To reach a more brain-like behavior LLMs need to integrate your inputs into their model dynamically, essentially retraining real-time bas...
To reach a more brain-like behavior LLMs need to integrate your inputs into their model dynamically, essentially retraining real-time based on the most salient input. Human brains do this selectively all the time and it's part of our plasticity. Biologically humans do similar compression, so introducing a similar concept to an LLM also feels reasonable. Hardware isn't fast/cheap enough to do this on an ongoing basis, similar to how it's too expensive for our brains to do this while we're moving through the world. All we have now most of the time in LLMs is "working memory" we're missing a lot of the functionality that allows for episodic memory and selective plasticity. The more you read about how human brains work, the more you realize that we may have figured out a piece with LLMs, but it's certainly nothing approaching AGI. People insisting so are blowing smoke for investor hype or don't understand a big piece of the concepts involved.
Posted by micromacrofoot on May 26, 2026, 4:50 PM
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Raise real-world problems, find people facing the same issue, and discuss solutions.2,000 issues0 comments
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Yeah, the plan is far too expensive for what it provides.
NewCrashed demand after one of the big AI labs (probably Anthropic because they focus way too hard on expensive frontier models) become inso...
New/dev/random is much too expensive for this.
Yeah, this always bugged me.
A year ago, I had the opinion that it'd be too expensive for developers to support offline mode, peer to peer, or community servers after...
The weird thing about this product is that its biggest competitor is "an old ipad." I feel like most of their target customer base alread...
There's a talk from Travis Kalanick recently on a podcast about this.
>nobody ever bought German cars for their low prices, except the Beetle Huh?
To reach a more brain-like behavior LLMs need to integrate your inputs into their model dynamically, essentially retraining real-time bas...
To reach a more brain-like behavior LLMs need to integrate your inputs into their model dynamically, essentially retraining real-time based on the most salient input. Human brains do this selectively all the time and it's part of our plasticity. Biologically humans do similar compression, so introducing a similar concept to an LLM also feels reasonable. Hardware isn't fast/cheap enough to do this on an ongoing basis, similar to how it's too expensive for our brains to do this while we're moving through the world. All we have now most of the time in LLMs is "working memory" we're missing a lot of the functionality that allows for episodic memory and selective plasticity. The more you read about how human brains work, the more you realize that we may have figured out a piece with LLMs, but it's certainly nothing approaching AGI. People insisting so are blowing smoke for investor hype or don't understand a big piece of the concepts involved.
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