I think what the parent post was saying is that there is a finite amount of useful mental function time in any one day, and once you’ve exhausted this any attempted learning will be pretty inefficient. Also some jobs will have a faster burn rate. Doing a workout is separate as it doesn’t draw on the mental energy pool.
I’m normally comparing frontier open/cheap models against frontier closed source. I use deepseek/glm regularly, they’re fine and you can get real work done with them but it’s super obvious when you switch back to opus or even sonnet. A 3B active param MoE model is not comparable.
You really need to take the benchmarks with a massive pinch of salt. I’ve been testing local LLMs since the original llama and there’s nothing I’ve tried that is in the same category as Opus.
I think this is true for projects beyond a certain complexity. I have 100% vibe coded projects with tens of thousands LOC, and haven't seen any real issues with fully automated maintenance. Will that approach work in every scenario, absolutely not, but the size and complexity of projects where it does is growing with each new model release.
That would imply that the biological physical substrate is necessary for conciousness, which I don't think you can say with any degree of certainty. It's not an assumption I would personally make. And while I'm speculating, my own view is that whatever the eventual subjective experience of what it's like to be an AI is, it will be nothing like the experience of what it's like to be a human, regardless of the fact we're training them to interact in human-like ways.
My point was the "stochastic parrot" label can be both true and irrelevant. LLMs are predicting the next token based on their training data, so at that level "stochastic parrot" is accurate. But it tells us nothing about the complexity of the system that is responsible for making the prediction. One might argue humans have evolved consciousness in order to allow world modelling that enables them to make better predictions.
The difference between a 1B LLM and Claude Opus matters, because we're talking about emergent phenomena. Is a 1B LLM conscious? I don't know, perhaps a tiny amount. Maybe Opus is more conscious. Is a jumping spider conscious? Perhaps a tiny amount.
I think (rather ironically) you're reacting to the version of my comment you have in your mind rather than what I actually wrote. My point was that "stochastic parrot" is reductionist and irrelevant as most people would agree that a real life parrot has some form of inner life, even if we don't really know what form it takes. For all we know an LLM has to build a complex world model in order to predict the next token.
Incidentally, when I pasted our exchange into Claude it managed to comprehend the nature of my argument. Perhaps its attention mechanism is more finely tuned.
The reason people are confused by LLMs is that they are stochastic parrots. They do an incredibly good job of emulating human behaviours and speech patterns as that's what they've been trained on. But like an actual parrot, it's impossible to say exactly how much conciousness they actually have. I certainly would argue that a parrot is concious, although likely less so than a human.
What we do know is that conciousness is not binary and that it emerged through evolution. That doesn't entirely rule out your magic tsar bomb particle but it gives a strong indicator as to it's likeliness.
The problem with this is that the word 'hot' only has meaning to a conscious being. And while we don't know what conciousness is, it's extremely hard to argue it's not an emergent property of physics. So if your supernova simulation is complex enough to also model emergent properties like conciousness, the simulated conciousness may well regard the supernova as 'hot'.
You can avoid the smells with a prompt. I have a benchmark involving short story writing within specific styles and the level of sophistication achievable is increasing over time, in my opinion.
I’d probably word it differently but I agree with much of the sentiment here. I’m also reminded of the stat where 93% of drivers rated themselves as above average.
Indeed. To be honest, I think everyone on HN is aware of how LLMs work at this point, it’s not actually adding a great deal to the discussion to keep going on about autocomplete or ‘stochastic parrots’.