State of AI Report 2020
Published by Nathan Benaich and Ian Hogarth on 1 October 2020.
Download 2020 ReportIntroduction
It’s been a curious year for AI — with important breakthroughs in NLP and drug discovery tempered by AI’s to-date modest contributions in the fight against Covid-19.
Produced with my friend Ian Hogarth during the pandemic, this year’s State of AI Report is a remedy to fears of a new AI winter, and we hope a much needed reminder of the extent of innovation and progress carrying on despite the present circumstances.
However, our report also demonstrates just how much of this innovation is enabled by massive computing infrastructure that is increasingly in the hands of big tech companies.
We need to think carefully about what this means for the future of AI innovation, but also acknowledge that we are seeing more and more AI-first startups implementing the core ideas that emerge from this research.
Elsewhere in the report, look out for the wealth of biotech progress. I’m particularly excited about the impact that AI is having in the life sciences as biology and medicine become large data domains ideal for AI applications. So much has changed since I finished my PhD in cancer research in 2013…we’re now on the brink of being able to decode a lot more about our health and revolutionise how we treat disease.
We write this report to compile the most interesting things we’ve seen, with the aim of provoking an informed conversation about the state of AI, and unpacking what developments in the field mean for our future. We’d love your view on the report and your take on our predictions. Please do share any observations you might have!
New to the 2020 edition are invited content contributions from two dozen well-known and up-and-coming companies and research groups. We’re incredibly grateful for their contributions that dive deeper into key themes of 2020: NLP, biology, and autonomous systems. Thank you to our reviewers for volunteering their time and valuable insights that keep us honest.
What are the key takeaways, you ask?
There are many, but here are four key findings:
Thanks!
Contributors
With thanks to: Babylon, Berkshire Grey, CloudNC, ComplyAdvantage, Disperse, Faculty, Graphcore, Hugging Face, InVivo AI, LabGenius, Lyft Level 5, Niantic, Onfido, ONI, OpenMined, PolyAI, PostEra, Recursion, Secondmind, Signal, Tessian, tinyclues, Tractable, and ZOE.
Reviewers
Jack Clark, Jeff Ding, Chip Huyen, Rebecca KaganKagan, Andrej Karpathy, Moritz Mueller-Freitag, Torsten Reil, Charlotte Stix, and Nu (Claire) Wang.