Presented By
O’Reilly + Intel AI
Put AI to Work
April 15-18, 2019
New York, NY

Monday, 04/15/2019

9:00am

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9:00am–5:00pm Monday, 04/15/2019
Training
AI Business Summit
Location: Clinton
Secondary topics:  AI in the Enterprise
Michael Li (The Data Incubator), Russ Martin (The Data Incubator)
This course is a non-technical overview of AI and data science. You’ll learn common techniques, how to apply them in your organization, and common pitfalls to avoid. Though this course, you’ll pick up the language and develop a framework to be able to effectively engage with technical experts and utilize their input and analysis for your business’s strategic priorities and decision making. Read more.
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9:00am–5:00pm Monday, 04/15/2019
Training
Implementing AI
Location: Madison
Secondary topics:  Deep Learning and Machine Learning tools
Dylan Bargteil (The Data Incubator)
The TensorFlow library provides for the use of computational graphs, with automatic parallelization across resources. This architecture is ideal for implementing neural networks. This training will introduce TensorFlow's capabilities in Python. It will move from building machine learning algorithms piece by piece to using the Keras API provided by TensorFlow with several hands-on applications. Read more.
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9:00am–5:00pm Monday, 04/15/2019
Training
Location: Harlem Suite
Secondary topics:  Deep Learning and Machine Learning tools
Ana Hocevar (The Data Incubator)
PyTorch is a machine learning library for Python that allows users to build deep neural networks with great flexibility. Its easy to use API and seamless use of GPUs make it a sought-after tool for deep learning. This course will introduce the PyTorch workflow and demonstrate how to use it. Students will be equipped with the knowledge to build deep learning models using real-world datasets. Read more.
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9:00am–5:00pm Monday, 04/15/2019
Training
Implementing AI, Models and Methods
Location: Green Room
Secondary topics:  Deep Learning and Machine Learning tools, Financial Services, Models and Methods, Temporal data and time-series
Francesca Lazzeri (Microsoft), Wee Hyong Tok (Microsoft), Krishna Anumalasetty (Microsoft)
Francesca Lazzeri will walk you through the core steps for using Azure Machine Learning services to train your machine learning models both locally and on remote compute resources. Read more.
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9:00am–5:00pm Monday, 04/15/2019
Training
Location: Hudson Suite
Wenming Ye (Amazon Web Services)
Machine learning (ML) and deep learning (DL) projects are becoming increasingly common at enterprises and startups alike and have been a key innovation engine for Amazon businesses such as Go, Alexa, and Robotics. In this 2 day training, Wenming Ye (AWS) and Miro Enev (Nvidia) offer a practical next step in DL learning with instructions, demos, and hands-on labs. Read more.
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9:00am–5:00pm Monday, 04/15/2019
Training
Implementing AI, Models and Methods
Location: Midtown Suite
Secondary topics:  Deep Learning and Machine Learning tools, Models and Methods, Text, Language, and Speech
Delip Rao (R7 Speech Science)
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.

10:30am

10:30am–11:00am Monday, 04/15/2019
Location: TBD
Morning Break (30m)

12:30pm

12:30pm–1:30pm Monday, 04/15/2019
Location: TBD
Lunch (1h)

3:00pm

3:00pm–3:30pm Monday, 04/15/2019
Location: TBD
Afternoon Break (30m)

Tuesday, 04/16/2019

9:00am

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Add to your personal schedule
Add to your personal schedule
Add to your personal schedule
Add to your personal schedule
Add to your personal schedule
9:00am–12:30pm Tuesday, 04/16/2019
Tutorial
Models and Methods
Location: Beekman
Secondary topics:  Deep Learning and Machine Learning tools, Models and Methods
Gunnar Carlsson (Ayasdi)
Using Topological Data Analysis, one can describe the functioning and learning of a neural network in a compact and understandable way. This understanding results in material speedups in performance (training time + accuracy) and allows for data-type customization of neural network architectures to further boost performance and widen the applicability of the method to all data sets. Read more.
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9:00am–12:30pm Tuesday, 04/16/2019
Tutorial
Location: Sutton South
Secondary topics:  Financial Services, Models and Methods, Text, Language, and Speech
Garrett Hoffman (StockTwits)
Garrett Hoffman walks you through deep learning methods for natural language processing and natural language understanding tasks, using a live example in Python and TensorFlow with StockTwits data. Methods include word2vec, recurrent neural networks and variants (LSTM, GRU), and convolutional neural networks. Read more.
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9:00am–12:30pm Tuesday, 04/16/2019
Tutorial
Implementing AI
Location: Regent Parlor
Secondary topics:  Deep Learning and Machine Learning tools, Ethics, Privacy, and Security
Rachel Bellamy (IBM Research), Kush Varshney (IBM Research), Karthikeyan Natesan Ramamurthy (IBM), Michael Hind (IBM Research AI)
Learn to use and contribute to the new open-source Python package AI Fairness 360 directly from its creators. Architected to translate new developments from research labs to data science practitioners in industry, this is the first comprehensive toolkit with metrics to check for unwanted bias in datasets and machine learning models, and state-of-the-art algorithms to mitigate such bias. Read more.
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9:00am–12:30pm Tuesday, 04/16/2019
Tutorial
AI Business Summit
Location: Mercury Ballroom
Secondary topics:  AI in the Enterprise, Interfaces and UX
Chris Butler (IPSoft)
Purpose, a well-defined problem, and trust from people are important factors to any system, especially those that employ AI. Chris Butler leads you through exercises that borrow from the principles of design thinking to help you create more impactful solutions and better team alignment. Read more.
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9:00am–12:30pm Tuesday, 04/16/2019
Tutorial
Implementing AI
Location: Mercury Rotunda
Secondary topics:  Deep Learning and Machine Learning tools
Mo Patel (Independent)
This tutorial will focus on all aspects of the PyTorch lifecycle via hand on examples such as image classification, text classification, and linear modeling. Other aspects of machine learning such as transfer learning, data modeling and deploying to production will be covered via immersive labs. Read more.
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Add to your personal schedule
9:00am–5:00pm Tuesday, 04/16/2019
Tutorial
AI Business Summit
Location: Sutton North/Center
Secondary topics:  AI in the Enterprise
Kristian Hammond (Northwestern Computer Science)
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.

10:30am

10:30am–11:00am Tuesday, 04/16/2019
Location: TBD
Morning Break (30m)

12:30pm

12:30pm–1:45pm Tuesday, 04/16/2019
Location: TBD
Lunch (Sponsored by Intel AI) (1h 15m)

1:45pm

Add to your personal schedule
1:45pm–5:15pm Tuesday, 04/16/2019
Tutorial
Location: Beekman
Secondary topics:  Deep Learning and Machine Learning tools, Reinforcement Learning
Robert Nishihara (UC Berkeley), Philipp Moritz (UC Berkeley), Ion Stoica (UC Berkeley)
Ray is a general purpose framework for programming your cluster. We will lead a deep dive into Ray, walking you through its API and system architecture and sharing application examples, including several state-of-the-art AI algorithms. Read more.
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1:45pm–5:15pm Tuesday, 04/16/2019
Tutorial
Implementing AI
Location: Sutton South
Secondary topics:  Models and Methods, Temporal data and time-series
Bruno Goncalves (JPMorgan Chase & Co.)
Time series are everywhere around us. Understanding them requires taking into account the sequence of values seen in previous steps and even long-term temporal correlations. Join Bruno Gonçalves to learn how to use recurrent neural networks to model and forecast time series and discover the advantages and disadvantages of recurrent neural networks with respect to more traditional approaches. Read more.
1:45pm–5:15pm Tuesday, 04/16/2019
Location: Regent Parlor
TUTORIAL TBC
Add to your personal schedule
1:45pm–5:15pm Tuesday, 04/16/2019
Tutorial
AI Business Summit
Location: Mercury Ballroom
Secondary topics:  AI in the Enterprise, Financial Services, Media, Marketing, Advertising
Alex Siegman (Dow Jones), Kabir Seth (Wall Street Journal)
This tutorial walks attendees through the steps necessary to appropriately leverage AI in a large organization: This includes ways to identify business opportunities that lend themselves to AI, as well as best practices on everything from data intake and manipulation to model selection, output analysis, development and deployment, all while navigating a complex organizational structure. Read more.
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1:45pm–5:15pm Tuesday, 04/16/2019
Tutorial
Implementing AI
Location: Mercury Rotunda
Secondary topics:  Deep Learning and Machine Learning tools, Text, Language, and Speech
In this workshop, you will get hands-on experience in developing intelligent AI assistants based entirely on machine learning and using only open source tools - Rasa NLU and Rasa Core. You will learn the fundamentals of conversational AI and the best practices of developing AI assistants that scale and learn from real conversational data. Read more.
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1:45pm–5:15pm Tuesday, 04/16/2019
Tutorial
Location: Grand Ballroom West
Join us to experience a series of rapid-fire demos and presentations by Intel® AI Builders members that show how to quickly solve enterprise business problems by working with Intel and its partners. Following this showcase, there will be a networking cocktail party. Read more.

3:00pm

3:00pm–3:30pm Tuesday, 04/16/2019
Location: TBD
Afternoon Break (30m)

5:15pm

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5:15pm–7:15pm Tuesday, 04/16/2019
Event
Location: Mercury Ballroom
Ignite is happening at AI in New York on Tuesday, April 16. Join us for a fun, high-energy evening of five-minute talks—all aspiring to live up to the Ignite motto: Enlighten us, but make it quick. Read more.

7:30pm

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7:30pm–9:30pm Tuesday, 04/16/2019
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 New York City has to offer. Read more.

Wednesday, 04/17/2019

8:00am

8:00am–8:50am Wednesday, 04/17/2019
Location: Various Locations
Morning Coffee (Sponsored by NetApp) (50m)

8:15am

Add to your personal schedule
8:15am–8:45am Wednesday, 04/17/2019
Event
Location: 3rd Floor West Promenade
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.

8:45am

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8:45am–8:55am Wednesday, 04/17/2019
Keynote
Location: Grand Ballroom West
Ben Lorica (O'Reilly Media), Roger Chen (Computable)
Opening Remarks Read more.

8:55am

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8:55am–9:05am Wednesday, 04/17/2019
Keynote
Location: Grand Ballroom West
Ben Lorica (O'Reilly Media), Roger Chen (Computable)
Keynote by Ben Lorica and Roger Chen Read more.

9:05am

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9:05am–9:20am Wednesday, 04/17/2019
Keynote
Location: Grand Ballroom West
Gadi Singer (Intel)
TBD Read more.

9:20am

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9:20am–9:35am Wednesday, 04/17/2019
Keynote
Location: Grand Ballroom West
In this talk, Aleksander will discuss major roadblocks that prevent the current AI framework from having this kind of broad impact and will outline approaches to addressing these issues and making this framework truly "human-ready". Read more.

9:35am

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9:35am–9:45am Wednesday, 04/17/2019
Keynote
Location: Grand Ballroom West
Danielle Dean (Microsoft)
TBD Read more.

9:45am

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9:45am–10:00am Wednesday, 04/17/2019
Keynote
Location: Grand Ballroom West
Desiree Gosby (Intuit)
Language is one of the most powerful tools in our highly social, interconnected society. If it takes years for a child to read proficiently, how is it possible to translate such a nuanced, complicated, human-centric concept like reading and comprehension for a computer? How do you write code to understand context cues? Read more.

10:00am

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10:00am–10:15am Wednesday, 04/17/2019
Keynote
Location: Grand Ballroom West
Tony Jebara (Netflix & Columbia University)
For many years, the main goal of the Netflix recommendation system has been to get the right titles in front of each member at the right time. Today, we use nonlinear, probabilistic, and deep learning approaches to make even better rankings of our movies and TV shows for each user. Read more.

10:15am

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10:15am–10:20am Wednesday, 04/17/2019
Keynote
Location: Grand Ballroom West
Keynote by Joleen Liang (Sponsored by Squirrel AI) Read more.

10:20am

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10:20am–10:30am Wednesday, 04/17/2019
Keynote
Location: Grand Ballroom West
Martial Hebert (Carnegie Mellon University)
This talk will give a brief overview of current challenges in AI for Robotics, and a glimpse of the exciting developments emerging in current research. Read more.

10:30am

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10:30am–10:35am Wednesday, 04/17/2019
Keynote
Location: Grand Ballroom West
Closing Remarks Read more.

10:35am

10:35am–11:05am Wednesday, 04/17/2019
Location: TBD
Morning Break (Sponsored by Squirrel AI) (30m)

11:05am

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11:05am–11:45am Wednesday, 04/17/2019
40-minute session
AI Business Summit, Case Studies
Location: Sutton North/Center
Secondary topics:  AI case studies, Interfaces and UX, Media, Marketing, Advertising
Lucy Wang (BuzzFeed), Swara Kantaria (BuzzFeed)
As BuzzFeed’s content production and social networks grow, curation becomes increasingly difficult. To this end, we first built publishing tools that let people work more efficiently. Now, we build artificial intelligence tools that let people work more intelligently. During this talk we plan to share this evolution with the audience. Read more.
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11:05am–11:45am Wednesday, 04/17/2019
40-minute session
Case Studies, Machine Learning
Location: Sutton South
Secondary topics:  AI case studies, Financial Services
Pamela Vagata (Stripe)
Explore how Stripe applies deep-learning to user-behavior for fraud detection. This deep-dive will include data-preparation, modeling methods and performance comparisons. Read more.
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11:05am–11:45am Wednesday, 04/17/2019
Models and Methods
Location: Regent Parlor
Secondary topics:  Computer Vision, Ethics, Privacy, and Security, Models and Methods
Siwei Lyu (University of Albany)
In this talk, I will first briefly review the evolution of techniques behind the generation of fake media, and then introduce several projects I was involved in digital media forensics for detection of fake media, with a special focus on some of our recent works on detecting AI-generated fake videos (DeepFakes). Read more.
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11:05am–11:45am Wednesday, 04/17/2019
40-minute session
AI Business Summit, Executive Briefing/Best Practices
Location: Mercury Ballroom
Secondary topics:  AI in the Enterprise, Data and Data Networks, Ethics, Privacy, and Security, Health and Medicine, Retail and e-commerce
Deepashri Varadharajan (CB Insights)
At CB Insights, we track over 3,000 AI startups across 25+ verticals. While every vertical has benefited from deep learning and better hardware processing, the bottlenecks and opportunities are unique to each sector. We will explore what is driving AI applications in different verticals like healthcare, retail, and security, and analyze emerging business models. Read more.
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11:05am–11:45am Wednesday, 04/17/2019
40-minute session
Implementing AI
Location: Mercury Rotunda
Secondary topics:  Deep Learning and Machine Learning tools
joshua gordon (Google)
Learn about the very latest in TensorFlow direct from Google. We will focus on TensorFlow 2.0 and its easy-to-use eager execution. We'll also cover how to use our revised high-level API, and pitfalls and tricks to get performance on accelerator hardware. Read more.
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11:05am–11:45am Wednesday, 04/17/2019
40-minute session
Models and Methods
Location: Grand Ballroom West
Secondary topics:  Models and Methods
Lise Getoor (University of California, Santa Cruz)
Much of today's data is noisy, incomplete, heterogeneous in nature, and interlinked in a myriad of complex ways. In this talk, I will describe AI methods that are able to exploit both the inherent uncertainty and the innate structure in a domain. I will describe both the benefit of utilizing structure and the inherent risk of ignoring structure. Read more.
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11:05am–11:45am Wednesday, 04/17/2019
40-minute session
Implementing AI
Location: Rendezvous
Secondary topics:  Deep Learning and Machine Learning tools, Edge computing and Hardware, Platforms and infrastructure
Mathew Salvaris (Microsoft), Fidan Boylu Uz (Microsoft)
Interested in deep learning models and how to deploy them on Kubernetes at production scale? Not sure if you need to use GPUs or CPUs? This session will help you by providing a step-by-step guide to go from a pre-trained deep learning model, package it in a Docker container and deploy as a webservice on Kubernetes cluster. Read more.
11:05am–11:45am Wednesday, 04/17/2019
Location: Clinton
TBC
11:05am–11:45am Wednesday, 04/17/2019
Location: Beekman
TBC

11:50am

Add to your personal schedule
11:50am–12:50pm Wednesday, 04/17/2019
Event
Location: Americas Hall 2
Topic Table discussions are a great way to informally network with people in similar industries or interested in the same topics. Read more.

1:00pm

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1:00pm–1:40pm Wednesday, 04/17/2019
40-minute session
AI Business Summit, Case Studies
Location: Sutton North/Center
Secondary topics:  AI case studies, Text, Language, and Speech
Joanna Chavez (Booz Allen Hamilton)
Cognitive Solutions, the application of intelligent technology and services to empower the user to draw insights from data using natural human interaction, is a disruptive force in the US Federal market and is changing the way citizens engage with data. Read more.
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1:00pm–1:40pm Wednesday, 04/17/2019
40-minute session
Case Studies, Machine Learning
Location: Sutton South
Secondary topics:  AI case studies, Media, Marketing, Advertising, Platforms and infrastructure, Text, Language, and Speech
Twitter is a company with massive amounts of data. Thus, it is no wonder that the company applies machine learning in myriad of ways. In this session, we are going to describe, in depth, one of those use cases: Timeline Ranking. From modeling to infrastructure our goal is to share some of the optimizations that this team have made in order to have models that are both expressive and efficient. Read more.
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1:00pm–1:40pm Wednesday, 04/17/2019
40-minute session
Machine Learning, Models and Methods
Location: Regent Parlor
Secondary topics:  Data and Data Networks, Models and Methods, Reinforcement Learning
Danny Lange (Unity Technologies)
Join this session to learn how to create artificially intelligent agents that act in the physical world (through sense perception and some mechanism to take physical actions, such as driving a car). Understand how observing emergent behaviors of multiple AI agents in a simulated virtual environment can lead to the most optimal designs and real-world practices. Read more.
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1:00pm–1:40pm Wednesday, 04/17/2019
40-minute session
AI Business Summit, Executive Briefing/Best Practices
Location: Mercury Ballroom
Secondary topics:  AI in the Enterprise
Larry Carin (Infinia ML)
Duke Professor Larry Carin, one of the world’s most published machine learning researchers, discusses the state of the art in machine learning, and how it translates to business impact. Carin will present examples of how modern machine learning is transforming business in several sectors, including healthcare delivery, security, and back-office business processing. Read more.
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1:00pm–1:40pm Wednesday, 04/17/2019
40-minute session
Implementing AI
Location: Mercury Rotunda
Secondary topics:  Deep Learning and Machine Learning tools
Catherine Ordun (Booz Allen Hamilton)
While building machine learning models for most large projects, data scientists typically design dozens of models using different combinations of hyperparameters, data configurations, and training settings. This session describes how to build your own machine learning model tracking leaderboard in Keras. Read more.
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1:00pm–1:40pm Wednesday, 04/17/2019
40-minute session
Machine Learning, Models and Methods
Location: Grand Ballroom West
Secondary topics:  Automation in machine learning and AI, Deep Learning and Machine Learning tools, Models and Methods
Ameet Talwalkar (Carnegie Mellon University and Determined AI)
Neural architecture search (NAS) is a promising research direction that has the potential to replace expert-designed networks with learned, task-specific architectures. In this talk, we present work which aims to help ground the empirical results in this field. In this talk we propose new NAS baselines. Read more.
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1:00pm–1:40pm Wednesday, 04/17/2019
40-minute session
Implementing AI
Location: Rendezvous
Secondary topics:  Edge computing and Hardware, Platforms and infrastructure, Reinforcement Learning, Retail and e-commerce, Temporal data and time-series
Jian Chang (Alibaba Group), Sanjian Chen (Alibaba Group)
Time series database (TSDB) is of great use for data management in IoT, finance, etc. Performance is always a major optimization point for TSDB. Recently, we introduced neural networks and reinforcement learning to perform mode selection for compression algorithm. Experimental results show one can improve average compression ratio by 20%-120%, comparing with other well-known compression format. Read more.
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1:00pm–1:40pm Wednesday, 04/17/2019
40-minute session
Sponsored
Location: Clinton
Zongjie Diao (Cisco)
In this session, we will discuss the key challenges companies facing in ML deployment and exam the root causes. More importantly, we will discuss the solutions to help demystify ML development in enterprises. Read more.
1:00pm–1:40pm Wednesday, 04/17/2019
Location: Beekman
TBC

1:50pm

Add to your personal schedule
1:50pm–2:30pm Wednesday, 04/17/2019
40-minute session
AI Business Summit, Executive Briefing/Best Practices
Location: Sutton North/Center
Secondary topics:  AI case studies, Text, Language, and Speech
David Talby (Pacific AI)
New AI solutions in question answering, chatbots, structured data extraction, text generation, and inference all require deep understanding of the nuances of human language. David Talby shares challenges, risks, and best practices for building NLU-based systems, drawing on examples and case studies from products and services built by Fortune 500 companies and startups over the past seven years. Read more.
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1:50pm–2:30pm Wednesday, 04/17/2019
40-minute session
Case Studies, Machine Learning
Location: Sutton South
Secondary topics:  AI in the Enterprise, Text, Language, and Speech
Maryam Jahanshahi (TapRecruit)
Word embeddings such as word2vec have revolutionized language modelling. In this talk I will discuss exponential family embeddings, which apply probabilistic embedding models to other data types. I describe how we implemented a dynamic embedding model to understand how tech skill-sets have changed over 3 years. The key takeaway is that these models can enrich analysis of specialized datasets. Read more.
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1:50pm–2:30pm Wednesday, 04/17/2019
40-minute session
Implementing AI
Location: Regent Parlor
Secondary topics:  Edge computing and Hardware
Simon Crosby (SWIM.AI)
Organizations are increasingly overwhelmed with large amounts of streaming data. Today’s approach to processing it is based on legacy big-data centric architectures, “the cloud”, and the assumption that organizations have access to data scientists to make sense of it all. Read more.
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1:50pm–2:30pm Wednesday, 04/17/2019
40-minute session
AI Business Summit, Executive Briefing/Best Practices
Location: Mercury Ballroom
Secondary topics:  Ethics, Privacy, and Security, Financial Services, Health and Medicine, Reliability and Safety
Anand Rao (PwC)
Broader AI adoption and gaining trust from customers requires AI systems to be fair, interpretable, robust, and safe. This talk synthesizes the current research in FAT (Fairness, Accountability, Transparency) into a step-by-step methodology to address these issues. Case studies from financial services and healthcare are used to illustrate the approach. Read more.
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1:50pm–2:30pm Wednesday, 04/17/2019
40-minute session
Implementing AI
Location: Mercury Rotunda
Secondary topics:  Platforms and infrastructure, Text, Language, and Speech
Jeremy Lewi (Google), Hamel Husain (GitHub)
In this talk, we will use the example of a search engine for code using natural language to illustrate how Kubeflow and Kubernetes can be used to build and deploy ML products. Read more.
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1:50pm–2:30pm Wednesday, 04/17/2019
40-minute session
Models and Methods
Location: Grand Ballroom West
Secondary topics:  Models and Methods, Platforms and infrastructure
vinay rao (RocketML Inc), Santi Adavani (Mr)
Growing data sizes are causing Training times to increase 5x the Moore's law. While Hardware innovations are helping, new software architectures for distributed system are needed for AI industry to solve critical problems. RocketML results show that we can build logistic regression models on KDD12 data set with ~150 Million samples on 8 Intel Xeon node cluster in < 1 minute. Read more.
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1:50pm–2:30pm Wednesday, 04/17/2019
40-minute session
Implementing AI
Location: Rendezvous
Secondary topics:  Media, Marketing, Advertising, Platforms and infrastructure
YU DONG (Facebook Inc)
An overview of why, what & how of building a production-scale ML platform based on ongoing ML research trends and industry adoptions. Read more.
1:50pm–2:30pm Wednesday, 04/17/2019
Location: Clinton
TBC
Add to your personal schedule
1:50pm–2:30pm Wednesday, 04/17/2019
40-minute session
Sponsored
Location: Beekman
Katie Taylor (SAS)
The sum of AI’s parts is greater than the whole. The importance of chaining together AI technologies is to build smart end-to-end processes. Achieving the best analytics edge often requires a mixture of technologies. This talk will explore use cases within key industries uncovering how AI success is being achieved through a layered technology stack. Read more.

2:40pm

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2:40pm–3:20pm Wednesday, 04/17/2019
40-minute session
AI Business Summit, Case Studies
Location: Sutton North/Center
Secondary topics:  AI case studies, Financial Services
Andrew Chin (AllianceBernstein), Celia Chen
Overview of data science applications within the asset management industry Specific use cases using ML to derive better investment insights and improve client engagement Read more.
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2:40pm–3:20pm Wednesday, 04/17/2019
40-minute session
Case Studies, Machine Learning
Location: Sutton South
Secondary topics:  Models and Methods, Text, Language, and Speech
Vijay Agneeswaran (Publicis Sapient), Abhishek Kumar (Publicis Sapient)
We illustrate how capsule networks can be industrialized: 1. Overview of capsule networks and how they help in handling spatial relationships between objects in an image. We also learn about how they can be applied to text analytics. 2. We show an implementation of recurrent capsule networks. 3. We also benchmark the RCN with capsule networks with dynamic routing on text analytics tasks. Read more.
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2:40pm–3:20pm Wednesday, 04/17/2019
40-minute session
Interacting with AI
Location: Regent Parlor
Secondary topics:  Computer Vision, Deep Learning and Machine Learning tools
Matt Zeiler (Clarifai)
At the core of today's problems with image classification and deep learning lies one fundamental truth: most AI systems operate by choosing the path of least resistance – not the path of highest long-term quality. Matt Zeiler, founder and CEO of Clarifai, will discuss the company's approach to Closing the Loop on AI and employing techniques to counter the AI quality regression phenomenon. Read more.
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2:40pm–3:20pm Wednesday, 04/17/2019
40-minute session
AI Business Summit, Executive Briefing/Best Practices
Location: Mercury Ballroom
Secondary topics:  AI in the Enterprise, Ethics, Privacy, and Security
Anna Gressel (Debevoise & Plimpton LLP), Jim Pastore (Debevoise & Plimpton LLP), Anwesa Paul (American Express)
This is a crash course on the emerging legal and regulatory frameworks governing AI, including GDPR and California Consumer Privacy Act. It will also explore key lawsuits challenging AI in U.S. courts - and unpack implications for companies going forward. By understanding these trends, companies can more effectively mitigate legal and regulatory risks and position their AI products for success. Read more.
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2:40pm–3:20pm Wednesday, 04/17/2019
40-minute session
Implementing AI
Location: Mercury Rotunda
Secondary topics:  AI in the Enterprise, Models and Methods, Text, Language, and Speech
Sumeet Vij (Booz Allen Hamilton), Matt Speck (Booz Allen Hamilton)
The session describes the innovative application of Deep Learning to power Cognitive Conversational Agents. By leveraging Transfer Learning and deep pre-trained models for NLP, we show how Chatbots can overcome limitations of limited training datasets. In addition, we will demonstrate how Machine Learning can advances Robotic Process Automation (RPA) from “robotic” to “cognitive” automation Read more.
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2:40pm–3:20pm Wednesday, 04/17/2019
Machine Learning, Models and Methods
Location: Grand Ballroom West
Secondary topics:  Automation in machine learning and AI, Models and Methods, Reinforcement Learning, Reliability and Safety
Sanjay Krishnan (University of Chicago)
I use my work over the last few years on building and deploying an RL-based relational query optimizer, a core component of almost every database system, as an exemplary application that highlights some of the under-appreciated challenges in Deep RL practice. Read more.
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2:40pm–3:20pm Wednesday, 04/17/2019
40-minute session
Implementing AI
Location: Rendezvous
Secondary topics:  Deep Learning and Machine Learning tools, Media, Marketing, Advertising, Platforms and infrastructure
Yi Zhuang (Twitter), Nicholas Leonard (Twitter)
Twitter is a 4000+ employee company with many ML use cases. Historically, there are many different ways to productionize ML at Twitter. In this session, we describe the setup and benefits of a unified ML platform for production, and how Twitter Cortex team brings together users of various ML tools. Read more.
2:40pm–3:20pm Wednesday, 04/17/2019
Location: Clinton
TBC
2:40pm–3:20pm Wednesday, 04/17/2019
Location: Beekman
TBC

3:20pm

3:20pm–4:05pm Wednesday, 04/17/2019
Location: TBD
Afternoon Break (Sponsored by Dataiku) (45m)

4:05pm

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4:05pm–4:45pm Wednesday, 04/17/2019
40-minute session
AI Business Summit, Case Studies
Location: Sutton North/Center
Secondary topics:  AI case studies, AI in the Enterprise, Financial Services, Text, Language, and Speech
Kyle Hoback (WorkFusion), Mikhail Abramchik (WorkFusion)
Using AI to combat financial crime is more than strong fraud detection models monitoring transactions. Banks follow significant Anti-Money Laundering (AML) and Know-Your-Customer (KYC) laws and procedures, wrought with growth chained to cost and requiring auditable automation. This session will walk-through a series of case studies that utilize AI-powered RPA that address AML and KYC. Read more.
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4:05pm–4:45pm Wednesday, 04/17/2019
40-minute session
Location: Sutton South
Tom Sabo (SAS)
Sources of international human trafficking data contain a wealth of textual information that is laborious to assess using manual methods. To improve international trafficking response, we demonstrate text-based machine learning, rule-based text extraction to generate training data for modeling efforts, and interactive visualization. Read more.
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4:05pm–4:45pm Wednesday, 04/17/2019
40-minute session
Interacting with AI
Location: Regent Parlor
Secondary topics:  Media, Marketing, Advertising, Models and Methods, Reinforcement Learning
Kevin He (DEEPMOTION, INC.)
Digital character interaction is hard to fake–whether it’s between two characters, between users and characters, or between a character and its environment. Nevertheless, interaction is central to building immersive XR experiences, robotic simulation, and user-driven entertainment. Kevin He will discuss using physical simulation and deep learning to create interactive character technology. Read more.
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4:05pm–4:45pm Wednesday, 04/17/2019
40-minute session
AI Business Summit, Executive Briefing/Best Practices
Location: Mercury Ballroom
Secondary topics:  AI in the Enterprise, Automation in machine learning and AI, Platforms and infrastructure
Sarah Aerni (Salesforce Einstein)
How does Salesforce manage to make data science an agile partner to over 100,000 customers? We will share the nuts and bolts of the platform and our agile process. From our open-source autoML library (TransmogrifAI) and experimentation to deployment and monitoring, we will cover how the tools make it possible for our data scientist to rapidly iterate and adopt a truly agile methodology. Read more.
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4:05pm–4:45pm Wednesday, 04/17/2019
40-minute session
Implementing AI
Location: Mercury Rotunda
Secondary topics:  AI case studies, Deep Learning and Machine Learning tools, Reliability and Safety
Pradip Bose (IBM T. J. Watson Research Center), Augusto Vega (IBM T. J. Watson Research Center), Nandhini Chandramoorthy (IBM T. J. Watson Research Center)
We will describe the fundamentals of a next generation AI research project. It is focused on creating future "self-aware" AI systems that have built-in autonomic detection and mitigation facilities to avoid faulty or undesirable behavior in the field: in particular, cognitive bias and inaccurate decisions that are perceived as being unethical. Software-hardware system architectures are discussed. Read more.
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4:05pm–4:45pm Wednesday, 04/17/2019
40-minute session
Machine Learning, Models and Methods
Location: Grand Ballroom West
Secondary topics:  Computer Vision, Deep Learning and Machine Learning tools
Bichen Wu (UC Berkeley)
For years we have been designing neural networks manually, but such design flow is extremely inefficient and designed networks are sub-optimal. To address this, we introduce an automated framework for neural network design and optimization. This approach generates superior neural network design and greatly reduces the need for manual efforts. Read more.
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4:05pm–4:45pm Wednesday, 04/17/2019
Location: Rendezvous
In this session we present the new Intel® Deep Learning Boost (Intel® DL Boost) technology featuring integer vector neural network instructions targeting future Intel(R) Xeon(R) Scalable processors. We will also go through the 8-bit integer convolution implementation made in Intel(R) MKL-DNN library to demonstrate how this new instruction is used in optimized code. Read more.
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4:05pm–4:45pm Wednesday, 04/17/2019
40-minute session
Sponsored
Location: Clinton
Ben Vigoda (Gamalon)
How does customer experience/digital marketing know what customers are saying to our human chat, bot chat, survey, or social? Why are they not satisfied or not moving to the next action? The first step is to deeply analyze customer conversations. A new generation of AI technology makes this possible, extracting the ideas contained in text to summarize, organize, and display for analysis. Read more.
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4:05pm–4:45pm Wednesday, 04/17/2019
40-minute session
Sponsored
Location: Beekman
Suresh Vadakath (DataRobot)
Many companies want to influence the future by adjusting factors that they control. We’re going to cover practical ways to extend machine learning models via simulations and point out common pitfalls to avoid. We’ll then discuss a few applications in marketing, pricing, and operations to illustrate how this approach works in the real world. Read more.

4:55pm

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4:55pm–5:35pm Wednesday, 04/17/2019
40-minute session
AI Business Summit, Case Studies
Location: Sutton North/Center
Secondary topics:  AI case studies, Automation in machine learning and AI, Financial Services, Platforms and infrastructure
Scott Clark (SigOpt), Matt Greenwood (Two Sigma Investments)
Increasingly, companies building modeling platforms to empower their researchers to efficiently scale the development and productionalization of their models. During this talk, we use a case study from a leading algorithmic trading firm to draw general best practices for building these types of platforms in any industry. Read more.
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4:55pm–5:35pm Wednesday, 04/17/2019
40-minute session
Location: Sutton South
Jack Dashwood (Intel), Anna Bethke (Intel AI)
The hardware, software, and algorithms that automatically tag our images or recommend the next book to read, can also improve medical diagnosis and protect our natural resources. This talk will describe a variety of technical projects at Intel, how they have enabled social good organizations, and provide guidance on creating or engaging in these types of projects. Read more.
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4:55pm–5:35pm Wednesday, 04/17/2019
40-minute session
Interacting with AI
Location: Regent Parlor
Secondary topics:  Deep Learning and Machine Learning tools, Reinforcement Learning
Paris Buttfield-Addison (Secret Lab Pty. Ltd.), Mars Geldard (University of Tasmania), Tim Nugent (lonely.coffee)
Learn how to use Unity to train, explore, and manipulate intelligent agents that learn. Train a quadruped to walk. Then train it to explore, fetch, and manipulate the world. Games are great places to explore AI. They’re wonderful contained problem spaces. Learn how to use them, even though you’re not a game developer. Read more.
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4:55pm–5:35pm Wednesday, 04/17/2019
40-minute session
AI Business Summit, Executive Briefing/Best Practices
Location: Mercury Ballroom
Secondary topics:  Financial Services
Angelo Calvello (Rosetta Analytics)
While there is no doubt that AI could be used to create better investment outcomes, successfully adopting AI requires asset managers to radically transform their existing business models and investment processes. Faced with such possible disruption, leadership will instead choose to maintain the status quo and introduce diluted forms of AI. Read more.
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4:55pm–5:35pm Wednesday, 04/17/2019
40-minute session
Implementing AI
Location: Mercury Rotunda
Secondary topics:  Deep Learning and Machine Learning tools, Ethics, Privacy, and Security
Andrew Zaldivar (Google)
The development of AI is creating new opportunities to improve the lives of all people. It is also raising new questions about ways to build fairness, interpretability and other moral and ethical values into these systems. Using Jupyter and TensorFlow, this presentation will share hands-on examples that highlight current work and recommended practices towards the responsible development of AI. Read more.
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4:55pm–5:35pm Wednesday, 04/17/2019
40-minute session
Models and Methods
Location: Grand Ballroom West
Secondary topics:  Ethics, Privacy, and Security, Models and Methods
Yishay Carmiel (IntelligentWire)
In recent years, we have seen tremendous improvements in artificial intelligence. The major breakthroughs are due to the advances of neural-based models. However, the more popular these algorithms and techniques get, the more serious the consequences of data and user privacy. These issues will drastically impact the future of AI research. Read more.
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4:55pm–5:35pm Wednesday, 04/17/2019
40-minute session
Implementing AI
Location: Rendezvous
Secondary topics:  Computer Vision, Edge computing and Hardware, Platforms and infrastructure
Ted Way (Microsoft Corporation), Aishani Bhalla (Microsoft)
Deep neural networks (DNNs) have enabled breakthroughs in AI. Serving DNNs at scale has been challenging: fast and cheap? Won’t be accurate. Accurate and fast? Won’t be cheap. You’ll learn how Python and TensorFlow can be used to easily train and deploy computer vision models on Intel FPGAs with Azure Machine Learning and Project Brainwave, getting performance such as ResNet 50 in under 2 ms. Read more.
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4:55pm–5:35pm Wednesday, 04/17/2019
40-minute session
Sponsored
Location: Clinton
Jack Norris (MapR Technologies)
This session will delve into the three building blocks and the one massive mistake to avoid for any organization looking to leverage AI. Read more.
4:55pm–5:35pm Wednesday, 04/17/2019
Location: Beekman
TBC

5:35pm

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5:35pm–6:35pm Wednesday, 04/17/2019
Event
Location: Expo Hall
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 Wednesday. Read more.

7:00pm

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7:00pm–9:00pm Wednesday, 04/17/2019
Event
Location: Bryant Park Grill
Don't miss AI at Night, happening on Wednesday after the Attendee Reception. Read more.

Thursday, 04/18/2019

8:00am

8:00am–9:00am Thursday, 04/18/2019
Location: Various Locations
Morning Coffee (Sponsored by Gamalon) (1h)

8:15am

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8:15am–8:45am Thursday, 04/18/2019
Event
Location: 3rd Floor West Promenade
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.

9:00am

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9:00am–9:05am Thursday, 04/18/2019
Keynote
Location: Grand Ballroom West
Ben Lorica (O'Reilly Media), Roger Chen (Computable)
Opening Remarks Read more.

9:05am

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9:05am–9:20am Thursday, 04/18/2019
Keynote
Location: Grand Ballroom West
Sean Gourley (Primer)
Keynote by Sean Gourley Read more.

9:20am

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9:20am–9:30am Thursday, 04/18/2019
Keynote
Location: Grand Ballroom West
Deep Learning is hard enough without worrying about setting up and managing complex infrastructure. Nauta is an open source Deep Learning ‘easy button’ allowing teams of data scientists to run complex distributed models on shared hardware resources. Read more.

9:30am

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9:30am–9:45am Thursday, 04/18/2019
Keynote
Location: Grand Ballroom West
Secondary topics:  Platforms and infrastructure
Kim Hazelwood (Facebook)
Applied Machine Learning at Facebook Read more.

9:45am

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9:45am–9:55am Thursday, 04/18/2019
Keynote
Location: Grand Ballroom West
Ruchir Puri (IBM)
Learn about the next revolution in automating AI - which strives to deploy AI itself to automate the task building, deploying and managing AI tasks, accelerating the journey of enterprises to AI. Read more.

9:55am

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9:55am–10:10am Thursday, 04/18/2019
Keynote
Location: Grand Ballroom West
Chris Re (Stanford University and Apple)
Keynote by Christopher Ré Read more.

10:10am

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10:10am–10:15am Thursday, 04/18/2019
Keynote
Location: Grand Ballroom West
Rajendra Prasad (Accenture)
After crossing the first AI implementation milestone, leaders often ask “What’s next?” Based on experience implementing AI-led automation for more than 100 clients, Accenture has developed an easy-to-use methodology for scaling and sustaining reliable AI solutions. Rajendra Prasad (RP) explains how leaders and change makers in large enterprises can make AI adoption successful. Read more.

10:15am

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10:15am–10:30am Thursday, 04/18/2019
Keynote
Location: Grand Ballroom West
Olga Troyanskaya (Princeton University)
Keynote by Olga Troyanskaya Read more.

10:30am

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10:30am–10:35am Thursday, 04/18/2019
Keynote
Location: Grand Ballroom West
Closing Remarks Read more.

10:35am

10:35am–11:05am Thursday, 04/18/2019
Location: TBD
Morning Break (Sponsored by Dell EMC) (30m)

11:05am

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11:05am–11:45am Thursday, 04/18/2019
40-minute session
Location: Sutton North/Center
Adam Cheyer (Samsung)
For decades, the relationship between developer and computer was simple: the human told the machine what to do. We will provide you with a freely downloadable development environment so that you can give this a try yourself, and start monetizing your content and services through a new channel that will be backed by more than a billion devices in just a few years. Read more.
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11:05am–11:45am Thursday, 04/18/2019
40-minute session
Case Studies, Machine Learning
Location: Sutton South
Secondary topics:  AI case studies, Financial Services, Models and Methods
vishal hawa (Vanguard)
While Deep Learning has shown significant promise towards model performance, it can quickly become untenable particularly when data size is short. RNNs can quickly memorize and over-fit . The presentation explains how a combination of RNNs and Bayesian Network (PGM) can improvise sequence-modeling behavior of RNNs. Read more.
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11:05am–11:45am Thursday, 04/18/2019
40-minute session
Location: Regent Parlor
Mohamed Fawzy (Facebook)
TBD Read more.
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11:05am–11:45am Thursday, 04/18/2019
40-minute session
AI Business Summit, Executive Briefing/Best Practices
Location: Mercury Ballroom
Secondary topics:  Data and Data Networks
Thomas G Marlow (Black Hills IP)
Three elements will control the AI market - Technology, Data and IP Rights. Leveraging rich patent data, we will uncover the companies with the top patent holdings across the world in groundbreaking research and implementation technologies, gaining insights into the sources and owners of AI technology as well as the hurdles and opportunities that lay in front of those entering the field today. Read more.
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11:05am–11:45am Thursday, 04/18/2019
40-minute session
Implementing AI
Location: Mercury Rotunda
Secondary topics:  AI in the Enterprise, Automation in machine learning and AI, Platforms and infrastructure
Diego Oppenheimer (Algorithmia)
In this talk, Diego Oppenheimer, CEO of Algorithmia, will draw upon his work with thousands of developers across hundreds of organizations and discuss the tools and processes every business will need to automate model deployment and management so they can optimize model performance, control compute costs, maintain governance, and keep data scientists doing data science. Read more.
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11:05am–11:45am Thursday, 04/18/2019
40-minute session
Location: Grand Ballroom West
Adam Straw (Intel), Adam Procter (Intel), Robert Earhart (Intel)
The rapid growth of deep learning in demanding, large-scale, real-world applications has led to a rapid increase in demand for high-performance training and inference solutions. In this talk, we provide a comprehensive overview of the nGraph deep learning compiler from Intel. Read more.
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11:05am–11:45am Thursday, 04/18/2019
40-minute session
Interacting with AI
Location: Rendezvous
Secondary topics:  Interfaces and UX
Following the launch of CTRL-labs’ developer kit, CTRL-kit (neural interface device), Patrick Kaifosh will paint a picture of a world with neural interfaces and how this technology will change our lives. This presentation will outline a future where we will be looking up at the world instead of down at our phones and will feature a live demo. Read more.
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11:05am–11:45am Thursday, 04/18/2019
40-minute session
Sponsored
Location: Clinton
Rajendra Prasad (Accenture)
After crossing the first AI implementation milestone, leaders often ask “What’s next?” Based on AI engineering and deploying AI, Accenture has developed an easy-to-use methodology for achieving predictable, high-speed production releases and sustaining reliable AI solutions. A must-see session for leaders and change makers in large enterprises who want to make AI adoption successful. Read more.
Add to your personal schedule
11:05am–11:45am Thursday, 04/18/2019
40-minute session
Location: Beekman
Ruchir Puri (IBM)
Learn about the next revolution in automating AI - which strives to deploy AI itself to automate the task building, deploying and managing AI tasks, accelerating the journey of enterprises to AI. Read more.

11:50am

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11:50am–12:50pm Thursday, 04/18/2019
Event
Location: Americas Hall 2
Topic Table discussions are a great way to informally network with people in similar industries or interested in the same topics. Read more.

1:00pm

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1:00pm–1:40pm Thursday, 04/18/2019
40-minute session
Law and Ethics
Location: Sutton North/Center
Secondary topics:  Ethics, Privacy, and Security
Joanna Bryson (University of Bath)
Although not a universally held goal, maintaining human accountability for AI is necessary for society’s long-term stability. Fortunately, the legal and technological problems of maintaining control are fairly well understood and amenable to engineering. The next problem is establishing the social and political will for assigning and maintaining accountability for intelligent artifacts. Read more.
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1:00pm–1:40pm Thursday, 04/18/2019
40-minute session
Case Studies, Machine Learning
Location: Sutton South
Yulia Zvyagelskaya (Dow Jones)
Companies have a strong need for complying with anti-money laundering, anti-bribery, corruption and economic sanctions regulation in mitigating third party risk. Dow Jones Risk & Compliance deliver research tools and services for vetting and investigation to evaluate these risks with more confidence. The presentation highlights how DJ uses deep learning and NLP for efficient compliance solutions. Read more.
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1:00pm–1:40pm Thursday, 04/18/2019
40-minute session
Machine Learning, Models and Methods
Location: Regent Parlor
Secondary topics:  Models and Methods, Text, Language, and Speech
Chang Ming-Wei (Google)
We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers. Unlike recent language representation models, BERT is designed to pre-train deep bidirectional representations by jointly conditioning on both left and right context in all layers. Read more.
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1:00pm–1:40pm Thursday, 04/18/2019
40-minute session
AI Business Summit, Executive Briefing/Best Practices
Location: Mercury Ballroom
Secondary topics:  AI in the Enterprise
Vinay Seth Mohta (Manifold)
A significant hype bubble is building up around AI that has convinced many executives that, if they’re not already tech-savvy, they might not be ready for AI’s “transformative power.” However, the reality is that AI is just another tool that can help your business, and you’re probably not that far behind. This talk will explain how to evaluate it as you would any other strategic investment. Read more.
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1:00pm–1:40pm Thursday, 04/18/2019
40-minute session
Implementing AI
Location: Mercury Rotunda
Secondary topics:  Deep Learning and Machine Learning tools, Platforms and infrastructure
Evan Sparks (Determined AI)
Building deep learning applications is hard. Building them repeatably is harder. Maintaining high computational performance during a repeatable deep learning development process is borderline impossible. We describe the key pitfalls associated with fast, repeatable, model development, and what practitioners can do to avoid these and maintain a super-charged AI development workflow. Read more.
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1:00pm–1:40pm Thursday, 04/18/2019
40-minute session
Machine Learning, Models and Methods
Location: Grand Ballroom West
Secondary topics:  AI case studies, Automation in machine learning and AI, Deep Learning and Machine Learning tools
Francesca Lazzeri (Microsoft), Wee Hyong Tok (Microsoft)
Automated machine learning (AutoML) enables both data scientists and domain experts (with limited machine learning training) to be productive and efficient. AutoML is seen as a fundamental shift in which organizations can approach making machine learning. In this talk, you'll learn how to use auto ML to automate selection of machine learning models and automate tuning of hyper-parameters. Read more.
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1:00pm–1:40pm Thursday, 04/18/2019
40-minute session
Interacting with AI
Location: Rendezvous
Secondary topics:  Ethics, Privacy, and Security, Interfaces and UX
Jeff Thompson (Stevens Institute of Technology)
What is it like to be a mobile phone or to attach a wind sensor to a neural network? This talk outlines several recent creative projects that push the tools of AI in new directions. Part technical discussion and part case study for embedding artists in technical institutions, this talk explores the ways that artists and scientists can collaborate to expand the ways that AI can be used. Read more.
1:00pm–1:40pm Thursday, 04/18/2019
Location: Clinton
TBC
Add to your personal schedule
1:00pm–1:40pm Thursday, 04/18/2019
40-minute session
Location: Beekman
Nick Curcuru (Mastercard)
There are many different decisions one must make when choosing the right solutions and infrastructure. Using real-world discussions from the considerations employed, to the use cases defined, the solutions implemented, and the results achieved, this session with explore different decisions, the associated considerations and best practices Mastercard exercised to build and deploy a successful AI. Read more.

1:50pm

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1:50pm–2:30pm Thursday, 04/18/2019
40-minute session
AI Business Summit, Case Studies
Location: Sutton North/Center
Secondary topics:  AI case studies, Computer Vision, Health and Medicine
Eric Oermann (Mount Sinai Health System), Katie Link (Allen Institute for Brain Science)
There is a significant interest in applying deep learning based solutions to problems in medicine and healthcare. This talk will focus on identifying actionable medical problems, and then recasting them as tractable deep learning problems and the techniques to solve them. Read more.
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1:50pm–2:30pm Thursday, 04/18/2019
40-minute session
Case Studies, Machine Learning
Location: Sutton South
Till Bergmann (Salesforce), Leah McGuire (Salesforce)
A problem in predictive modeling data is label leakage. At Enterprise companies such as Salesforce, this problem takes on monstrous proportions as the data is populated by diverse business processes, making it hard to distinguish cause from effect. We will describe how we tackled this problem at Salesforce, where we need to churn out thousands of customer-specific models for any given use case. Read more.
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1:50pm–2:30pm Thursday, 04/18/2019
40-minute session
Interacting with AI
Location: Regent Parlor
Secondary topics:  Ethics, Privacy, and Security, Interfaces and UX
Forough Poursabzi-Sangdeh (Microsoft Research NYC)
In this talk, I will argue that to understand interpretability, we need to bring humans in the loop and run human-subject experiments. I approach the problem of interpretability from an interdisciplinary perspective which builds on decades of research in psychology, cognitive science, and social science to understand human behavior and trust. Read more.
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1:50pm–2:30pm Thursday, 04/18/2019
40-minute session
AI Business Summit, Executive Briefing/Best Practices
Location: Mercury Ballroom
Jana Eggers (Nara Logics)
Explainability and transparency are discussed and debated as both required and unachievable goals for AI. This talk will focus on helping teams structure discussions about levels of explainability possible and needed for both user trust and regulatory requirements. Read more.
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1:50pm–2:30pm Thursday, 04/18/2019
40-minute session
Location: Mercury Rotunda
Morten Dahl (Dropout Labs)
Machine learning applied to health care or otherwise sensitive data may be blocked if privacy is not adequately addressed. We review modern cryptographic techniques such as homomorphic encryption and multi-party computation. Finally, we show how data scientists can get started with privacy-preserving techniques today, without needing to master the cryptography. Read more.
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1:50pm–2:30pm Thursday, 04/18/2019
40-minute session
Machine Learning, Models and Methods
Location: Grand Ballroom West
Secondary topics:  Financial Services, Models and Methods, Temporal data and time-series
Arun Kejariwal (Independent), Ira Cohen (Anodot)
In this talk we shall shares a novel two-step approach for building more reliable prediction models by integrating anomalies in them. Further, we shall walk the audience through how to marry correlation analysis with anomaly detection, discusses how the topics are intertwined, and details the challenges you may encounter based on production data. Read more.
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1:50pm–2:30pm Thursday, 04/18/2019
40-minute session
Location: Rendezvous
Adam Marek (Intel Corporation)
During this session the audience will learn more about the motivation, architecture and, functionality offered by Nauta. We will also discuss how it differs from other OSS offerings in the Deep Learning space. Read more.
1:50pm–2:30pm Thursday, 04/18/2019
Location: Clinton
TBC
1:50pm–2:30pm Thursday, 04/18/2019
Location: Beekman
TBC

2:40pm

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2:40pm–3:20pm Thursday, 04/18/2019
40-minute session
AI Business Summit, Case Studies
Location: Sutton North/Center
Secondary topics:  AI case studies, Computer Vision, Health and Medicine
Enhao Gong (Subtle Medical), Greg Zaharchuk (Stanford University)
Clinical radiology is faced with several clinical issues: 1) improvement in imaging efficiency, 2) reduction of risks, 3) high imaging quality. Subtle Medical provides Deep Learning/AI solution, powered and accelerated by industry solution such as OpenVINO, to address these problems by enabling faster MRI, faster PET and low dose, providing real clinical and financial benefit to hospitals. Read more.
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2:40pm–3:20pm Thursday, 04/18/2019
40-minute session
Case Studies, Machine Learning
Location: Sutton South
Secondary topics:  AI case studies, Computer Vision, Ethics, Privacy, and Security, Models and Methods, Reinforcement Learning
Alina Matyukhina (Canadian Institute for Cybersecurity)
Machine learning models are often susceptible to adversarial deception of their input at test time, which is leading to a poorer performance. In this session we will investigate the feasibility of deception in source code attribution techniques in real world environment. This session will present attack scenarios on users identity in open-source projects and discuss possible protection methods. Read more.
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2:40pm–3:20pm Thursday, 04/18/2019
40-minute session
Interacting with AI
Location: Regent Parlor
Secondary topics:  Computer Vision, Health and Medicine, Models and Methods, Reliability and Safety
Behrooz Hashemian (Massachusetts General Hospital)
Artificial Intelligence has shown great potentials to revolutionize clinical medicine and health care delivery. However, incorporating these algorithms into clinical workflows faces a big challenge: convincing clinicians and regulators to trust a “black box” solution. In this talk, I present how we are making deep neural networks interpretable to provide evidences for clinical decisions. Read more.
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2:40pm–3:20pm Thursday, 04/18/2019
Location: Mercury Ballroom
In this talk, we explore a process for repeatedly creating effective AI products, from idea through process to specific design considerations, and how architecture and algorithmic choices can support or hinder this process. Read more.
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2:40pm–3:20pm Thursday, 04/18/2019
40-minute session
Implementing AI
Location: Mercury Rotunda
Secondary topics:  Deep Learning and Machine Learning tools
Magnus Hyttsten (Google)
Session description: This session covers how to use TensorFlow effectively in a distributed manner using best-practices. We will cover using TensorFlow's new DistributionStrategy to get easy high-performance training with Keras models (and custom models) on multi-GPU setups as well as multi-node training on clusters with accelerators. Read more.
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2:40pm–3:20pm Thursday, 04/18/2019
40-minute session
Machine Learning, Models and Methods
Location: Grand Ballroom West
Secondary topics:  Computer Vision, Models and Methods, Text, Language, and Speech
Anoop Katti (SAP)
We address understanding documents with 2D layout using machine learning. Examples of such documents are invoices, resumes, presentations etc. (in contrast to plain text documents like tweets, articles and reviews). We explore the shortcomings of the existing techniques and discuss a processing pipeline for 2D documents – the chargrid - pioneered by data scientists at SAP Read more.
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2:40pm–3:20pm Thursday, 04/18/2019
40-minute session
Implementing AI
Location: Rendezvous
Secondary topics:  Computer Vision, Data and Data Networks, Ethics, Privacy, and Security, Reliability and Safety
Ryan Mukherjee (JHU/APL), Neil Fendley (JHU/APL)
While deep learning has led to many advancements in computer vision, most research has focused on ground-based imagery. To address this, we released an ImageNet for satellite imagery called functional Map of the World (fMoW). We present our work building the dataset, running a public prize challenge, and investigating how one might attack or defend these deep learning models. Read more.
2:40pm–3:20pm Thursday, 04/18/2019
Location: Clinton
TBC
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2:40pm–3:20pm Thursday, 04/18/2019
40-minute session
Location: Beekman
Nanda Vijaydev (BlueData (recently acquired by HPE))
How do you accelerate innovation and deliver faster time-to-value for your AI initiative, while ensuring enterprise-grade security and high performance? How do you provide easy access to the tools and data your data science teams need for large-scale distributed ML / DL with greater agility for rapid prototyping and iteration? Read more.

3:20pm

3:20pm–4:05pm Thursday, 04/18/2019
Location: TBD
Afternoon Break (Sponsored by Accenture) (45m)

4:05pm

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4:05pm–4:45pm Thursday, 04/18/2019
40-minute session
AI Business Summit, Case Studies
Location: Sutton North/Center
Secondary topics:  AI case studies, Data and Data Networks, Text, Language, and Speech
A case study that details lights-out automation and how DCL uses AI to transform massive volumes of confidential disparate data into searchable and structured information. Considerations for architecting a solution that processes a continuous flow of 5M+ “pages” of complex work units. Read more.
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4:05pm–4:45pm Thursday, 04/18/2019
40-minute session
Case Studies, Machine Learning
Location: Sutton South
Secondary topics:  AI case studies, Financial Services, Text, Language, and Speech
Chakri Cherukuri (Bloomberg LP)
In this talk we will see how machine learning and deep learning techniques can be applied in the field of quantitative finance. We will look at a few use-cases in detail and see how machine learning techniques can supplement and sometimes even improve upon already existing statistical models. We will also look at novel visualizations to help us better understand and interpret these models. Read more.
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4:05pm–4:45pm Thursday, 04/18/2019
40-minute session
Implementing AI
Location: Regent Parlor
Secondary topics:  AI case studies, Financial Services, Temporal data and time-series
Aric Whitewood (WilmotML)
Our firm focuses on the application of AI to investment management. Topics covered in this presentation include the application of AI to the problem of asset selection, dealing with low signal-to-noise ratios in financial time series data, the development of real-time macroeconomic indicators from social media data, and the use of heterogeneous compute architectures, specifically GPUs and FPGAs. Read more.
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4:05pm–4:45pm Thursday, 04/18/2019
40-minute session
AI Business Summit, Executive Briefing/Best Practices
Location: Mercury Ballroom
Secondary topics:  AI in the Enterprise, Automation in machine learning and AI, Data and Data Networks
Paco Nathan (derwen.ai)
Data governance is an almost overwhelming topic. This talk surveys history, themes, plus a survey of tools, process, standards, etc. Mistakes imply data quality issues, lack of availability, and other risks that prevent leveraging data. OTOH, compliance issues aim to preventing risks of leveraging data inappropriately. Ultimately, risk management plays the "thin edge of the wedge" in enterprise. Read more.
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4:05pm–4:45pm Thursday, 04/18/2019
40-minute session
Interacting with AI
Location: Mercury Rotunda
Secondary topics:  Computer Vision, Data and Data Networks, Models and Methods
Humayun Irshad (Figure Eight)
In this talk, an active learning framework with crowd sourcing approach is introduced to solve a real-world problem in transportation and autonomous driving discipline, parking sign recognition, for which a large amount of unlabeled data is available. It generates an accurate model in a cost-effective and fast way to solve the parking sign recognition problem in spite of the unevenness of the data Read more.
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4:05pm–4:45pm Thursday, 04/18/2019
40-minute session
Machine Learning, Models and Methods
Location: Grand Ballroom West
Secondary topics:  Media, Marketing, Advertising, Models and Methods, Retail and e-commerce
Marcel Kurovski (inovex GmbH)
Recommender Systems support decision making with personalized suggestions. They have proven useful in e-commerce, entertainment, or social networks. However, sparse data and linear models are a burden. Application of Deep Learning sets new boundaries and constitutes remarkable results. This talk shows its application on vehicle recommendations at Germany's biggest online vehicle market. Read more.
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4:05pm–4:45pm Thursday, 04/18/2019
40-minute session
Implementing AI
Location: Rendezvous
Secondary topics:  Automation in machine learning and AI, Media, Marketing, Advertising, Models and Methods, Text, Language, and Speech
Jaewon Lee (LINE Corp.), Sihyeung Han (NAVER & LINE Corp)
"Until when are you going to cluster queries by yourself to manage large data corpus?" "Until when are you going to tune model hyper parameters by yourself?" I would like to introduce how to implement self-trained dialogue model by using AutoML in Chatbot within our Chatbot Builder Framework. Read more.
4:05pm–4:45pm Thursday, 04/18/2019
Location: Clinton
TBC
4:05pm–4:45pm Thursday, 04/18/2019
Location: Beekman
TBC

4:55pm

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4:55pm–5:35pm Thursday, 04/18/2019
40-minute session
Location: Sutton North/Center
Sheldon Fernandez (DarwinAI)
In this talk, DarwinAI CEO Sheldon Fernandez, who possesses degrees in both engineering and theology, will separate fact from fad in ensuring that artificial systems behave ethically. Read more.
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4:55pm–5:35pm Thursday, 04/18/2019
40-minute session
Case Studies, Machine Learning
Location: Sutton South
Secondary topics:  Models and Methods, Reliability and Safety, Temporal data and time-series
Mohammad Mavadati (Affectiva)
According to the CDC, up to 6,000 fatal crashes caused by drowsy drivers annually. Driver alertness monitoring systems will allow us to develop more reliable vehicles and safer roads. In this talk, Affectiva introduces state-of-the-art vision-based DNN techniques for drowsiness (intensity) annotations and modeling, and reveals some of the AI solutions for in-car drowsiness predictions. Read more.
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4:55pm–5:35pm Thursday, 04/18/2019
40-minute session
Interacting with AI
Location: Regent Parlor
Secondary topics:  AI case studies, Models and Methods
Andrew Caosun (Horace Mann School)
We propose a framework that unifies Hidden Markov Model and deep learn algorithm (RNN) with modeling components that consider long-term memory and semantics of music (LSTM and Convolution). It takes user original creation as input, modifies the raw scores, and generates musically appropriate melodies. Read more.
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4:55pm–5:35pm Thursday, 04/18/2019
40-minute session
AI Business Summit, Executive Briefing/Best Practices
Location: Mercury Ballroom
Secondary topics:  Edge computing and Hardware
Jennifer Fernick (NCC Group )
Quantum computers will enable us to efficiently compute things never thought possible - how will this impact artificial intelligence? In this talk, attendees will learn to filter signal from noise in discussions surrounding quantum machine learning by exploring how quantum computers work, what types of AI problems they may be good at, and which industries and use cases will (and will not) benefit. Read more.
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4:55pm–5:35pm Thursday, 04/18/2019
40-minute session
Implementing AI
Location: Mercury Rotunda
Secondary topics:  Data and Data Networks
Dmitry Petrov (Iterative AI), Ivan Shcheklein (Iterative AI)
Many companies are using machine learning today, ML teams size is growing and complexity of ML project is increasing. Establishing a well define and manageable process become a central issue in this environment. ML models and data set versioning is an essential first step in the direction of establishing a good process. We will discuss open source tools and practices for ML models versioning. Read more.
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4:55pm–5:35pm Thursday, 04/18/2019
40-minute session
Machine Learning, Models and Methods
Location: Grand Ballroom West
Secondary topics:  AI in the Enterprise, Models and Methods
Maja Vukovic (IBM)
Existing AI driven automation in enterprises employ ML, NLP and chatbots. There is additional opportunity for AI Planning to drive reasoning about action trajectories to help build automation. I will demo application of AI planning for migration of legacy infrastructure to Cloud, based on real world examples and data, and discusses challenges in adopting AI planning solutions in the enterprise. Read more.
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4:55pm–5:35pm Thursday, 04/18/2019
40-minute session
Models and Methods
Location: Rendezvous
Secondary topics:  Media, Marketing, Advertising, Models and Methods, Reinforcement Learning
Matthew Reyes (Independent Researcher and Consultant)
This talk considers optimizing preference towards a product on a social network. The model for consumer decision-making is based on the notion of random utility. The contributions of the model are stochastic decisions that will be learned from data, and the inclusion of marketing under the control of individual companies. These contributions enable a reinforcement learning based approach. Read more.
4:55pm–5:35pm Thursday, 04/18/2019
Location: Clinton
TBC
4:55pm–5:35pm Thursday, 04/18/2019
Location: Beekman
TBC