A full-day Open Source AI workshop
“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 the trust and reduce the risks.
In this workshop, we have a twofold 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.
We will have a series of talks each followed by a short Q&A.
A tentative 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)
- 10:00 — Using AWS Cloud for ML — Neil Mackin (Amazon)
- 10:30 — Intro to ML in the Google Cloud using Keras — Marc Cohen (Google)
- 11:00 — Machine Learning and Big Scientific Data — Jeyan Thiyagalingam (UKRI)
- 11:30 — Open source ML toolkit RAPIDS — Miguel Martinez (NVIDIA)
- 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
- 15:30 — Deep learning in weather and climate — Peter Düben (ECMWF)
- 16:00 — Deep Learning Atmospheric Features — Daniel Galea (University of Reading)
- 16:15 — Curating big and small data: possibilities for understanding buildings in use — Hiral Patel (University of Reading)
- 16:30 — Open source software for Deep Learning — Huizhi Liang (University of Reading)
- 17:00 — From Academic Research into Open Source Products — Andy Hind (Oracle)
- 17:30 — Networking coffee
- 18:30 — Adjourn
Registration is necessary for our planning, please register as soon as possible if you want to attend the lunch. It is possible to register for the sessions morning and afternoon independently.
Deadline for registration with lunch is March 20th.
The workshop will take place in Room 185 (1st floor), Polly Vacher, Computer Science Department, University of Reading.
That is Building number 38 (in D4) on the University of Reading map right next to the “Pepper Lane” entrance.