Andy and Dave discuss the latest in AI news and research, including:
0:57: The Allen Institute for AI and others come together to create a publicly available “COVID-19 Challenges and Directions” search engine, building off of the corpus of COVID-related research.
5:06: Researchers with the University of Warwick perform a systematic review of test accuracy for the use of AI in image analysis of breast cancer screening and find most (34 or 36) AI systems were less accurate than a single radiologist, and all were less accurate than a consensus of two or more radiologists (among other concerning findings).
10:19: A US judge rejects an appeal for the AI system DABUS to own a patent, noting that US federal law requires an “individual” to be an owner, and the legal definition of an “individual” is a natural person.
17:01: The US Patent and Trademark Office uses machine learning to analyze the history of AI in patents.
19:42: BCS publishes Priorities for the National AI Strategy, as the UK seeks to set global AI standards.
20:42: In research, MIT, Northeastern, and U Penn explore the challenges of discerning emotion from a person’s facial movements (which largely relates to context), and highlight the reasons why facial recognition algorithms will struggle with this task.
28:02: GoogleAI uses diffusion models to generate high fidelity images; the approach slowly adds noise to corrupt the training data, and then using a neural network to reverse that corruption.
35:07: Springer-Verlag makes AI for a Better Future, by Bernd Carsten Stahl, available for open access.
36:19: Thomas Smith, co-founder of Gado Images, chats with GPT-3 about the COVID-19 pandemic and finds that it provides some interesting responses to his questions.
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