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Reflections on AI at the End of 2025

antirez.com

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Re: Reflections on AI at the End of 2025

#91

There's videos about Diffusion LLMs too, apparently getting rid of the linear token generation. But I'm no ML engineer.

As someone who worked on transformer-based diffusion models before (not for language though), i can say one thing: they're hard. Denoising diffusion models benefited a lot from the u-net, which is a pretty simple network (compared to a transformer) and very well-adapted to the denoising task. Plus diffusion on images is great to research because it's very easy to visualize, and therefore to wrap your head around Doin…

Thanks. Do you see that part of the field as plateauing or ramping up (even taking into account the difficulty).

If you know labs / researchers on the topic, i'd love to read their page / papers

Re: Reflections on AI at the End of 2025

#92
post #87

Earlier quoted context omitted.

"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…

If the tech plateaus today, LLM plans will go to $60-80/mo, Chinese-hosted chinese models will be banned (national security will be the given reason), and the AI companies will be making ungodly money. I'm not gonna dig out the math again, but if AI usage follows the popularity path of cell phone usage (which seems to be the case), then trillions invested has a ROI of 5-7 years. Not bad at all.

OpenAI would still lose money if the basic subscriptions were costing $500 and they had the same amount of subscribers as right now. There's not a single model shop who's ever making any money, let alone ungodly amounts.

Re: Reflections on AI at the End of 2025

#93
post #65
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.

OK, maybe. But how many programmers will know this in 10 years' time as use of LLMs is normalized? I like to hear what employers are saying already about recent graduates.

I'm uncertain that programming will be a major profession in 10 years.

Programming is more like math than creative writing. It's largely verifiable, which is where RL is repeatedly proven to eventually achieve significantly better than human intelligence.

Our saving grace, for now, is that it's not entirely verifiable because things like architectural taste are hard to put into a test. But I would not bet against it.

Re: Reflections on AI at the End of 2025

#94
post #65
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.

OK, maybe. But how many programmers will know this in 10 years' time as use of LLMs is normalized? I like to hear what employers are saying already about recent graduates.

If they don't learn that they won't get very far.

This is true for everything, any tool you might use. Competent users of tools understand how they work and thus their limitations and how they're best put to work.

Incompetents just fumble around and sometimes get things working.

Re: Reflections on AI at the End of 2025

#96
post #7

> 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.

What makes it a scare tactic? There are other areas in which extinction is a serious concern and people don't behave as though it's all that scary or important. It's just a banal fact. And for all of the extinction threats, AI included, it's very easy to find plenty of deep dive commentary if you care.

Re: Reflections on AI at the End of 2025

#97
post #13

Earlier quoted context omitted.

> by a random internet person. The creator of Redis.

Sure but quite a few claims in the article are about AI research. He does not have any qualifications there. If the focus was more on usefulness, that would be a different discussion and then his experience does add weight.

> smart, intelligent person gives opinion

> woah buddy this persons opinion isn’t worth anything more than a random homeless person off the street. they’re not an expert in this field

Is there a term for this kind of pedantry? Obviously we can put more weight behind the words a person says if they’ve proven themselves trustworthy in prior areas - and we should! We want all people to speak and let the best idea win. If we fallback to only expert opinions are allowed that’s asking to get exploited. And it’s also important to know if antirez feels comfortable spouting nonsense.

This is like a basic cornerstone of a functioning society. Though, I realize this “no man is innately better than another, evaluate on merit” is mostly a western concept which might be some of my confusion.

Re: Reflections on AI at the End of 2025

#98
post #13
post #12

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.

Don't see how that gives him more credibility wrt AI.

His entirely unsupported statements about AGI are pretty useless, for instance.

So many people assume AGI is possible, yet no one has a concrete path to it or even a concrete definition of what it or what form it might take.

Re: Reflections on AI at the End of 2025

#99
> Programmers resistance to AI assisted programming has lowered considerably. 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: now the return on the investment is acceptable for many more folks.

I'm not a fan of this phrasing. Use of the terms "resistance" and "skeptics" implies they were wrong. It's important we don't engage in revisionist history that allows people in the future to say "Look at the irrational fear programmers had of AI, which turned out to be wrong!" The change occurred because LLMs are useful for programming in 2025 and the earliest versions weren't for most programmers. It was the technology that changed.

Re: Reflections on AI at the End of 2025

#100

Earlier quoted context omitted.

If the tech plateaus today, LLM plans will go to $60-80/mo, Chinese-hosted chinese models will be banned (national security will be the given reason), and the AI companies will be making ungodly money. I'm not gonna dig out the math again, but if AI usage follows the popularity path of cell phone usage (which seems to be the case), then trillions invested has a ROI of 5-7 years. Not bad at all.

OpenAI would still lose money if the basic subscriptions were costing $500 and they had the same amount of subscribers as right now. There's not a single model shop who's ever making any money, let alone ungodly amounts.

These costs you are referencing are training/R&D costs. Take those largely away, and you are left with inference costs, which are dirt cheap.

Now you have a world of people who have become accustomed to using AI for tons of different things, and the enshittification starts ramping up, and you find out how much people are willing to pay for their ChatGPT therapist.

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