On the origins of #LLMs 120 Paper: https://
arxiv.org/abs/2307.09793
AI
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Origins of Large Language Models Research Paper Analysis
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FTC Chief Khan Defends Big Tech Antitrust Lawsuits After Microsoft Ruling
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F.T.C.’s Lina Khan Faces Fresh Questions After Microsoft Ruling: Lina Khan has said a fear of defeat should not deter the agency from suing big tech companies. But after Microsoft won a ruling this week, her critics say that… #Technology #Tech #FutureTech https://
nytimes.com/2023/07/11/tec
hnology/lina-khan-ftc-strategy.html?utm_source=dlvr.it&utm_medium=twitter
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Exploitation Mode: The Illusion of Progress Through Scaling
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Going into exploitation mode (scaling up what works) can give you the illusion of fast progress when you're looking at the wrong metrics. Like "solving" air travel by forever scaling up a hydrogen zeppelin. It may seem like you can cover ever greater distances, but you're still
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Deep Learning Limitations Unchanged Since 2017
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Re-reading an article I wrote in 2017, and I'm finding I could have written it yesterday. It's fascinating how the limitations of deep learning have stayed the same since. Same problems, same failure modes, no progress.
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HashiCorp License Change Through Realpolitik Lens
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I just used the word "realpolitik" in a blog post and it felt so good to revisit my undergraduate and graduate studies in international relations. (Yes, of course it's about the Hashicorp license change. )
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Criticism of LLM-Generated History Timeline for Autonomize Inc
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Check out this history timeline about Autonomize, Inc > the kind of bullshit these LLMs spew! #fail https://
historytimelines.co/timeline/auton
omize-inc
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AI’s Role in Medical Research: Protein Folding and Data Quality
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I think the case for "AI" helping with medical research might come from the work on protein folding–crucially a supervised machine learning project with extremely high quality data behind it–but I've never even seen the case re climate change expanded.
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Media bias: forced positivity narratives despite documented AI harms
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It's part and parcel of that annoying trope of having to pay lip-service to the supposed up-sides of "AI" even in reporting about the actual (documented, really happening) harms & risks of further harm. >>
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AI Marketing Talking Points: Disease Cures and Climate Solutions
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Anyone noticed that when folks get even a little specific about the supposed benefits of "AI" the call outs are often "curing disease" (sometimes specifically cancer and/or Alzheimer's) & "addressing climate change"? I'm hearing it enough to wonder where the talking pts come from
