The "Generate an SVG of a pelican riding a bicycle" AI benchmark, from Simon Willison
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🚨 🚨 As of yesterday afternoon, British users will no longer be able to use end-to-end encryption on their Cloud backups because Apple was forced to disable it. This is extremely dangerous because unauthorized gov personnel or hackers could manage to access the backdoor that Apple will provide to the British authorities, putting the entire population at risk. It's incredible that this happens just after the Chinese hack of the backdoors that US authorities had forced telcos to insert. As discussed in my Survival Tech (https://survival-tech.org): the remedy (the freedom risk of exposing the entire population to data leaks) is worse than the disease (the initial security problem which justifies backdoors). It's more and more urgent to recognize end-to-end encryption as a key basic human right, and as a natural and necessary counterbalance to the overwhelming power that Big Tech, governments, and malicious actors obtain from accessing our data. https://www.bbc.com/news/articles/cgj54eq4vejo
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"How Machines Learned to Discover Drugs" by D.Khullar on The New Yorker TL;DR: - Antibiotics aren’t very profitable for pharma companies: they are expensive to develop, and customers use them for 1-2 weeks - Bacteria quickly learn to resist antibiotics. By 2050, 10m people per year will die from antibiotic-resistant infections - We need new generations of antibiotics for those "evolved" bacteria, which are even less profitable (they affect fewer people) - AI-based drug testing research can help by inventing molecules that pass Phase I (testing on healthy individuals) but so far haven’t passed Phase II (testing on patients) better than human-made molecules - AI & medicine perform best when the dataset is richer (than in the Antibiotics space). See the recent success of DeepMind’s AlphaFold in designing proteins, a completely different field - Long story short: let's moderate the enthusiasm and keep on studying. https://www.newyorker.com/magazine/2024/09/09/how-machines-learned-to-discover-drugs
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