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GPT-6 Astra

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Re: GPT-6 Astra

#581
post #354

It's fun, but every new model release makes me even less interested to create cool stuff. Like, what's the point, if the next AI can do it in 5 seconds?

> Like, what's the point, if the next AI can do it in 5 seconds? I built a phone app recently, not released to the public, just an idea I had for ages but could never spend the time actually building. Its 100% vibe coded, and took me a few weekends to build... I'm talking a few hours in total. The point I'm making is that you now have the power to create stuff you would never have had the time to build. You can think…

Yes, that's cool and useful. Creating stuff for ourselves, for our own use. But we are social animals, we like sharing.

Before it was cool to share an app you made, but now? What's the point of sharing an app, if the other person can make their own, even better suited for their needs, in a few seconds?

Re: GPT-6 Astra

#582

For people skeptical of AGI. Consider the following: 15 years ago if you were the sole proprietor of these models, would you be able to hold a dozen remote junior engineer jobs? Maybe even more? These models could certainly pass all interviews with flying colors and even survive independently in a company role. I think sole ownership of AI 15 years ago could be worth north of $10 million per year. Just as rank-and-fi…

Cool. Being sole proprietor of AGI 15 years ago should result in monuments and religions devoted to you today. Cancer should be cured, and we should be a post-quantum interstellar fusion-powered civilization. I wish the AGI crowd would finally shut up now that it's clear no one is even trying for AGI (OpenAI revised that to "$100B in profit") What we're getting is incredible, where we're headed is incredible, but som…

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Re: GPT-6 Astra

#584

The ARC-AGI-3 scorecard is extremely misleading given that it clearly states itself that "with [the responses API] harness, we estimate Sol would score in the ballpark of ~30%." but it shows a score of 7.8% for GPT-5.6 Sol presumably since if they updated the percentage for GPT-5.6 Sol to the score it would receive with the responses API harness they used for GPT-6 Astra they'd have to do the same for the percentage…

Only someone who doesn't do any work of any meaningful difficulty could think these models have anything to do with AGI. Today I spent half a day trying to solve a moderately interesting software engineering problem. I was switching between GPT-5.6 Sol and Fable 5.1 to check each other's work in Cursor. And the result was gradually driving me insane. As the models struggled to find a solution that would actually work…

What was the problem?

Re: GPT-6 Astra

#585

The ARC-AGI-3 scorecard is extremely misleading given that it clearly states itself that "with [the responses API] harness, we estimate Sol would score in the ballpark of ~30%." but it shows a score of 7.8% for GPT-5.6 Sol presumably since if they updated the percentage for GPT-5.6 Sol to the score it would receive with the responses API harness they used for GPT-6 Astra they'd have to do the same for the percentage…

AGI is a meaningless term that can mean nothing and everything at the same time. It can be used by AI bros to hype their latest releases which are always one step away from achieving AGI, or it can be used by anti-AI people to say it's not AGI because of X arbitrary thing they decided on in the moment. It's a term of pure convenience meant to obfuscate other more pressing discussions on the topic.

Most telling is M$ or whichever one of these borg megacorpos defined AGI as (paraphrased) "AGI is whatever tooling earns us a gazillion dollars in revenue"

Re: GPT-6 Astra

#586
post #354

It's fun, but every new model release makes me even less interested to create cool stuff. Like, what's the point, if the next AI can do it in 5 seconds?

The point is to inject something into the process that these AIs can't do for you. People SHOULD feel like making a useless Mario Kart clone isn't worth the effort anymore. They should, instead, be trying to figure out how to actually use these models to make something that doesn't feel like a useless Mario Kart clone.

One thing that still stands today, is that even vibe-coding a good product takes time and thousands of dollars in tokens costs.

Software will be more like a "proof of work", where people would still pay $100 for good software that took $10k tokens to build.

Re: GPT-6 Astra

#587
post #239

I want to take a step back: So, this is GPT-6 -- the natural number version release comparable to GPT-4 and GPT-5 from the past few years. The ARC-AGI-3 score is obviously impressive at 99.9% (we'll need to wait for more details on how they used the response API harness on GPT-6 Astra, wrt reasoning retention and compaction), but every other benchmarks seems to be a relatively modest improvement, comparable with any…

We've had AGI (artificial general intelligence) probably since the first release of ChatGPT, and certainly since the first agentic harnesses. They're just finally acknowledging what the term means.

Re: GPT-6 Astra

#588

I can’t help but notice how much this echoes Francois Chollet’s On the Measure of Intelligence: https://arxiv.org/abs/1911.01547 Most of frontier-model progress still looks like skill acquisition optimization: broader benchmark coverage and performance, more domains absorbed into the training distribution, and increasingly strong performance within that surface area. It seems more about coverage-driven competence. So…

They can do new tasks with in-context learning but its obviously limited by context window

Re: GPT-6 Astra

#590

OpenAI is killing it now that they are more focused. Killing projects like Sora et al have seen it go from irrelevant to level footing with Anthropic. Sol is so much better than Fable 5. Then we get Astra (yet to use it) few days after Fable 5.1 (which is very impressive). Codex is slightly better than Claude Code. Good on Sam Altman getting back to basics and turning OpenAI around.

Codex is missing a few things that Claude code has had for some time like defined plugin subagents and a few other things. But overall it’s fairly capable. The biggest gripe I have is that codex really restricts context window sizes and compaction leads to a lot of grounding work, and overall codex GPT is too literal in many situations - it’s follows direction slavishly, and when subagent reviewers are used, they tend to find increasingly obscure “flaws” on the instruction following impetus, and the harness agent takes them literally as issues to fix even when it leads to bizarre outcomes. For instance I’ve had several runs where it tries to end up building a hermetic system with sha hashing of everything (including operating system binaries and kernels, tool chains, etc) to certify test results are valid, etc. I have to sort of watch it carefully to be sure it’s not drifting into some insane yak shaving corner, which it will happily do for weeks on end.

Claude has the exact opposite problem, especially opus-5, where I literally can’t trust it to print hello world without taking a shortcut, or just simply lying and saying it printed it when it didn’t, behind a giant wall of inscrutable text. I find it very ironic that Anthropic is the vendor of the lazy lying cheating model that does almost everything you tell it to it do.

I’d really kill for something that balances instruction following and loop escaping behavior better. Fable 5.1 does seem a lot better, feeling more like 4.6 behavior, and honestly Sol has improved as well. I’m pretty psyched for the next generation, as I think the competition has heated up so much that things will improve really fast to the point of marginal utility opportunity being increasingly close to epsilon.

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