Jun 12, 2020
In this week’s COVID-related AI news, Andy and Dave discuss “SciFact” from the Allen Institute for AI, which built on neural network VeriSci and can link to supporting or refuting materials for claims about COVID-19. Berkeley Labs releases COVIDScholar, which uses natural language processing text-mining to search over 60,000 papers and draw insights and connections. Berekely Labs also announces plans to use machine learning to estimate COVID-19’s seasonal cycle. In non-COVID AI news, Google publishes a response to the European Commission’s white paper on AI, cautioning that their definition of AI is far too broad and risks stifling innovation. CSET maps where AI talent is produced in the U.S., where it gets concentrated, and where AI funding equity goes. In research, OpenAI releases GPT-3, a 175B parameter NLP model, and shows that massively scaling up the language model greatly improves task-agnostic few-shot performance. A report from the European Parliament’s Panel for the Future of Science and Technology shows the ethics initiatives of nations around the globe. A review paper in Science suggests that progress in AI has stalled (perhaps as much as 10 years) in some fields. Abbass, Scholz, and Reid publish Foundations of Trusted Autonomy, a collection of essays and reports on trustworthiness and autonomy. And in the video of the week, CSIS sponsored a conversation with (now retired) JAIC Director, Lt Gen Shanahan.
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