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Cake day: July 7th, 2023

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  • For people lacking context, Boeing split off and sold their division that became Spriti Aerosystems. The theory at the time was that Boeing’s core competency wasn’t building airplanes, it was managing relationships with other vendors. In particular, the actual plane manufacturing part of the company was undesirable due to perceived poor “Return on Net Assets.” The theory they pitched to shareholders was they should sell off non obviously profitable divisions so they reduced asset liability while keeping the same or better profits.

    That was their explanation, of course it was a terrible idea.







  • CLAs can be abusive, but not necessarily. Apache Foundation contributors need to sign CLAs, which essentially codify in contract form the terms of the Apache 2.0 license. It’s a precaution, in case some jurisdiction doesn’t uphold the passive licensing scheme used otherwise. There’s also a relicensing clause, but that’s restricted to keeping in spirit, they can’t close the source.




  • If you want vertical tabs with the ability to organize them in trees I suggest the Sideberry extension. It legitimately makes me nervous that the functionality would ever go away, it improves my productivity so much.

    You can bookmark trees, collapse them, search them, load/unload them manually, I could go on. It makes it easy to organize dozens or hundreds of tabs. I have some trees for emails, news, forums, projects, etc. When I’m done just fold it up: the top tab bar can hide tabs that aren’t in the active tree you’re using, so you can still navigate the tabs normally.








  • So this is probably another example of Google using too blunt of instruments for AI. LLMs are very suggestible and leading questions can severely bias responses. Most people using them without knowing a lot about the field will ask “bad” questions. So it likely has instructions to avoid “which is better” and instead provide pros and cons for the user to consider themselves.

    Edit: I don’t mean to excuse, just explain. If anything, the implication is that Google rushed it out after attempting to slap bandaids on serious problems. OpenAI and Anthropic, for example, have talked about how alignment training and human adjustment takes a majority of the development time. Since Google is in a self described emergency mode, cutting that process short seems a likely explanation.




  • Compression is actually a mathematical field that’s fairly well explored, and this isn’t compression. There are theoretical limits on how much you can compress data, so the data is always somewhere, either in the dictionary or the input. Trained models like these are gigantic, so even if it was perfect recall the ratio still wouldn’t be good. Lossy “compression” is another issue entirely, more of an engineering problem of determining how much data you can throw out while making acceptable compromises.