Sep 9–12, 2019

Sponsored Sessions

Please Note: Keynotes are not available to Expo Plus pass holders.

9:25am9:35am Wednesday, September 11, 2019
Location: Hall 2
Average rating: ****.
(4.20, 5 ratings)
Dinesh Nirmal examines how, with a unified, prescriptive information architecture, organizations can successfully unlock the value of their data for AI as well as trust and control the business impact and risks of AI while coexisting in a multicloud world. Read more.
9:50am9:55am Wednesday, September 11, 2019
Location: Hall 2
Triveni Gandhi (Dataiku)
Average rating: ***..
(3.25, 4 ratings)
With the adoption of AI in the enterprise accelerating, its impacts—both positive and negative—are rapidly increasing. Triveni Gandhi explores why the builders of these new AI capabilities all bear some moral responsibility for ensuring that their products create maximum benefit and minimal harm. Read more.
10:10am10:15am Wednesday, September 11, 2019
Location: Hall 2
Daniel Russakoff (Voxeleron)
Average rating: ***..
(3.50, 4 ratings)
The emphasis in AI is on replicating human performance. Examples abound: ImageNet, self-driving cars, etc. It’s the same in medicine. Daniel Russakoff explains how Voxeleron LLC is working on what’s next—AI algorithms that do things that humans can’t, such as the prediction of age-related macular degeneration (AMD) progression, critical to successful treatment of this leading cause of vision loss. Read more.
11:05am11:45am Wednesday, September 11, 2019
Location: 230 B
Bharath Kadaba (Intuit)
Average rating: ****.
(4.40, 5 ratings)
To unleash the full potential of AI, Intuit envisions a future that melds the best capabilities of machines and humans to deliver personalized customer experiences, all on one secure platform. Bharath Kadaba examines how Intuit combines rules-based knowledge engineering with data-driven machine learning and natural language processing to build the human-expert-in-the-loop AI systems of the future. Read more.
11:05am11:45am Wednesday, September 11, 2019
Location: 231
Manish Bhide (IBM Watson), Rohan Vaidyanathan (IBM Watson)
Average rating: ***..
(3.40, 5 ratings)
With the potential to transform businesses, AI has become a strategic imperative for most enterprises. A lot of investment is toward machine learning and deep learning models to support business applications. However, as Manish Bhide and Rohan Vaidyanathan explain, these models bring about risks and uncertainties that are difficult to manage. Read more.
11:05am11:45am Wednesday, September 11, 2019
Location: Santa Clara Room (Hilton)
Kurt Muehmel (Dataiku)
We're rapidly closing in on a future where large companies across different sectors will be enriching every business process and decision with AI and gaining a sustained competitive edge as a result. Join Kurt Muehmel on a forward-looking exploration of companies that are already well on their way toward this target. He details Dataiku's vision of the journey ahead. Read more.
11:55am12:35pm Wednesday, September 11, 2019
Location: 231
Ramesh Radhakrishnan (Dell Technologies), John Zedlewski (NVIDIA)
Average rating: *****
(5.00, 1 rating)
Data scientists and machine learning engineers need the flexibility to work in multiple environments without wasting precious time configuring hardware and software and modifying code. Ramesh Radhakrishnan and John Zedlewski walk you through deploying a simple set of technologies for executing end-to-end pipelines entirely on GPUs. Read more.
11:55am12:35pm Wednesday, September 11, 2019
Location: Santa Clara Room (Hilton)
Sunil Mallya (Amazon Web Services)
Average rating: ****.
(4.67, 3 ratings)
Sunil Mallya walks you through how to build complex ML-enabled products using reinforcement learning (RL), explores hardware design challenges and trade-offs, and details real-life examples of how any developer can up level their RL skills through autonomous driving. Read more.
1:45pm2:25pm Wednesday, September 11, 2019
Location: 231
Sina Bari (iMerit)
Sina Bari explores how to overcome obstacles to creating high-quality ground truth data for ML applications. Read more.
1:45pm2:25pm Wednesday, September 11, 2019
Location: Santa Clara Room (Hilton)
Sunil Mallya (Amazon Web Services)
Average rating: *****
(5.00, 1 rating)
Sunil Mallya explores how to use data from equipment to build, train, and deploy predictive models. You'll dive deep into the architecture, deployment guide, and development resources for using the turbofan degradation simulation dataset to train the model to recognize potential equipment failures. Read more.
2:35pm3:15pm Wednesday, September 11, 2019
Location: 231
Pankaj Goyal (Hewlett Packard Enterprise), Nanda Vijaydev (Hewlett Packard Enterprise)
Average rating: *****
(5.00, 1 rating)
Join Pankaj Goyal and Nanda Vijaydev to learn how HPE put AI into action and helps enterprises unlock the value of their data with a proven, practical approach to AI. Read more.
2:35pm3:15pm Wednesday, September 11, 2019
Location: Santa Clara Room (Hilton)
Moon soo Lee (Zepl | Apache Zeppelin), Louis Huard (Zepl)
Average rating: *****
(5.00, 3 ratings)
A key step in the data science workflow is rapid model development; however, gaps still exist. Teams are moving from siloed to sharing and reusing models, code, and results. There are also in challenges deploying models into production using tools like Kubeflow and TensorFlow. Moon Soo Lee and Louis Huard examine how leading companies solve these issues, and how you can improve your workflow. Read more.
4:00pm4:40pm Wednesday, September 11, 2019
Location: 231
Margaret Laffan (TalentSeer | BoomingStar Ventures)
With the rapid advancement of AI technology and commercial breakthroughs, building a strong AI team becomes increasingly critical for business success in the high-tech era. Margaret Laffan helps tech and talent leaders to better understand the AI talent market and explores best practices for building, nurturing, and retaining the right team to accelerate their business growth. Read more.
4:00pm4:40pm Wednesday, September 11, 2019
Location: Santa Clara Room (Hilton)
Navdeep Gill (H2O.ai)
Average rating: *****
(5.00, 1 rating)
Navdeep Gill takes a deep dive into how to combine innovations from several subdisciplines of machine learning research to train understandable, fair, trustable, and accurate predictive modeling systems. Read more.
4:50pm5:30pm Wednesday, September 11, 2019
Location: 231
Labhesh Patel (Jumio)
Average rating: ****.
(4.00, 1 rating)
Labhesh Patel explores how deep learning informs computer vision through smarter data extraction, fraud detection, and risk scoring. Labhesh details what it takes to put AI in production and how a machine learning infrastructure needs to be fundamentally thought out to allow for better human-in-the-loop AI workflows. Read more.
9:20am9:30am Thursday, September 12, 2019
Location: Hall 2
Lei Pan (Nauto)
Average rating: ****.
(4.00, 3 ratings)
Lei Pan examines how Nauto uses Amazon SageMaker and other AWS services, including Amazon Simple Notification Service (SNS) and Amazon Simple Queue Service (SQS) to continually evolve smarter data for driver behavior. Read more.
11:05am11:45am Thursday, September 12, 2019
Location: Santa Clara Room (Hilton)
Carlos Escapa (Amazon Web Services)
Average rating: ****.
(4.75, 4 ratings)
Carlos Escapa takes a deep dive into how to identify use cases for ML, acquire cutting-edge best practices to frame problems in a way that key stakeholders and senior management can understand and support, and set the stage for delivering successful ML-based solutions for your business. Read more.
1:45pm2:25pm Thursday, September 12, 2019
Location: Santa Clara Room (Hilton)
Anand Rao (PwC)
Anand Rao provides an overview from the practitioner’s perspective on addressing ethics within businesses. Anand explores PwC’s responsible AI toolkit, which enables businesses to identify and contextualize relevant ethical AI principles and provides tools for evaluating interpretability of systems. You'll see example applications that illustrate model interpretability. Read more.
2:35pm3:15pm Thursday, September 12, 2019
Location: Santa Clara Room (Hilton)
Arno Candel (H2O.ai)
Driverless AI is H2O.ai’s latest flagship product for automatic machine learning for the enterprise. Arno Candel outlines Driverless AI, explores customer use cases, and performs a live demo with custom recipes to solve a specific machine learning problem. Read more.

Contact us

confreg@oreilly.com

For conference registration information and customer service

partners@oreilly.com

For more information on community discounts and trade opportunities with O’Reilly conferences

Become a sponsor

For information on exhibiting or sponsoring a conference

pr@oreilly.com

For media/analyst press inquires