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AI with AI

Episode 4.18: D.E.R.Y.L.

In news, Andy and Dave discuss a machine learning algorithm from Synergies Intelligent System and Universität Hamburg that can identify people in a moving crowd who are mostly likely asymptomatic carriers of COVID-19. US lawmakers have introduced the Public Health Emergency Privacy Act, to boost privacy protections for COVID-19 technology such as tracing apps and vaccine scheduling apps. A team led by researchers from Oxford have introduced new reporting guidelines to bridge a gap in development to implementation when using clinical AI technologies, dubbed DECIDE-AI. Over 30 authors from a wide swath of organizations have proposed a “living benchmark” to evaluate progress in natural language generation, which they call GEM (Generation, Evaluation, and Metrics). And the combination we saw coming, research from Queen Mary University demonstrate a deep learning framework for detection of emotion using wireless signals. Researchers at the University of Virginia claim to detect physiological responses to racial bias with 76.1% accuracy, though it more focuses on exploring any link between mental associations of skin color. In research, Stanford researchers explore how learning and evolution occur in complex environments, and how they affect the diversity of morphological forms, with DERL (Deep Evolutionary Reinforcement Learning). Researchers from University of Illinois, Urbana-Champaign, introduce GANs for editing images via their latent space, which provides greater control over editing (e.g., editing a mouth without re-generating the entire face). And in the video of the week, a 12-minute video provides a short history on DARPA with highlights on many of its military robot programs.

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