[itay-maman]

Something that caught my eye from the announcement:

> GPT‑5.3‑Codex is our first model that was instrumental in creating itself. The Codex team used early versions to debug its own training

I'm happy to see the Codex team moving to this kind of dogfooding. I think this was critical for Claude Code to achieve its momentum.

[codethief]

Sounds like the researchers behind https://ai-2027.com/ haven't been too far off so far.

[cootsnuck]

We'll see. The first two things that they said would move from "emerging tech" to "currently exists" by April 2026 are:

- "Someone you know has an AI boyfriend"

- "Generalist agent AIs that can function as a personal secretary"

I'd be curious how many people know someone that is sincerely in a relationship with an AI.

And also I'd love to know anyone that has honestly replaced their human assistant / secretary with an AI agent. I have an assistant, they're much more valuable beyond rote input-output tasks... Also I encourage my assistant to use LLMs when they can be useful like for supplementing research tasks.

Fundamentally though, I just don't think any AI agents I've seen can legitimately function as a personal secretary.

Also they said by April 2026:

> 22,000 Reliable Agent copies thinking at 13x human speed

And when moving from "Dec 2025" to "Apr 2026" they switch "Unreliable Agent" to "Reliable Agent". So again, we'll see. I'm very doubtful given the whole OpenClaw mess. Nothing about that says "two months away from reliable".

[YawningAngel]

I don't think generative AI is even close to making model development 50% faster

[beernet]

Only on HN will people still doubt what is happening right in front of their eyes. I understand that putting things into perspective is important, still, the type of downplaying we can see in the comments here is not only funny but also has a dangerous dimension to it. Ironically, these are the exact same people who will claim "we should have prepared better!" once the effects become more and more visible. Dear super engineers, while I feel sorry that your job and passion become a commodity right in front of you, please stay out the way.

[0x1ceb00da]

Is gpt5.3 200x bigger than gpt4? Looks like openai used this fanfiction as its marketing strategy

[JackYoustra]

> researchers

that's certainly one way to refer to Scott Alexander

[aurareturn]

More importantly, this is the early steps of a model self improving itself.

Do we still think we'll have soft take off?

[mrandish]

> Do we still think we'll have soft take off?

There's still no evidence we'll have any take off. At least in the "Foom!" sense of LLMs independently improving themselves iteratively to substantial new levels being reliably sustained over many generations.

To be clear, I think LLMs are valuable and will continue to significantly improve. But self-sustaining runaway positive feedback loops delivering exponential improvements resulting in leaps of tangible, real-world utility is a substantially different hypothesis. All the impressive and rapid achievements in LLMs to date can still be true while major elements required for Foom-ish exponential take-off are still missing.

[reducesuffering]

This has already been going on for years. It's just that they were using GPT 4.5 to work on GPT 5. All this announcement mean is that they're confident enough in early GPT 5.3 model output to further refine GPT 5.3 based on initial 5.3. But yes, takeoff will still happen because of this recursive self improvement works, it's just that we're already past the inception point.

[thrance]

I think the limiting factor is capital, not code. And I doubt GPTX is anymore competent at raising funds than the other, fleshy, snake oilers...

[quinncom]

Exponential growth may look like a very slow increase at first, but it's still exponential growth.

[aaaalone]

I'm only saying no to keep optimistic tbh

It feels crazy to just say we might see a fundamental shift in 5 years.

But the current addition to compute and research etc. def goes in this direction I think.

[8note]

making the specifications is still hard, and checking how well results match against specifications is still hard.

i dont think the model will figure that out on its own, because the human in the loop is the verification method for saying if its doing better or not, and more importantly, defining better