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2025: The Year in LLMs

simonwillison.net

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Re: 2025: The Year in LLMs

#161

Post by nstart »

syndacks wrote: post #89

I can’t get over the range of sentiment on LLMs. HN leans snake oil, X leans “we’re all cooked” —- can it possibly be both? How do other folks make sense of this? I’m not asking for a side, rather understanding the range. Does the range lead you to believe X over Y?

The problem with X is that so many people who have no verifiable expertise are super loud in shouting "$INDUSTRY is cooked!!" every time a new model releases. It's exhausting and untrue. The kind of video generation we see might nail realism but if you want to use it to create something meaningful which involves solving a ton of problems and making difficult choices in order to express an idea, you run into the walls of easy work pretty quickly. It's insulting then for professionals to see manga PFPs on X put some slop together and say "movie industry is cooked!". It betrays a lack of understanding of what it takes to make something good and it gives off a vibe of "the loud ones are just trying to force this objectively meh-by-default thing to happen".

The other day there was that dude loudly arguing about some code they wrote/converted even after a woman with significant expertise in the topic pointed out their errors.

Gen AI has its promise. But when you look at the lack of ethics from the industry, the cacophony of voices of non experts screaming "this time it's really doom", and the weariness/wariness that set in during the crypto cycle, it's a natural tendency that people are going to call snake oil.

That said, I think the more accurate representation here is that HN as a whole is calling the hype snake oil. There's very little question anymore about the tools being capable of advanced things. But there is annoyance at proclamations of it being beyond what it really is at the moment which is that it's still at the stage of being an expertise+motivation multiplier for deterministic areas of work. It's not replacing that facet any time soon on its current trend (which could change wildly in 2026). Not until it starts training itself I think. Could be famous last words

Re: 2025: The Year in LLMs

#162

Post by ewoodrich »

vunderba wrote: post #141
didip wrote: post #67

Indeed. I don't understand why Hacker News is so dismissive about the coming of LLMs, maybe HN readers are going through 5 stages of grief? But LLM is certainly a game changer, I can see it delivering impact bigger than the internet itself. Both require a lot of investments.

> I don't understand why Hacker News is so dismissive about the coming of LLMs. Eh. I wouldn’t be so quick to speak for the entirety of HN. Several articles related to LLMs easily hit the front page every single day, so clearly there are plenty of HN users upvoting them. I think you're just reading too much into what is more likely classic HN cynicism and/or fatigue.

Exactly. There was a stretch of 6 months or so right after ChatGPT was released where approximately 50% of front page posts at any given time were related to LLMs. And these days every other Show HN is some kind of agentic dev tool and Anthropic/OpenAI announcements routinely get 500+ comments in a matter of hours.

Re: 2025: The Year in LLMs

#164

Post by mgfist »

OGEnthusiast wrote: post #15
throwup238 wrote: post #4

Earlier quoted context omitted.

> they voted to add some syntactic sugar to Java... I remember when we just wanted to rewrite everything in Rust. Those were the simpler times, when crypto bros seemed like the worst venture capitalism could conjure.

Crypto bros in hindsight were so much less dangerous than AI bros. At least they weren't trying to construct data centers in rural America or prop up artificial stocks like $NVDA.

It's funny how people complain about the rust belt dying and factories leaving rural communities and so on, then when someone wants to build something that can provide jobs and tax revenue, everyone complains.

Re: 2025: The Year in LLMs

#165

Post by nasnsjdkd »

simonw wrote: post #130
probably_wrong wrote: post #129

Earlier quoted context omitted.

Speaking for myself: because if the hype were to be believed we should have no relational databases when there's MongoDB, no need for dollars when there's cryptocoins, all virtual goods would be exclusively sold as NFTs, and we would be all driving self-driving cars by now. LLMs are being driven mostly by grifters trying to achieve a monopoly before they run out of cash. Under those conditions I find their promises h…

The way I've been handling the deafening hype is to focus exclusively on what the models that we have right now can do. You'll note I don't mention AGI or future model releases in my annual roundup at all. The closest I get to that is expressing doubt that the METR chart will continue at the same rate. If you focus exclusively on what actually works the LLM space is a whole lot more interesting and less frustrating.

[flagged]

Re: 2025: The Year in LLMs

#166

Post by ewoodrich »

d4rkp4ttern wrote: post #132
sanreau wrote: post #5

> Vendor-independent options include GitHub Copilot CLI, Amp, OpenHands CLI, and Pi ...and the best of them all, OpenCode[1] :) [1]: https://opencode.ai

Can OpenCode be used with the Claude Max or ChatGPT Pro subscriptions, i.e., without per-token API charges?

Yes, I use it with a regular Claude Pro subscription. It also supports using GitHub Copilot subscriptions as a backend.

Re: 2025: The Year in LLMs

#167

Post by crystal_revenge »

handoflixue wrote: post #158
crystal_revenge wrote: post #154

Earlier quoted context omitted.

That must have been a long time back. Having lived through the time when web pages were served through CGI and mobile phones only existed in movies, when SVMs where the new hotness in ML and people would write about how weird NNs were, I feel like I've seen a lot more concrete progress in the last few decades than this year. This year honestly feels quite stagnant. LLMs are literally technology that can only reproduc…

> LLMs are literally technology that can only reproduce the past. Funny, I've used them to create my own personalized text editor, perfectly tailored to what I actually want. I'm pretty sure that didn't exist before. It's wild to me how many people who talk about LLM apparently haven't learned how to use them for even very basic tasks like this! No wonder you think they're not that powerful, if you don't even know ba…

> You really owe it to yourself to try them out.

I've worked at multiple AI startups in lead AI Engineering roles, both working on deploying user facing LLM products and working on the research end of LLMs. I've done collaborative projects and demos with a pretty wide range of big names in this space (but don't want to doxx myself too aggressively), have had my LLM work cited on HN multiple times, have LLM based github projects with hundreds of stars, appeared on a few podcasts talking about AI etc.

This gets to the point I was making. I'm starting to realize that part of the disconnect between my opinions on the state of the field and others is that many people haven't really been paying much attention.

I can see if recent LLMs are your first intro to the state of the field, it must feel incredible.

Re: 2025: The Year in LLMs

#168

Post by llmslave2 »

HPMOR wrote: post #159
llmslave2 wrote: post #144

Earlier quoted context omitted.

Pretty neat how this exponential progress hasn't resulted in exponential productivity. Perhaps you could explain your perspective on that?

I think this is an open question still and very interesting. Ilya discussed this on the Dwarkesh podcast. But the capabilities of LLMs is clearly exponential and perhaps super exponential. We went from something that could string together incoherent text in 2022 to general models helping people like Terrance Tao and Scott Aaronson write new research papers. LLMs also beat IMO and the ICPC. We have entered the John He…

> But the capabilities of LLMs is clearly exponential and perhaps super exponential

By what metric?

Re: 2025: The Year in LLMs

#169

Post by mgfist »

llmslave2 wrote: post #144
aoeusnth1 wrote: post #128

Earlier quoted context omitted.

We're very clearly seeing exponential progress - even above trend, on METR, whose slope keeps getting revised to a higher and higher estimate each time. Explain your perspective on the objective evidence against exponential progress?

Pretty neat how this exponential progress hasn't resulted in exponential productivity. Perhaps you could explain your perspective on that?

Because that requires adoption. Devs on hackernews are already the most up to date folks in the industry and even here adoption of LLMs is incredibly slow. And a lot of the adoption that does happen is still with older tech like ChatGPT or Cursor.

Re: 2025: The Year in LLMs

#170

Post by llmslave2 »

aoeusnth1 wrote: post #157
llmslave2 wrote: post #144

Earlier quoted context omitted.

Pretty neat how this exponential progress hasn't resulted in exponential productivity. Perhaps you could explain your perspective on that?

It has! CLs/engineer increased by 10% this year. LLMs from late 2024 were nearly worthless as coding agents, so given they have quadrupled in capability since then (exponential growth, btw), it's not surprising to see a modestly positive impact on SWE work. Also, I'm noticing you're not explaining yourself :)

Hey, I'm not the OG commentator, why do I have to explain myself! :)

When Fernando Alonso (best rookie btw) goes from 0-60 in 2.4 seconds in his Aston Martin, is it reasonable to assume he will near the speed of light in 20 seconds?

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