Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

GPT-5.2

openai.com

Post reply on HN
Print view View original

201–210 of 1001 posts

Re: GPT-5.2

#201

Post by Imnimo »

a_wild_dandan wrote: post #183

> Unlike the previous GPT-5.1 model, GPT-5.2 has new features for managing what the model "knows" and "remembers to improve accuracy. Dumb nit, but why not put your own press release through your model to prevent basic things like missing quote marks? Reminds me of that time an OAI released wildly inaccurate copy/pasted bar charts.

It does seem to raise fair questions about either the utility of these tools, or adoption inertia. If not even OpenAI feels compelled to integrate this kind of model-check into their pipeline, what's that say about the business world at-large? Is it that it's too onerous to set up, is it that it's too hard to get only true-positive corrections, is it that it's too low value for the effort?

Re: GPT-5.2

#202

Post by ACCount37 »

dinobones wrote: post #171

It's becoming challenging to really evaluate models. The amount of intelligence that you can display within a single prompt, the riddles, the puzzles, they've all been solved or are mostly trivial to reasoners. Now you have to drive a model for a few days to really get a decent understanding of how good it really is. In my experience, while Sonnet/Opus may not have always been leading on benchmarks, they have always…

The good old "benchmarks just keep saturating" problem.

Anthropic is genuinely one of the top companies in the field, and for a reason. Opus consistently punches above its weight, and this is only in part due to the lack of OpenAI's atrocious personality tuning.

Yes, the next stop for AI is: increasing task length horizon, improving agentic behavior. The "raw general intelligence" component in bleeding edge LLMs is far outpacing the "executive function", clearly.

Re: GPT-5.2

#203

Post by ghosty141 »

sheeshe wrote: post #128
JanSt wrote: post #42

The benchmarks are very impressive. Codex and Opus 4.5 are really good coders already and they keep getting better. No wall yet and I think we might have crossed the threshold of models being as good or better than most engineers already. GDPval will be an interesting benchmark and I'll happily use the new model to test spreadsheet (and other office work) capabilities. If they can going like this just a little bit fu…

Ok so why isn’t there mass lay offs ensuing right now?

Because from my experience using codex in a decently complex c++ environment at work, it works REALLY well when it has things to copy. Refactorings, documentation, code review etc. all work great. But those things only help actual humans and they also take time. I estimate that in a good case I save ~50% of time, in a bad case it's negative and costs time.

But what I generally found, it's not that great at writing new code. Obviously an LLM can't think and you notice that quite quickly, it doesn't create abstractions, use abstractions or try to find general solution to problems.

People who get replaced by Codex are those who do repetitive tasks in a well understood field. For example, making basic websites, very simple crud applications etc..

I think it's also not layoffs but rather companies will hire less freelancers or people to manage small IT projects.

Re: GPT-5.2

#204

Post by tmaly »

simonw wrote: post #125

Wow, there's a lot going on with this pelican riding a bicycle: https://gist.github.com/simonw/c31d7afc95fe6b40506a9562b5e83...

seems to be eating something

Re: GPT-5.2

#205

Post by CamelCaseName »

leaK_u wrote: post #199
jeanlucas wrote: post #188

Earlier quoted context omitted.

no.

how.

I find ChatGPT's voice to text to be the absolute best in the world, nearly perfect.

I have constant frustrations with Gemini voice to text misunderstanding what I'm saying or worse, immediately sending my voice note when I pause or breathe even though I'm midway through a sentence.

Re: GPT-5.2

#206

Post by tmaly »

zug_zug wrote: post #31

For me the last remaining killer feature of ChatGPT is the quality of the voice chat. Do any of the competitors have something like that?

I can't keep up with half the new features all the model companies keep rolling out. I wish they would solve that

Re: GPT-5.2

#207

Post by mrguyorama »

standardUser wrote: post #75
Mistletoe wrote: post #66

Earlier quoted context omitted.

How do you measure whether it works better day to day without benchmarks?

Subscriptions.

Ah yes, humans are famously empirical in their behavior and we definitely do not have direct evidence of the "best" sports players being much more likely than the average to be superstitious or do things like wear "lucky underwear" or buy right into scam bracelets that "give you more balance" using a holographic sticker.

Re: GPT-5.2

#209

Post by g947o »

tedsanders wrote: post #67
breakingcups wrote: post #43

Is it me, or did it still get at least three placements of components (RAM and PCIe slots, plus it's DisplayPort and not HDMI) in the motherboard image[0] completely wrong? Why would they use that as a promotional image? 0: https://images.ctfassets.net/kftzwdyauwt9/6lyujQxhZDnOMruN3f...

Yep, the point we wanted to make here is that GPT-5.2's vision is better, not perfect. Cherrypicking a perfect output would actually mislead readers, and that wasn't our intent.

When I saw that it labeled DP ports as HDMI I immediately decided that I am not going to touch this until it is at least 5x better with 95% accuracy with basic things.

I don't see any advantage in using the tool.

Re: GPT-5.2

#210

Post by verdverm »

stego-tech wrote: post #126
verdverm wrote: post #18

Earlier quoted context omitted.

We're also in benchmark saturation territory. I heard it speculated that Anthropic emphasizes benchmarks less in their publications because internally they don't care about them nearly as much as making a model that works well on the day-to-day

These models still consistently fail the only benchmark that matters: if I give you a task, can you complete it successfully without making shit up? Thus far they all fail. Code outputs don’t run, or variables aren’t captured correctly, or hallucinations are stated as factual rather than suspect or “I don’t know.” It’s 2000’s PC gaming all over again (“gotta game the benchmark!”).

I'm not sure, here's my anecdotal counter example, was able to get gemini-2.5-flash, in two turns, to understand and implement something I had done separately first, and it found another bug (also that I had fixed, but forgot was in this path)

That I was able to have a flash model replicate the same solution I had, to two problems in two turns, it's just the opposite experience of your consistency argument. I'm using tasks I've already solved as the evals while developing my custom agentic setup (prompts/tools/envs). They are able to do more of them today then they were even 6-12 months ago (pre-thinking models).

https://bsky.app/profile/verdverm.com/post/3m7p7gtwo5c2v

Post reply on HN