10 posts found.

Date selected: February 2020

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Tech Talk 5

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CLOSING HEADLINER: AI – From Social Good to Ambient Intelligence

This session will highlight how AI can be helpful in addressing societal problems in a range of areas, and how Conversional AI can be transformative in removing barriers of modality and languages and impact how people can interact with technology and with each other.

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Tech Talk 2: Building an AI-powered IT infrastructure

Ramprakash will give a presentation focused around shipping features to enterprise users at scale, and managing them effectively to make sure the models are relevant in the longer run.

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WORKSHOP 4: Build, Train, Deploy and Monitor ML models with Amazon SageMaker

Traditional machine learning (ML) development is a complex, expensive, and iterative process made even more difficult because of the lack of integrated tools connecting the entire ML workflow. Users often need to stitch together tools and workflows, which is time-consuming and error-prone. Amazon SageMaker solves this challenge by providing all of the components used for […]

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WORKSHOP 1: Bringing cutting-edge AI technology where it counts the most – to people

In the personal health and wellness field, demand for counselling is quickly outpacing capacity. And when people struggling with mental and life challengers reach out for help, there is often no time for lengthy paperwork, complicated processes, and organizations centered on procedures and tradition as the norm. Learn how IBM, in working closely with counsellors […]

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HEADLINER: Towards understanding why deep learning works

Deep learning has shown incredible successes in the past few years, but there is still a lot of work remaining in order to understand why such over-parameterized models still generalize so well. In this presentation, Samy will cover recent work showing empirically interesting relations between learned internal representations and generalization. .

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HEADLINER: Learning to edit software with relational deep learning

We are collecting incredible amounts of data from professional software developers doing their jobs. Can we leverage this data to make developing software easier? Recent advances in deep learning—particularly around “relational deep learning” methods that can process irregular, graph-structured data—are giving us a powerful new toolbox to tackle the hard problems in this space. Danny […]

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