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Reflections on AI at the End of 2025

antirez.com

161–170 of 383 posts

Re: Reflections on AI at the End of 2025

#161
post #127

LLMs have certainly become extremely useful for Software Engineers, they're very convincing (and pleasers, too) and I'm still unsure about the future of our day-to-day job. But one thing that has scared me the most, is the trust of LLMs output to the general society. I believe that for software engineers it's really easy to see if it's being useful or not -- We can just run the code and see if the output is what we e…

> using AI to ask for medical advice So the number of anti-vaxxers is going to plummet drastically in the following decade, I guess.

Depends if they use lobotomized bots like Grok...

Re: Reflections on AI at the End of 2025

#162
post #127

LLMs have certainly become extremely useful for Software Engineers, they're very convincing (and pleasers, too) and I'm still unsure about the future of our day-to-day job. But one thing that has scared me the most, is the trust of LLMs output to the general society. I believe that for software engineers it's really easy to see if it's being useful or not -- We can just run the code and see if the output is what we e…

> using AI to ask for medical advice So the number of anti-vaxxers is going to plummet drastically in the following decade, I guess.

I haven't tried with this specific topic, but being the pleasers llms are, I doubt someone so focused on being anti-vaxxer will be convinced by an LLM, if anything, the LLM will give them reason at some point.

Re: Reflections on AI at the End of 2025

#163
post #87
post #43

I have programmed 30K+ hours. Do LLMs make bad code: yes all the time (at the moment zero clue about good architecture). Are they still useful: yes, extremely so. The secret sauce is that you'd know exactly what to do without them.

"Do LLMs make bad code: yes all the time (at the moment zero clue about good architecture). Are they still useful: yes, extremely so." Well, lets see how all the economics will play out. LLMs might be really useful, but as far as I can see all the AI companies are not making money on inference alone. We might be hitting plateau in capabilities with money being raised on vision of being this godlike tech that will cha…

> but as far as I can see all the AI companies are not making money on inference alone.

This was the missed point on why GPT5 was such an important launch (quality of models and vibes aside). It brought the model sizes (and hence inference cost) to more sustainable numbers. Compared to previous SotA (GPT4 at launch, or o1/3 series), GPT5 is 8x-12x cheaper! I feel that a lot of people never re-calibrated their views on inference.

And there's also another place where you can verify your take on inference - the 3rd party providers that offer "open" models. They have 0 incentive to subsidise prices, because people that use them often don't even know who serves them, so there's 0 brand recognition (say when using models via openrouter).

These 3rd party providers have all converged towards a price-point per billion param models. And you can check those prices, and have an idea on what would be proffitable and at what sizes. Models like dsv3.2 are really really cheap to serve, for what they provide (at least gpt5-mini equivalent I'd say).

So yes, labs could totally become profitable with inference alone. But they don't want that, because there's an argument to be made that the best will "keep it all". I hope, for our sake as consumers that it isn't the case. And so far this year it seems that it's not the case. We've had all 4 big labs one-up eachother several times, and they're keeping eachother honest. And that's good for us. We get frontier level offerings at 10-25$/MTok (Opus, gpt5.2, gemini3pro, grok4), and we get highly capable yet extremely cheap models at 1.5-3$/MTok (gemini3-flash, gpt-minis, grok-fast, etc)

Re: Reflections on AI at the End of 2025

#164

Earlier quoted context omitted.

> using AI to ask for medical advice So the number of anti-vaxxers is going to plummet drastically in the following decade, I guess.

Depends if they use lobotomized bots like Grok...

>> So the number of anti-vaxxers is going to plummet drastically in the following decade, I guess.

> Depends if they use lobotomized bots like Grok...

What are you on about?

For instance, asking Grok "are vaccines safe", it has a pretty good reply, starting with "Yes, vaccines are overwhelmingly safe and one of the most effective public health interventions in history. Extensive scientific evidence from decades of research, including rigorous clinical trials, post-licensure monitoring, and systematic reviews by organizations like the WHO, CDC, NIH, and independent bodies, shows that the benefits of vaccination far outweigh the risks for individuals and populations." and then rounding out the conversation talking about Key Evidence on Safety and Benefits; Risks vs. Benefits; Addressing Concerns.

https://grok.com/share/c2hhcmQtNA_69e20553-2558-46be-9f21-6a...

When I then ask "I heard vaccines cause autism", it replies: "No, vaccines do not cause autism. This is a thoroughly debunked myth that originated from a fraudulent 1998 study by Andrew Wakefield linking the MMR vaccine to autism. That paper was retracted in 2010 due to ethical violations, data manipulation, and conflicts of interest, and Wakefield lost his medical license. Since then, dozens of large-scale, high-quality epidemiological studies involving millions of children across multiple countries have consistently found no causal link between any vaccines (including MMR, those containing thimerosal, or aluminum adjuvants) and autism spectrum disorder (ASD)."

Seems pretty good to me.

Re: Reflections on AI at the End of 2025

#165
post #127

LLMs have certainly become extremely useful for Software Engineers, they're very convincing (and pleasers, too) and I'm still unsure about the future of our day-to-day job. But one thing that has scared me the most, is the trust of LLMs output to the general society. I believe that for software engineers it's really easy to see if it's being useful or not -- We can just run the code and see if the output is what we e…

I get this take, but given the state of the world (the US anyways), I find it hard to trust anyone with any kind of profit motive. I feel like any information can’t be taken as fact, it can just be rolled into your world view and discarded if useful or not. If you need to make a decision that can’t be backed out of that has real world consequences I think/hope most people are learning to do as much due diligence as r…

> I find it hard to trust anyone with any kind of profit motive.

As much as this is true, and i.e. doctors for sure can profit (here in my country they don't get any type of sponsor money AFAIK, other than having very high rates), there is still accountability.

We have built a society based on rules and laws, if someone does something that can harm you, you can follow the path to at least hold someone accountable (or, try).

The same cannot be said about LLMs.

Re: Reflections on AI at the End of 2025

#166
post #127

LLMs have certainly become extremely useful for Software Engineers, they're very convincing (and pleasers, too) and I'm still unsure about the future of our day-to-day job. But one thing that has scared me the most, is the trust of LLMs output to the general society. I believe that for software engineers it's really easy to see if it's being useful or not -- We can just run the code and see if the output is what we e…

With code, even when it looks correct, it can be subtly wrong and traditional search engines don’t sit there and repeatedly pressure you into merging the PR.

Re: Reflections on AI at the End of 2025

#167
post #36

> 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.

> Here we go again. Statements with the single source in the head of the speaker. And it’s also not true.

You're making the same sort of baseless claim you are criticising the blogger for making. Spewing baseless claims hardly moves any discussion forward.

> The llms still produce bad/irrelevant code at such rate that you can spend more time promoting than doing things yourself.

If that is your personal experience then I regret to tell you that it is only the reflection of your own inability to work with LLMs and coding agents. Meanwhile, I personally manage to effectively use LLMs anywhere between small refactoring needs and large software architecture designs, including generating fully working MVPs in one-shot agent prompts. From this alone it's rather obvious who is making baseless statements that are more aligned with reality.

Re: Reflections on AI at the End of 2025

#169

Earlier quoted context omitted.

No, that doesn’t make you a skeptic in this context. The LLM skeptics claim LLM usefulness is an illusion. That the LLMs are a fad, and they produced more problems than they solve. They cite cherry picked announcements showing that LLM usage makes development slower or worse. They opened ChatGPT a couple times a few months ago, asked some questions, and then went “Aha! I knew it was bad!” when they encountered their…

Skeptic here: I do think LLMs are a fad for software development . They're an interesting phenomen that people have convinced themselves MUST BE USEFUL in the context of software development, either through ignorance or a sense of desperation. I do not believe LLMs will be used long term for any kind of serious software development use cases, as the maintenance cost of the code they produce will run development teams…

In this year of 2025, in December, I find it untenable for anyone to hold this position unless they have not yet given LLMs a good enough try. They're undeniably useful in software development, particularly on tasks that are amenable to structured software development methodologies. I've fixed countless bugs in a tiny fraction of the time, entirely accelerated by the use of LLM agents. I get the most reliable results simply making LLMs follow the "red test, green test" approach, where the LLM first creates a reproducer from a natural language explanation of the problem, and then cooks up a fix. This works extremely well and reliably in producing high quality results.

Re: Reflections on AI at the End of 2025

#170
post #105

>* 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…

Give me an example of one of those rare or unusual tasks.

Set the font size of a simple field in openxml. Doesn't even seem that rare. It said to add a run inside and set the font there. Didn't do anything. I ended up reverse engineering the output out of ms word. This happened yesterday.
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