Keynote: Building an Operating System for AI

Yochay Ettun, CEO & Co-Founder at Intel® Tiber™ AI Studio
Leah Kolben, CTO & Co-Founder at Intel® Tiber™ AI Studio

Adding Machine Learning to Search

Samay Kapadia, Data Science Lead - Search at DeliveryHero

The 4th dimension: The Impact of Time on Machine Learning Systems

Leonardo Neves, Lead Research Scientist at Snap Inc

Should Data Influence ML Platform and System Development?

Abon Chaudhuri, Engineering Manager, Core ML Team at Robinhood

Visual Search in Deployment

Morgan Cundiff, Data Scientist at ShopRunner

The Good and Bad in Kubernetes for AI

Itay Ariel, Backend Team Lead at Intel® Tiber™ AI Studio

Accelerating FinTech Workloads with RiskFuel and Habana Gaudi

Sree Ganesan, AI Software Product Management at Habana Labs
Maxime Bergeron, Director of Research & Development at Riskfuel

Retriever Augmented GPT

Arvind Neelakantan, Research Lead at OpenAI

How to Build an NLP Pipeline with BERT in PyTorch

Vasilis Vagias, AI Architect at Intel® Tiber™ AI Studio

Making Sense of ML Metrics

Michael McCourt, Head of Engineering at SigOpt, an Intel company

Landing the First Use Cases of Data Science in a Traditional Non-Tech Enterprise

Rushen Patel, Head of Enterprise Data Science at Marks & Spencer

Kubernetes Without Containers – Running AI/HPC Workloads on Bare Metal

Dmitry Kartsev, Cloud Native Dev Lead at Intel® Tiber™ AI Studio

Balancing Product and Customer Signals to Improve E-Commerce Search Results

Tyan Hynes, Senior Technology Product Manager at Zulily

Building Attention Recommendation at Wish

Chandler Phelps, Data Science Manager at Wish

Content and Commerce AI – Building Enterprise AI solutions for Adobe customers

Deepak Pai, Senior Manager of Machine Learning at Adobe

Natural Language Processing at Scale

Andrei Lopatenko, VP of Engineering at Zillow

Lidar Enhances Insights

Aniket Patange, Head of AI and Innovation at Hitachi

Anomalies: Simple Detection and Alerting Techniques

Margaret Campbell, Senior Data Scientist at Snowflake

Path to ML from the CTO’s Perspective

Jeff Sternberg, Technical Director, Applied AI at Google Cloud Office of the CTO, Google
James Tromans, Technical Director, Applied AI at Google Cloud Office of the CTO at Google

Strategies for running a successful AI/ML pilot with St Jude Children’s Research Hospital

Dr. Franz Parkins, Computational Scientist at St Jude
Chris Bogan, HPC/AI Leader at Mark III Systems

Minding the Machines: Building and Leading Data Science and Analytics Teams

Jeremy Adamson, Head of Advanced Revenue Analytics at WestJet

Transforming Data Science Productivity with Spark

Philip Hummel, Distinguished Member Technical Staff at Dell Technologies

Deploying a Deep RL Algorithm on Low-memory and Low-compute Devices

Benjamin Fuhrer, AI Engineer at NVIDIA
Doron Haritan, AI Engineer at NVIDIA

Efficiency of NLP deployed in production

Moshe Wasserblat, Senior PE, DL and NLP Research Manager at Intel Corporation

Recommendations at CNN

Tim Obert, Data Scientist at CNN
Ailish Byrne, Engineer at CNN

Automated Image Labeling for Medical Imaging AI

Patrick Bangert, VP of AI at Samsung

Building a Semantic Enterprise-Scale Knowledge Graph for Pharmaceutical Brands

Srayanta Mukherjee, Director Data Science at Novartis

ML & AI in Drug Development: The Hidden Part of the Iceberg

Paul Agapow, Director Oncology R&D at AstraZeneca

Training Data for CV/DL

Nikita Manovich, Deep Learning Manager, Internet of Things Group at Intel Corporation