Perhaps the most interesting theme from the last month has been discussions of what can be done with NFTs and other Web3 technologies aside from selling links to bored apes. Chris Anderson points out that NFTs are a new kind of link that includes history, and that’s a fascinating idea. We’re also seeing a lot of debate around the metaverse; an increasing number of companies are lining up in opposition to Facebook/Meta’s vision.
AI
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The Algorithmic Justice League has proposed paying “bug bounties” for algorithmic harms, similar to the way security researchers are paid bounties for finding vulnerabilities in software.
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OpenAI has released a new version of GPT-3 that is less toxic–less prone to reproducing racist, sexual, or violent language, though it can still do so when asked. This is not the end of the story, but it’s a big step forward. The new model, InstructGPT, is also much smaller: 1.3 billion parameters, as opposed to 175 billion.
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How do humans learn to work with AI systems? When should a human co-worker accept an AI’s predictions? Researchers at MIT are working on training methods that help human experts to understand when an AI is, or is not, likely to be accurate.
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It’s no surprise that AI systems can also discriminate on the basis of age, in addition to race and gender. While bias in AI is much discussed, relatively little work goes into building unbiased ...
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