Workshop sessions that will be a deep dive into domain challenges, platforms, and approaches to tackle these issues. We will have enough time for discussions and networking between the peers.
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AGENDA
09:30 - Welcome coffee
09:45 - Welcome address - Julian Kunkel (University of Reading), Giuseppe Di Fatta (Head of Department, Department of Computer Science, University of Reading)
Session:
10:00 - Using AWS Cloud for ML - Neil Mackin (Amazon)
10:30 - Open source ML toolkit RAPIDS - Miguel Martinez (NVIDIA)
11:00 - Machine Learning and Big Scientific Data - Jeyan Thiyagalingam (UKRI)
11:30 - From Academic Research into Open Source Products - Andy Hind (Oracle)
12:00 - Lunch
Session: Applications and use cases for AI
13:00 - The importance of AI for high-performance I/O - Julian Kunkel (University of Reading)
13:30 - Machine Learning of I/O behavior - Eugen Betke (DKRZ)
14:00 - Integration of autonomous and human-driven cars - Ekene Ozioka (University of Reading)
14:30 - AI in Production: Challenges and how we made it work — Yingzhao Zhou (Oracle)
15:00 - Coffee
Session:
15:30 - Deep learning in weather and climate - Peter Düben (ECMWF)
16:00 - Deep learning atmospheric features - Daniel Galea (University of Reading)
16:30 - Open source software for Deep Learning - Hhuizhi Liang (University of Reading)
17:00 - From academic research into Open Source Products - Andy Hind (Oracle)
17:30 - Networking and refreshments
18:00 - Adjourn
More information: https://ossg.bcs.org/blog/event/open-source-ai-april-2019/
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SYNOPSIS
“Artificial intelligence will reach human levels by around 2029. Follow that out further to, say, 2045, we will have multiplied the intelligence, the human biological machine intelligence of our civilization a billion-fold.” — Ray Kurzweil
Artificial intelligence promises to aid and augment humans in all facets of our life. As the decisions made by an intelligent system may have wide implications, ethical questions must be resolved as the technology development progresses. Open RD&E can help to increase trust and reduce the risks.
In this workshop, we have a two-fold goal:
- bring together scientists, users, and vendors to talk about open source platforms and models for artificial intelligence.
- discuss socially relevant use cases and challenges and how they are addressed with AI.
The full-day workshop is structured into two sections, a morning and afternoon workshop session that will be a deep dive into domain challenges, platforms, and approaches to tackle these issues. We will have enough time for discussions and networking between the peers.
In the evening, we will follow the traditional BCS OSSG schedule that allows employees to participate: We will have a series of talks each followed by a short Q&A.
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For overseas delegates who wish to attend the event please note that BCS does not issue invitation letters.
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THIS EVENT IS BROUGHT TO YOU BY:
BCS Open Source SG
Visit https://ossg.bcs.org
