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🎟️ Lineup+RSVP! 5th Research and Applied AI Summit

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Hey! We're organising the Research and Applied AI Summit in London on 28 June 2019. I'd like to share
 

nathan.ai newsletter

April 30 · Issue #32 · View online
A market intelligence newsletter covering AI in the technology industry, research lab and venture capital market.

Hey! We’re organising the Research and Applied AI Summit in London on 28 June 2019. I’d like to share our final speaker lineup with you as well as a preview of the topics we’ll cover. For our 5th annual event, we’re proud to bring you a strong group of entrepreneurs and researchers who have:
  • Built impactful AI-driven enterprise, consumer and life science startups
  • Pioneered widely-used methods, models and open source projects for ML, as well as the next generation of privacy-preserving tools
  • Invented novel hardware that drives AI progress.
On our side, we’ll be launching the State of AI Report 2019 (last year’s here) and sharing updates on Air Street Capital and the projects we’ve supported through our non-profit RAAIS Foundation.
100% of the event’s proceeds go towards funding open source AI research, tools and education for the common good. If you’re interested in getting involved, please drop me a line here.
👉 Register your interest here before May 7th 👈 We’ll be hosting 250 attendees from technology startups, large companies and universities all over the world.
Thanks to Google Cloud for Startups and Cooley LLP for your continued support in growing the RAAIS community.

📛 RAAIS 2019 Speakers
🔬 AI meets life science
Life sciences and healthcare are now in the limelight for technologists, in part because AI technologies are well suited to make a positive impact to key workflows. I have previously detailed 6 impactful applications of AI to the life sciences as a primer to the field. At RAAIS 2019, we’ll be running a series of talks on drug discovery and microbial engineering with Aaron Kimball (CTO, Zymergen), James Field (CEO, LabGenius), David Healey (Senior Data Scientist, Recursion) and Jonathan Bloom (Institute Scientist, Broad Institute). Together, these organisations are leading the charge globally.
📝 Research frontiers
Over the last 12 months, we’ve seen significant breakthroughs on natural language processing tasks such as machine translation, document generation and syntactic parsing. A key enabler of these results is in fact the Transformer model architecture that was co-authored by Ashish Vaswani (Senior Research Scientist, GoogleAI) and colleagues in 2017 at NIPS and has now been cited >1,500 times. Ashish will share his latest work on this thread.
At RAAIS, we believe in supporting both established and emerging research talent. For our research deep dive, we’re excited to be hosting Ashish in addition to two talented graduate students who we think will achieve great things in the future: Alex Ratner (Stanford), the lead of the Snorkel project, and Coline Devine (Berkeley).
💻 ML in large-scale production
Many of us in the community focus on bringing cutting-edge ML software from R&D into production. As such, we’ll feature two talks on this subject at RAAIS 2019. The first will be from Travis Addair (Senior Software Engineer, Uber) who works on Uber’s Michaelangelo ML platform and sits on the Technical Steering Committee for Horovod, Uber’s open source distributed deep learning framework. The second will be from Sarah Jarvis (Head of Data Science, PROWLER.io) who works with a global team of researchers and engineers in building the company’s multi-agent decision-making platform and deployments in logistics and finance.
👾 AI hardware
In 2017, we hosted Simon Knowles, co-founder and CTO of then 1-year old Graphcore. Since then, the AI hardware industry has flourished. This year, we’re pleased to host two renowned leaders in microprocessor and algorithm design: Carlo Luschi (Director of Research, Graphcore) and Kunle Olukotun (Professor of EECS, Stanford University; Chief Technologist, SambaNova Systems). Together, they will share the latest and greatest on hardware for machine intelligence from the vantage point of several decades of experience.
🔒 Privacy-preserving ML
One of the most pertinent topics in AI today is that of data privacy and model ownership. Significant value has accrued to large organisations as they understandably act as centers of gravity for talent and capital. However, for the long-term benefits of AI to be enjoyed by everyone, it is important to work on distributing tools, data and ownership broadly.
To explore this theme, we’re hosting one talk and one fireside chat amongst pioneers in federated learning, privacy policy and open source privacy-preserving ML. Brendan McMahan (Senior Staff Research Scientist, GoogleAI) will share his group’s latest work deploying federated learning into Google products. Andrew Trask (Leader, OpenMined; Research Scientist, DeepMind; PhD student, Oxford) will lead a fireside chat with Peter Eckersley (Director of Research, Partnership on AI) and Morten Dahl (Leader, TF-Encrypted; Research Scientist, DropOut Labs).

Thanks!
Nathan
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