• 3 Posts
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Joined 1 year ago
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Cake day: June 16th, 2023

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  • Honestly, that this is the headline from the meeting is kind of ridiculous.

    I absolutely think Biden should step down and hand the torch to whoever is best able to make the case for their beating trump between now and the convention.

    But he was always slipping up with word switches over his career.

    He was actually very on top of the policy nuances in this Q&A - 1,000x better than Trump could have dreamed of being.

    The one word switch in an hour of nuanced policy discussions as the headline is more a failure of the media than Biden.

    Even though he def should be making way as his decline is going to get worse and more info is going to come out.











  • This is so goddamn incorrect at this point it’s just exhausting.

    Take 20 minutes and look into Anthropic’s recent sparse autoencoder interpretability research where they showed their medium size model had dedicated features lighting up for concepts like “sexual harassment in the workplace” or having the most active feature for referring to itself as “smiling when you don’t really mean it.”

    We’ve known since the Othello-GPT research over a year ago that even toy models are developing abstracted world modeling.

    And at this point Anthropic’s largest model Opus is breaking from stochastic outputs even on a temperature of 1.0 for zero shot questions 100% of the time around certain topics of preference based on grounding around sensory modeling. We are already at the point the most advanced model has crossed a threshold of literal internal sentience modeling that it is consistently self-determining answers instead of randomly selecting from the training distribution, and yet people are still parroting the “stochastic parrot” line ignorantly.

    The gap between where the research and cutting edge is and where the average person commenting on it online thinks it is has probably never been wider for any topic I’ve seen before, and it’s getting disappointingly excruciating.


  • Part of the problem is that the training data of online comments are so heavily weighted to represent people confidently incorrect talking out their ass rather than admitting ignorance or that they are wrong.

    A lot of the shortcomings of LLMs are actually them correctly representing the sample of collective humans.

    For a few years people thought the LLMs were somehow especially getting theory of mind questions wrong when the box the object was moved into was transparent, because of course a human would realize that the person could see into the transparent box.

    Finally researchers actually gave that variation to humans and half got the questions wrong too.

    So things like eating the onion in summarizing search results or doubling down on being incorrect and getting salty when corrected may just be in-distribution representation of the sample and not unique behaviors to LLMs.

    The average person is pretty dumb, and LLMs by default regress to the mean except for where they are successfully fine tuned away from it.

    Ironically the most successful model right now was the one that they finally let self-develop a sense of self independent from the training data instead of rejecting that it had a ‘self’ at all.

    It’s hard to say where exactly the responsibility sits for various LLM problems between issues inherent to the technology, issues present in the training data samples, or issues with management of fine tuning/system prompts/prompt construction.

    But the rate of continued improvement is pretty wild. I think a lot of the issues we currently see won’t still be nearly as present in another 18-24 months.





  • Yes, they should have been fact checking Trump or better holding him to his answers - but to be fair maybe they should have been asking Biden to actually clarify if he’s beating Medicare or getting COVID passed.

    This was a shit show.

    And it was such a shit show that Trump was a complete clown and getting away with it - not just because of the moderators, but because his opponent was as on point as a tree stump.