41–50 of 383 posts
> Even if LLMs make mistakes, the ability of LLMs to deliver useful code and hints improved to the point most skeptics started to use LLMs anyway Here we go again. Statements with the single source in the head of the speaker. And it’s also not true. The llms still produce bad/irrelevant code at such rate that you can spend more time prompting than doing things yourself. I’m tired of this overestimation of llms.
> And I've vibe coded entire ephemeral apps just to find a single bug because why not - code is suddenly free, ephemeral, malleable, discardable after single use. Vibe coding will terraform software and alter job descriptions. I'm not super up-to-date on all that's happening in AI-land, but in this quote I can find something that most techno-enthusiast seem to have decided to ignore: no, code is not free. There are i…
Super skeptical of this claim. Yes, if I have some toy poorly optimized python example or maybe a sorting algorithm in ASM, but this won’t work in any non-trivial case. My intuition is that the LLM will spin its wheels at a local minimum the performance of which is overdetermined by millions of black-box optimizations in the interpreter or compiler signal from which is not fed back to the LLM.
> The fundamental challenge in AI for the next 20 years is avoiding extinction. That's a weird thing to end on. Surely it's worth more than one sentence if you're serious about it? As it stands, it feels a bit like the fearmongering Big Tech CEOs use to drive up the AI stocks. If AI is really that powerful and I should care about it, I'd rather hear about it without the scare tactics.
Also "my product will kill you and everyone you care about" is not as great a marketing strategy as you seem to imply, and Big Tech CEOs are not talking about risks anymore. They currently say things like "we'll all be so rich that we won't need to work and we will have to find meaning without jobs"
>* For years, despite functional evidence and scientific hints accumulating, certain AI researchers continued to claim LLMs were stochastic parrots: probabilistic machines that would: 1. NOT have any representation about the meaning of the prompt. 2. NOT have any representation about what they were going to say. In 2025 finally almost everybody stopped saying so. Man, Antirez and I walk in very different circles! I s…
When it comes to of being able to do novel tasks on known knowledge, they seem to be quite good. One also needs to consider that problem-solving patterns are also a kind of (meta-)knowledge that needs to be taught, either through imitation/memorisation (Supervised Learning) or through practice (Reinforcement Learning). They can be logically derived from other techniques to an extent, just like new knowledge can be derived from known knowledge in general, and again LLMs seem to be pretty decent at this, but only to a point. Regardless, all of this is definitely true of humans too.
> Even if LLMs make mistakes, the ability of LLMs to deliver useful code and hints improved to the point most skeptics started to use LLMs anyway Here we go again. Statements with the single source in the head of the speaker. And it’s also not true. The llms still produce bad/irrelevant code at such rate that you can spend more time prompting than doing things yourself. I’m tired of this overestimation of llms.
Earlier quoted context omitted.
he’s not a “random internet person”, he created Redis. Despite that, I don’t know how authoritative of a figure he is with respect to AI research. He’s definitely a prolific programmer though.
That still qualifies as a random internet person, wrt the topic. And I think the emphasis is on no sources and I beliefs and I thinks, in any case :)
This is a bunch of "I believe" and "I think" with no sources by a random internet person.
> by a random internet person. The creator of Redis.