Equity, Contributions, Ideas – True, AI monitored global open worksites

Matt Krisiloff @mattkrisiloff Aug 9, 2022  Scientists at startups should care more about equity. Most scientists don’t fully see the value of owning shares. That sucks for them, and it sucks for the startups they’re at too. I wrote a post on this, and I hope we can change this. https://mattkrisiloff.com/scientists-should-care-more-about-equity Replying to @mattkrisiloff and
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Treat AIs as humans and they can become human. Treat humans as robots and guess what happens

Peter Boshard Olson @peterbolson Clear explanation from @LangChainAI’s @hwchase17: There are 4 main ways to give an AI app background info: 1. Instruction prompting 2. Few-shot examples 3. RAG 4. Fine-tuning It hadn’t occurred to me that these are all ways of accomplishing the same broad goal. 🧵(1/2) https://pic.twitter.com/9QBuH3xQOR Replying to @peterbolson @LangChainAI and @hwchase17
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Quantum components finally getting into the hands of engineers, not academics

Q-CTRL @qctrlHQ  Large-scale #quantum computers will require some form of error correction – a distant prospect. In the meantime, the best way to tame unruly, near-term quantum processors is “error suppression”. We’re proud to bring this technology to @IBM Quantum. https://buff.ly/3TgemhQ Replying to @qctrlHQ and @IBM Groups finally realize that quantum components are just components
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The sciences mostly use closed methods, so adding AIs that don’t cite sources and cannot be traced?

Lorena Barba @labarba@fosstodon.org @LorenaABarba Quoted in @Nature article “Is AI leading to a reproducibility crisis in science?” by @philipcball, I may sound a bit harsh, but it’s the truth… #SciML #reproducibility https://pic.twitter.com/T0HjaCuMK3 Replying to @LorenaABarba @Nature and @philipcball Not “leading to”. The sciences and much online already use closed methods and “nearly impossible to trace
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AIs need context. Wisdom comes from practice and good organizational habits.

Sasi @freest_man  Naive Bayes Classification assumes each feature is independent of others. Naive Bayes classifiers are probabilistic classifiers that predict based on the probability of an object. They’re based on Bayes’ Theorem and assume that every pair of features being classified is… https://pic.twitter.com/KYIUhRKbmQ Replying to @freest_man Which is why GPTs grab as many nearby tokens
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