
Anmol Jagetia (Media.net)
Machine learning and object recognition have matured to the point that exciting applications are now possible. Anmol Jagetia demonstrates how to create a Pokédex that uses a camera phone to recognize the Pokémon it's looking at in real time. You'll see how to gather data, prepare your dataset, tune models, and deploy it to a mobile device, using the same tech that is used in self-driving cars. Read more.
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16:00–16:40 Wednesday, 10/10/2018
Session
AI in the Enterprise, Impact of AI on Business and Society
Location: Hilton Meeting Room 3-6 Level: Intermediate
Secondary topics:  Computer Vision, Financial Services
GIORGIA FORTUNA (Machine Learning Reply)
Many industries, including banking, financial sectors, and insurance, continuously face the problem of detecting fraudulent activities. Giorgia Fortuna explores state-of-the-art innovations in fraud detection and explains how unsupervised ML fits into the picture, focusing on signature checks and face recognition. Read more.
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16:00–16:40 Wednesday, 10/10/2018
Session
AI Business Summit, Impact of AI on Business and Society
Location: Park Suite Level: Intermediate
Secondary topics:  Interfaces and UX
Alice Zimmermann (Google)
Average rating: ***..
(3.00, 1 rating)
Fueled by the growth of messaging apps, conversational interfaces are quickly becoming an essential component of every service and product. Join Alice Zimmermann to learn how Google approaches the emerging UX challenges in its conversational agent platform. Along the way, Alice discusses the opportunities in this space and the future of conversation agents. Read more.

16:50

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16:50–17:30 Wednesday, 10/10/2018
Session
Impact of AI on Business and Society, Implementing AI
Location: King's Suite - Sandringham Level: Intermediate
Secondary topics:  Edge computing and Hardware
Kaz Sato (Google)
Average rating: *****
(5.00, 1 rating)
Kaz Sato offers an overview of ML Ops (DevOps for ML), sharing solutions and best practices for bringing ML into production service. You'll learn how to combine Apache Airflow, Kubeflow, and cloud services to build a data pipeline for continuous training and validation, version control, scalable serving, and ongoing monitoring and alerting. Read more.
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16:50–17:30 Wednesday, 10/10/2018
Session
Sponsored, TensorFlow at AI
Location: Buckingham Room - Palace Suite
Zack Akil (Google)
Zack Akil shares pragmatic techniques and useful tools that can help you avoid common pitfalls when building ML, including tools for notebook collaboration and version control that will help prevent you and your teammates from stepping on each others' toes as well as an iterative ML model development approach that will prevent your project from stagnating. Read more.
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16:50–17:30 Wednesday, 10/10/2018
Session
AI Business Summit
Location: Blenheim Room - Palace Suite Level: Beginner
Secondary topics:  AI in the Enterprise
Simon Greenman (Best Practice AI)
We're experiencing an AI gold rush. Tech giants, corporations, startups, and governments are investing billions, and headlines about AI have reached fever pitch. It's dizzying to keep track of the latest AI developments and claims. Join Simon Greenman to learn who can and who will make money in this gold rush—and who will become economic casualties along the way. Read more.
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16:50–17:30 Wednesday, 10/10/2018
Session
Implementing AI
Location: Windsor Suite Level: Intermediate
Secondary topics:  Platforms and infrastructure, Retail and e-commerce, Text, Language, and Speech
Alan Nichol (Rasa)
Average rating: ****.
(4.50, 2 ratings)
Alan Nichol walks you through building fully machine learning-based voice and chatbots with the open source Rasa stack. Read more.
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16:50–17:30 Wednesday, 10/10/2018
Session
Implementing AI
Location: King's Suite - Balmoral Level: Beginner
Secondary topics:  Computer Vision, Media, Marketing, Advertising, Text, Language, and Speech
Daniel Ecer (eLife Sciences Publications Ltd), Paul Shannon (eLife Sciences Publications Ltd)
eLife’s mission is to accelerate discovery and encourage responsible behaviors in science. Daniel Ecer and Paul Shannon detail eLife’s journey in using NLP, computer vision, and similarity algorithms to find more diverse peer reviewers, apply semantics to archive content, automate the submission process, and find insights into the sentiment of scholarly content. Read more.
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16:50–17:30 Wednesday, 10/10/2018
Session
Location: Westminster Suite
Secondary topics:  Reinforcement Learning
Gal Novik (Intel AI)
Gal Novik offers an overview of Reinforcement Learning Coach, an open source Python library that models the interaction between an agent and an environment in a modular way, making it easy for researchers to implement new reinforcement learning algorithms and for data scientists to integrate additional simulation environments modeling their business problems. Read more.
16:50–17:30 Wednesday, 10/10/2018
Location: Hilton Meeting Room 3-6
TBC
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16:50–17:30 Wednesday, 10/10/2018
Session
AI in the Enterprise
Location: Park Suite Level: Beginner
Weiyue Wu (University of Oxford)
Does good technology equal a good product? Not necessarily. Instead of taking only technology into account, you may need to deep dive into the AI ecosystem and look at other players and factors. Weiyue Wu explains how such analysis can help in predicting AI implementation schedules, prioritizing corporate tasks, and allocating resources efficiently. Read more.

17:30

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17:30–18:30 Wednesday, 10/10/2018
Event
Location: Sponsor Pavilion
Come enjoy delicious snacks and beverages with fellow AI Conference attendees, speakers, and sponsors at the Attendee Reception, happening immediately after the afternoon sessions on Tuesday. Read more.

19:00

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19:00–21:00 Wednesday, 10/10/2018
Event
Location: Heist Bank
Join us at Heist Bank, the new playground for grown-ups that's just a short walk from the Hilton Metropole along the Grand Union Canal. Come meet fellow attendees for games, beverages, and wood-fired pizza. Read more.

Thursday, 11/10/2018

8:15

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8:15–8:45 Thursday, 11/10/2018
Event
Location: King's Suite foyer
Ready, set, network! Meet fellow attendees who are looking to connect at the AI Conference. We'll gather before Wednesday and Thursday keynotes for an informal speed networking event. Be sure to bring your business cards—and remember to have fun. Read more.

9:00

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9:00–9:05 Thursday, 11/10/2018
Keynote
Location: King's Suite
Ben Lorica (O'Reilly Media), Roger Chen (Computable Labs)
Program cochairs Ben Lorica and Roger Chen open the second day of keynotes. Read more.

9:05

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9:05–9:15 Thursday, 11/10/2018
Keynote
Location: King's Suite
Kristian Hammond (Northwestern Computer Science)
Kristian Hammond walks you through an approach to bring AI into the enterprise, based on the functional, business aspects of AI technologies. Kristian maps out simple rules, useful metrics, and where AI should live in the org chart, laying out the route you should follow to make good on the promise of the technologies of intelligence. Read more.

9:15

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9:15–9:30 Thursday, 11/10/2018
Keynote
Location: King's Suite
Marc Warner (ASI), Louis Barson (BEIS)
Fireside chat with Marc Warner and Louis Barson Read more.

9:30

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9:30–9:40 Thursday, 11/10/2018
Keynote
Location: King's Suite
Jason Knight (Intel)
Jason Knight offers an overview of the state of the field for scaling training and inference across distributed systems from a practitioner's point of view. Along the way, Jason dives deep into available tools, resources, and venues for getting started without having to go it alone. Read more.

9:40

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9:40–9:55 Thursday, 11/10/2018
Keynote
Location: King's Suite
Secondary topics:  Computer Vision, Ethics, Privacy, and Security, Media, Marketing, Advertising
Supasorn Suwajanakorn (VISTEC (Vidyasirimedhi Institute of Science and Technology))
Supasorn Suwajanakorn discusses the possibilities and the dark side of building artificial people. Read more.

9:55

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9:55–10:15 Thursday, 11/10/2018
Keynote
Location: King's Suite
Cassie Kozyrkov (Google)
Average rating: ***..
(3.00, 2 ratings)
Why do businesses fail at machine learning despite its tremendous potential and the excitement it generates? Is the answer always in data, algorithms, and infrastructure, or is there a subtler problem? Will things improve in the near future? Cassie Kozyrkov shares lessons learned at Google and explains what they mean for applied data science. Read more.

10:15

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10:15–10:30 Thursday, 11/10/2018
Keynote
Location: King's Suite
Michael Chui (McKinsey Global Institute)
Average rating: *****
(5.00, 1 rating)
Drawing on the McKinsey Global Institute's groundbreaking research, Michael Chui explores commonly asked questions relating to AI and its impact on work. Michael also previews new research showing that despite the rapid pace of AI adoption, much foundational work in enterprises remains to be done to capture value at scale. Read more.

10:30

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10:30–10:35 Thursday, 11/10/2018
Keynote
Location: King's Suite
Ben Lorica (O'Reilly Media), Roger Chen (Computable Labs)
Program cochairs Ben Lorica and Roger Chen close the second day of keynotes. Read more.

10:35

10:35–11:05 Thursday, 11/10/2018
Location: Sponsor Pavilion
Morning break (30m)

11:05

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11:05–11:45 Thursday, 11/10/2018
Implementing AI
Location: King's Suite - Sandringham Level: Intermediate
Secondary topics:  Platforms and infrastructure, Retail and e-commerce
Mikio Braun (Zalando SE)
Mikio Braun looks back on the past 20 years of machine learning research to explore aspects of artificial intelligence. He then turns to current examples like autonomous cars and chatbots, putting together a mental model for a reference architecture for artificial intelligence systems. Read more.
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11:05–11:45 Thursday, 11/10/2018
Session
Sponsored, TensorFlow at AI
Location: Buckingham Room - Palace Suite
Daniel Smilkov (Google), Nikhil Thorat (Google)
TensorFlow.js is the recently released JavaScript version of TensorFlow that runs in the browser and Node.js. Daniel Smilkov and Nikhil Thorat offer an overview of the TensorFlow.js ML framework and share a demo of a complete machine learning workflow, including training, client-side deployment, and transfer learning. Read more.
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11:05–11:45 Thursday, 11/10/2018
Session
AI Business Summit
Location: Blenheim Room - Palace Suite Level: Beginner
Secondary topics:  Ethics, Privacy, and Security
Susan Etlinger (Altimeter Group)
Average rating: *****
(5.00, 2 ratings)
Susan Etlinger explores how AI fundamentally changes the relationship between people and businesses, lays out its risks and opportunities, and demonstrates emerging best practices for designing customer-centric and ethical products and services. Read more.
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11:05–11:45 Thursday, 11/10/2018
Session
Location: Windsor Suite
Mounia Lalmas (Spotify)
Average rating: *****
(5.00, 3 ratings)
Understanding user listening behavior is essential for personalizing music listening experiences on Spotify. Mounia Lalmas explains how Spotify uses machine learning recommenders that take into account what and how users consume playlists and the rich diversity of playlist experiences. Read more.
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11:05–11:45 Thursday, 11/10/2018
Models and Methods
Location: King's Suite - Balmoral
Secondary topics:  Deep Learning models, Temporal data and time-series
Vitaly Kuznetsov (Google), Zelda Mariet (MIT)
Vitaly Kuznetsov and Zelda Mariet compare sequence-to-sequence modeling to classical time series models and provide the first theoretical analysis of a framework that uses sequence-to-sequence models for time series forecasting. Read more.
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11:05–11:45 Thursday, 11/10/2018
Location: Westminster Suite
Secondary topics:  Ethics, Privacy, and Security
Andrew Trask (OpenMined)
Andrew Trask details the most important new techniques in secure, privacy-preserving, and multiowner governed artificial intelligence and offers a demonstration of the OpenMined project. Read more.
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11:05–11:45 Thursday, 11/10/2018
Session
Models and Methods
Location: Hilton Meeting Room 3-6 Level: Intermediate
Secondary topics:  Media, Marketing, Advertising, Text, Language, and Speech
Ryan Micallef (Cloudera Fast Forward Labs)
Multitask learning is an approach to problem solving that allows supervised algorithms to master more than one objective in parallel. Ryan Micallef shares a multitask neural net in PyTorch trained to classify news from several publications, which highlights distinct language use per publication enabled by the analysis of task-specific and agnostic representations part of multitask networks. Read more.
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11:05–11:45 Thursday, 11/10/2018
Session
AI Business Summit, Impact of AI on Business and Society
Location: Park Suite Level: Beginner
Secondary topics:  Computer Vision, Ethics, Privacy, and Security
Marc Warner (ASI)
Average rating: ****.
(4.00, 1 rating)
How can AI impact national security? Collaborating with the UK Home Office Counterterrorism Unit, ASI Data Science built a tool that removes extremist propaganda from the web. Drawing on this experience, Marc Warner discusses the role of AI in the fight against terror and explains how shared access to this technology may be part of the answer. Read more.

11:55

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11:55–12:35 Thursday, 11/10/2018
Session
Models and Methods
Location: King's Suite - Sandringham Level: Intermediate
Secondary topics:  Deep Learning models, Retail and e-commerce, Text, Language, and Speech
Dafna Shahaf (The Hebrew University of Jerusalem)
Average rating: ****.
(4.00, 1 rating)
The availability of large idea repositories (e.g., patents) could significantly accelerate innovation and discovery by providing people inspiration from solutions to analogous problems. Dafna Shahaf presents an algorithm that automatically discovers analogies in unstructured data and demonstrates how these analogies significantly increased people's likelihood of generating creative ideas. Read more.
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11:55–12:35 Thursday, 11/10/2018
Session
Sponsored, TensorFlow at AI
Location: Buckingham Room - Palace Suite
Brian Lee (Google Brain), Priya Gupta (Google)
TensorFlow AutoGraph automatically converts plain Python code into its TensorFlow equivalent, using source code transformation. Brian Lee and Priya Gupta demonstrate how to distribute your training in TensorFlow easily across multiple accelerators and machines. Read more.
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11:55–12:35 Thursday, 11/10/2018
Session
AI Business Summit
Location: Blenheim Room - Palace Suite Level: Beginner
Secondary topics:  Ethics, Privacy, and Security, Interfaces and UX
Max Gadney (After the flood), Sabih Ali (After the Flood)
Max Gadney and Sabih Ali explore some of the ways designers and product teams are designing systems with transparency, trust, and privacy in mind. Read more.
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11:55–12:35 Thursday, 11/10/2018
Session
Location: Windsor Suite
Secondary topics:  Edge computing and Hardware, Platforms and infrastructure
Cormac Brick (Intel)
Recent research has shown that training for quantization can lead to large gains in energy efficiency, and embedded runtime packages like TensorFlow Lite and Caffe2Go offer portability over a number of platforms. Cormac Brick asks, Why can't we have both performance and portability? Cormac explores industry challenges and details the progress needed to close the portability-performance gap. Read more.
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11:55–12:35 Thursday, 11/10/2018
Models and Methods
Location: King's Suite - Balmoral Level: Intermediate
Secondary topics:  Deep Learning models
David Barber (UCL)
While great strides have been made in perceptual AI (for example, in speech recognition), there's been relatively modest progress in reasoning AI—systems that can interact with us in natural ways and understand the objects in our environment. David Barber explains why general AI will be out of reach until we address how to endow machines with knowledge of our environment. Read more.
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11:55–12:35 Thursday, 11/10/2018
Session
AI in the Enterprise
Location: Westminster Suite Level: Intermediate
Secondary topics:  AI in the Enterprise
Christopher Nguyen shares lessons learned implementing multiple AI commercial projects at Panasonic. Along the way, Christopher discusses a number of use cases at various stages of implementation maturity and explains what AI really means today in enterprise products, where the key opportunities are, their impact, and key success factors in the adoption of AI across the enterprise. Read more.
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11:55–12:35 Thursday, 11/10/2018
Session
Implementing AI
Location: Hilton Meeting Room 3-6 Level: Intermediate
Secondary topics:  Temporal data and time-series
Aileen Nielsen (Skillman Consulting)
Average rating: *****
(5.00, 1 rating)
Deep learning for time series prediction has made rapid progress in the past few years, but performance still greatly lags that of other intelligence tasks. Aileen Nielsen offers an overview of the state of the art in 2018, covering the hottest new architectures, emerging best practices for RNN training, and long overdue standard metrics to measure and compete on neural network prediction. Read more.
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11:55–12:35 Thursday, 11/10/2018
Session
AI Business Summit, Implementing AI
Location: Park Suite Level: Intermediate
Secondary topics:  Deep Learning models, Platforms and infrastructure
The common perception of applying deep learning is that you take an open source or research model, train it on raw data, and deploy the result as a fully self-contained artifact. The reality is far more complex. Nick Pentreath shares lessons learned building a deep learning model exchange and discusses the future of standardized cross-framework deep learning model training and deployment. Read more.

12:35

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12:35–13:45 Thursday, 11/10/2018
Event
Location: Sponsor Pavilion
Topic Table discussions are a great way to informally network with people in similar industries or interested in the same topics. Read more.
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12:35–13:45 Thursday, 11/10/2018
Event
Location: Thames
Join fellow executives, business leaders, and strategists for a networking lunch on Thursday for AI Business Summit attendees and speakers. Read more.

13:45

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13:45–14:25 Thursday, 11/10/2018
Session
Implementing AI
Location: King's Suite - Sandringham Level: Beginner
Thomas Endres (TNG Technology Consulting), Samuel Hopstock (TNG Technology Consulting)
Thomas Endres and Samuel Hopstock demonstrate how to apply machine learning techniques on a program's source code, covering problems you may encounter, how to get enough relevant training data, how to encode the source code as a feature vector so that it can be processed mathematically, what machine learning algorithms to use, and more. Read more.
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13:45–14:25 Thursday, 11/10/2018
Session
Sponsored, TensorFlow at AI
Location: Buckingham Room - Palace Suite
Thomas Norrie (Google)
Training complex machine learning models with large amounts of data can take a very long time. Thomas Norrie explores methods for accelerating this process by distributing training across multiple accelerators and machines and leads a technical deep dive into Google Cloud’s TPU accelerators. Read more.
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13:45–14:25 Thursday, 11/10/2018
Session
AI Business Summit, AI in the Enterprise
Location: Blenheim Room - Palace Suite Level: Intermediate
Secondary topics:  AI in the Enterprise
AI is a key innovation accelerator for digital business transformation. To help you with your strategic roadmap, Philip Carnelley shares IDC's research into the AI market across hundreds of European organizations and explains why organizations should establish a digital platform based on big data, AI, and cloud technologies, with an intelligent core, as part of their transformation strategy. Read more.
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13:45–14:25 Thursday, 11/10/2018
Session
Implementing AI, Models and Methods
Location: Windsor Suite Level: Intermediate
Secondary topics:  Computer Vision, Deep Learning models, Retail and e-commerce
Florian Wilhelm (inovex GmbH)
Average rating: *****
(5.00, 1 rating)
Even in the age of big data, labeled data is a scarce resource in many machine learning use cases. Florian Wilhelm evaluates generative adversarial networks (GANs) when used to extract information from vehicle registrations under a varying amount of labeled data, compares the performance with supervised learning techniques, and demonstrates a significant improvement when using unlabeled data. Read more.
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13:45–14:25 Thursday, 11/10/2018
Session
Models and Methods
Location: King's Suite - Balmoral Level: Intermediate
Secondary topics:  Media, Marketing, Advertising, Text, Language, and Speech
Guy Feigenblat (IBM Research AI)
Average rating: ****.
(4.00, 3 ratings)
Automatic summarization is the computational process of shortening one or more text documents in order to identify their key points. Guy Feigenblat surveys recent advances in unsupervised automated summarization technologies and discusses recent research publications and datasets. Guy concludes with an overview of a novel summarization technology developed by IBM. Read more.
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13:45–14:25 Thursday, 11/10/2018
Session
Implementing AI, Models and Methods
Location: Westminster Suite Level: Intermediate
Secondary topics:  Computer Vision, Deep Learning models, Text, Language, and Speech
Lars Hulstaert (Microsoft)
Transfer learning allows data scientists to leverage insights from large labeled datasets. The general idea of transfer learning is to use knowledge learned from tasks for which a lot of labeled data is available in settings where only little labelled data is available. Lars Hulstaert explains what transfer learning is and demonstrates how it can boost your NLP or CV pipelines. Read more.
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13:45–14:25 Thursday, 11/10/2018
Implementing AI
Location: Hilton Meeting Room 3-6
Secondary topics:  Ethics, Privacy, and Security
Katharine Jarmul (KIProtect)
When you train a model on private data, how much of that information does the model retain? Katharine Jarmul reviews research on attacks against models to extract training data and expose potentially sensitive information. Katharine then shares potential defenses as well as best practices when training models using private or sensitive data. Read more.
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13:45–14:25 Thursday, 11/10/2018
Session
AI Business Summit, AI in the Enterprise, Interacting with AI
Location: Park Suite Level: Intermediate
Chris Boyd (The Wall Street Journal), John Wiley (The Wall Street Journal)
Chris Boyd and John Wiley explain how the Wall Street Journal uses machine learning and a proprietary algorithm to predict the likelihood for someone subscribing, which in turn dictates the paywall experience that customer receives. Read more.

14:35

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14:35–15:15 Thursday, 11/10/2018
Session
Location: King's Suite - Sandringham
Secondary topics:  Edge computing and Hardware, Platforms and infrastructure
Ananth Sankar (Intel), Valeriu Codreanu (SURFsara), Damian Podareanu (SURFsara), Colin Healy (Dell EMC)
SURFSara and Intel collaborated as part of the Intel Parallel Computing Center initiative to advance the state of large-scale neural network training on Intel Xeon CPU-based servers. Ananth Sankar, Valeriu Codreanu, Damian Podareanu, and Steve Smith share insights on several best-known methods for neural network training and present results from tests performed on Stanford's CheXNet project. Read more.
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14:35–15:15 Thursday, 11/10/2018
Session
Sponsored, TensorFlow at AI
Location: Buckingham Room - Palace Suite
Pete Warden (Google)
Pete Warden discusses the surprising effectiveness of deep learning on low-power devices. Read more.
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14:35–15:15 Thursday, 11/10/2018
Session
AI Business Summit
Location: Blenheim Room - Palace Suite Level: Intermediate
Secondary topics:  Media, Marketing, Advertising, Retail and e-commerce
Bessie Lee (Withinlink), Ching Law (Tencent)
Advertising in China is on the frontline of AI adoption and innovation. Join Bessie Lee and Ching Law for a conversation on how AI is changing advertising. You'll hear how China's white-hot AI advertising applications can serve as roadmaps and spark ideas in other industries and how companies like Tencent are improving performance by leveraging AI technology. Read more.
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14:35–15:15 Thursday, 11/10/2018
Session
Implementing AI
Location: Windsor Suite Level: Advanced
Secondary topics:  Deep Learning models
On his journey to the top spot at Kaggle, Marios Michailidis noticed that many of the things he does to perform competitively in data challenges could be automated. Marios shares lessons learned from his Kaggle experience and shows how you can achieve competitive performance in predictive modeling tasks automatically, using H2O.ai’s Driverless AI—an AI that creates AI. Read more.
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14:35–15:15 Thursday, 11/10/2018
Session
Models and Methods
Location: King's Suite - Balmoral Level: Beginner
Secondary topics:  Financial Services, Media, Marketing, Advertising, Text, Language, and Speech
Amy Heineike (Primer)
Average rating: ***..
(3.67, 3 ratings)
When building natural language processing (NLP)-based applications, you quickly learn that no single NLP algorithm can handle the wide range of tasks required to turn text into value. Amy Heineike explains how she orchestrates natural language processing, understanding, and generation algorithms to build text-based AI applications for Fortune 500 companies. Read more.
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14:35–15:15 Thursday, 11/10/2018
Models and Methods
Location: Westminster Suite
Secondary topics:  Data Networks and Data Markets
Roger Chen (Computable Labs)
Blockchain technologies offer new internet primitives for creating open and online data marketplaces. Roger Chen explores how data markets can be constructed and how they offer a shared resource on the internet for AI-based research, discovery, and development. Read more.
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14:35–15:15 Thursday, 11/10/2018
Session
Models and Methods
Location: Hilton Meeting Room 3-6 Level: Beginner
Secondary topics:  Deep Learning models, Interfaces and UX, Text, Language, and Speech
Peter Cahill (Voysis)
Peter Cahill explains why Wavenet will be the next generation of recognition, synthesis, and voice-activity detection. Read more.
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14:35–15:15 Thursday, 11/10/2018
Session
AI Business Summit, AI in the Enterprise, Impact of AI on Business and Society
Location: Park Suite Level: Intermediate
Secondary topics:  Ethics, Privacy, and Security
Aileen Nielsen (Skillman Consulting)
We're in the year of the AI fake out. "Fake news" is the order of the day, as nebulous chatbots have become significant political actors. Startups peddle robotically handwritten notes and algorithmically personalized gifts for our loved ones. Soon we won't even be able to tell if a customer service agent is a real person. Aileen Nielsen asks, How should we redefine intelligence as fakes flourish? Read more.

15:15

15:15–16:00 Thursday, 11/10/2018
Location: Sponsor Pavilion
Afternoon break (45m)

16:00

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16:00–16:40 Thursday, 11/10/2018
Session
Models and Methods
Location: King's Suite - Sandringham Level: Intermediate
Secondary topics:  Computer Vision, Edge computing and Hardware, Platforms and infrastructure
Paul Brasnett (Imagination Technologies )
In recent years, we’ve seen a shift from traditional vision algorithms to deep neural network algorithms. While many companies expect to move to deep learning for some or all of their algorithms, they may have a significant investment in classical vision. Paul Brasnett explains how to express and adapt a classical vision algorithm to become a trainable DNN. Read more.
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16:00–16:40 Thursday, 11/10/2018
Session
TensorFlow at AI
Location: Buckingham Room - Palace Suite
Kenny Song (Google), Quentin de Laroussilhe (Google)
As machine learning evolves from experimentation to serving production workloads, so does the need to effectively manage the end-to-end training and serving workflow. Kenny Song and Quentin de Laroussilhe offer an overview of TensorFlow Extended, the end-to-end machine learning platform for TensorFlow that powers products across all of Google. Read more.
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16:00–16:40 Thursday, 11/10/2018
Session
AI Business Summit, Impact of AI on Business and Society
Location: Blenheim Room - Palace Suite Level: Advanced
Secondary topics:  Ethics, Privacy, and Security, Interfaces and UX
Marie Johnson (Centre for Digital Business Pty Ltd)
What does a workforce augmented by digital humans look like? Marie Johnson shares the story of the creation of Nadia, the world’s first digital human for service delivery. Drawing on her experience developing the concept and leading the delivery, Marie presents a framework to help leaders meet exponential changes across industries augmented by digital humans, including healthcare. Read more.
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16:00–16:40 Thursday, 11/10/2018
Session
Implementing AI, Models and Methods
Location: Windsor Suite Level: Beginner
Secondary topics:  Computer Vision, Deep Learning models, Deep Learning tools
Vanja Paunic (Microsoft), Patrick Buehler (Microsoft)
Average rating: **...
(2.00, 2 ratings)
Dramatic progress has been made in computer vision. Deep neural networks (DNNs) trained on millions of images can recognize thousands of different objects, and they can be customized to new use cases. Vanja Paunic and Patrick Buehler outline simple methods and tools that enable users to easily and quickly adapt Microsoft's state-of-the-art DNNs for use in their own computer vision solutions. Read more.
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16:00–16:40 Thursday, 11/10/2018
Session
Implementing AI, Models and Methods
Location: King's Suite - Balmoral Level: Intermediate
Secondary topics:  Reinforcement Learning, Retail and e-commerce, Text, Language, and Speech
Dr. Sid J Reddy (Conversica)
Sid Reddy shows you how to avoid the hype and decide which use cases are the best for deep reinforcement learning. You'll explore the Markov decision process with conversational AI and learn how to set up the environment, states, agent actions, transition probabilities, reward functions, and end states. You'll also discover when to use end-to-end reinforcement learning. Read more.
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16:00–16:40 Thursday, 11/10/2018
Session
Implementing AI
Location: Westminster Suite Level: Beginner
Secondary topics:  Edge computing and Hardware
Jameson Toole (Fritz)
Machine learning and AI models now outperform humans on many tasks. However, sending sensor data up to the cloud and back is too slow for many apps and autonomous machines. Jameson Toole explains why developers seeking to provide seamless user experiences must now move their models down to devices on the edge, where they can run faster, at lower cost, and with greater privacy. Read more.
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16:00–16:40 Thursday, 11/10/2018
Session
AI in the Enterprise, Impact of AI on Business and Society
Location: Hilton Meeting Room 3-6 Level: Intermediate
Secondary topics:  Interfaces and UX
Archisman Majumdar (Mphasis)
Archisman Majumdar and Jai Ganesh describe the effects of AI techniques on frontend GUI development—specifically, the use of automatically generated code and architecture from text descriptions—and share deep learning techniques for text-to-image creation and template-to-code generation, along with cloud technologies in automated deployment, management, and scaling of such applications. Read more.
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16:00–16:40 Thursday, 11/10/2018
Session
AI Business Summit, AI in the Enterprise, Impact of AI on Business and Society
Location: Park Suite Level: Intermediate
Secondary topics:  Temporal data and time-series
Ira Cohen (Anodot)
With the more applications of machine learning-based applications, the complex algorithms that automate behaviors can get out of control. Ira Cohen explains how to catch problems and glitches early on by using machine learning algorithms to monitor these algorithms for anomalous behavior. Read more.

16:50

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16:50–17:30 Thursday, 11/10/2018
Session
Implementing AI
Location: King's Suite - Sandringham Level: Beginner
Secondary topics:  Computer Vision
natalie fridman (ImageSat International (iSi))
Average rating: ****.
(4.00, 1 rating)
Detection of moving vessels with satellite sensors is a challenging problem. Satellite imagery is expensive, covers a very small area, and can be acquired only at predefined acquisition opportunities. Natalie Fridman dives into this challenging problem and shares ISI's AI-based solution along with successful examples of detecting maritime vessels with ISI's satellites. Read more.
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16:50–17:30 Thursday, 11/10/2018
Session
Sponsored, TensorFlow at AI
Location: Buckingham Room - Palace Suite
Sara Robinson (Google)
Whether you’re new to machine learning (ML) or you’re already an expert, Google Cloud Platform (GCP) has a variety of tools to help you. Sara Robinson starts with the basics: how to use a pretrained ML model with a single API call. She then demonstrates how to customize a pretrained model with AutoML. Sara concludes by explaining how to train and serve a custom TensorFlow model on GCP. Read more.
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16:50–17:30 Thursday, 11/10/2018
Session
AI Business Summit
Location: Blenheim Room - Palace Suite Level: Intermediate
Secondary topics:  AI in the Enterprise
Benjamin Wright-Jones (Microsoft), Simon Lidberg (Microsoft)
As organizations turn to data-driven strategies, there's been increasing interest in creating AI centers of excellence (COEs). Benjamin Wright-Jones and Simon Lidberg take you through the building blocks of a center of excellence and describe the value for organizations embarking on data-driven strategies. Read more.
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16:50–17:30 Thursday, 11/10/2018
Session
AI in the Enterprise, Implementing AI
Location: Windsor Suite Level: Intermediate
Secondary topics:  Platforms and infrastructure
Christopher Cho (Google), David Sabater (Google)
Christopher Cho details how to leverage Kubernetes and the mighty Kubernetes APIs to build a complete deep learning pipeline, from data ingestion and aggregation to preprocessing and ML training to serving. Along the way, Christopher covers Kubeflow, a Google open source solution for managing machine learning with TensorFlow in a portable, scalable manner. Read more.
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16:50–17:30 Thursday, 11/10/2018
Session
Impact of AI on Business and Society
Location: King's Suite - Balmoral Level: Beginner
Secondary topics:  Financial Services, Temporal data and time-series
Johnnie Ball (Fluidly)
Average rating: *****
(5.00, 1 rating)
Cashflow is responsible for 80–90% of UK SME failure. Fluidly uses the wealth of financial data available through APIs to instantly predict cashflow. Johnnie Ball details how the company built an automated cashflow engine, explores the challenges faced in applying AI to financial data, and explains how machine learning can redefine how we think about established approaches to modeling. Read more.
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16:50–17:30 Thursday, 11/10/2018
Session
Implementing AI
Location: Westminster Suite Level: Intermediate
Secondary topics:  Edge computing and Hardware, Platforms and infrastructure
Zhipeng Huang (Huawei)
Zhipeng Huang explains how resource representation (RR) works with various intermediate representation (IR) technologies to help achieve the democratization of AI. Read more.
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16:50–17:30 Thursday, 11/10/2018
Session
Implementing AI
Location: Park Suite Level: Beginner
Alasdair Allan (Babilim Light Industries)
Average rating: *****
(5.00, 1 rating)
Google's AIY Projects kits bring Google's machine learning algorithms to developers with limited experience in the field, allowing them to prototype machine learning applications and smart hardware more easily. Alasdair Allan walks you through setting up and building the kits and demonstrates how to use the kits' Python SDK for machine learning both in the cloud and locally on a Raspberry Pi. Read more.