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OpenAI begins rolling out GPT-6 Astra

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Re: OpenAI begins rolling out GPT-6 Astra

#203
post #25

I think they embargoed the news, and then they failed to put up their own blog post synchronized to the scheduled news releases, probably because of the outages they're having today. Reuters announced at 2.03pm and at 2.40pm still no blog post. All the news articles say that OpenAI announced it in a blog post, of course. All the love to the folks at OpenAI scrambling to get this out right now! Edit: HN user codergaut…

This stood out: "Artificial Analysis Intelligence Index v4.1.1 61.2" So on the Metacritic of LLM benchmarks, it's.. basically where everyone else is (except for Fable 5.1, which is a bit ahead).

On their Agentic Index, GPT-6 Astra (both max/xhigh) has the same result as Qwen3.8-27b. Weird.

Re: OpenAI begins rolling out GPT-6 Astra

#205
post #22

Earlier quoted context omitted.

You should have a sub agent adversarially enforce KISS before every commit.

"You should have a sub-hammer to adversarially enforce that your primary hammer accurately drives nails into wood" We wouldn't accept such behavior from any other tool, machine, or computer program. At least most of us would not. To paraphrase the old saying: Some people, when confronted with a problem with an AI model think "I know, I'll use an additional AI model." Now they have two problems. I find it very intrigu…

Human level programmers generally suck too. Unending security holes have been human behavior ever since we started sharing computers.

Also, programming isn't a destination, it is a process and everyone has a different ruleset on what that process looks like. Writing a computer program of any complexity is not a determinalistic process. Trying to compare it to a detemanilisic tool will just leave you with broken analogies and a poorer understanding of the world.

Or another way to say this. If programming were deteminalistic we'd have solved it without AI.

Re: OpenAI begins rolling out GPT-6 Astra

#206
post #181

Earlier quoted context omitted.

Apparently Greg Brockman said that as far as he's concerned it may be AGI, or something along those lines. OTOH OpenAI have their own meaningless definition of AGI as "able to do most commercially valuable work" or somesuch, which I'm sure is not true, and is also not what I'd call AGI. If it can't learn for itself, then it's certainly not AGI. The biggest significance of anyone at OpenAI calling it AGI is their cont…

>If it can't learn for itself, then it's certainly not AGI. What does this even mean, exactly? For example if it can filter new information to put into the next version of itself does that qualify? If not, explain exactly why that's the case.

Ask 100 people what their definition of AGI is and you'll probably get 100 different answers.

My definition is closer to DeepMind's "can do any [computer-based] task that a human can do", and certainly a human intern can learn on the job and do better on day #2 than day #1.

Learning is basically THE hallmark of intelligence. Being able to learn from experience and use that to do better in the future.

If you could somehow take everything the LLM learnt today and "put it into" an update for tomorrow that would be better than nothing, but the intern on the job is probably learning dozens of things per day that stack upon each other, so that's going to be a S-L-O-W learning AI intern !

Leaving aside the technical issue how you could store a days learning, or what that would even mean, you've also got the privacy and merge issues if this were to be done in the cloud without every customer having their own personalized model.

For real continual learning we need to get past gradient descent-based batch training and develop a new learning algorithm so the model itself learns incrementally as it runs (animal-like predict, observe, learn cycle), rather than being reliant on some external alien to come in, equipped with it's entire learning curriculum, and program its weights.

Re: OpenAI begins rolling out GPT-6 Astra

#207

So, on the one hand, we have AGI; on the other, the release page is returning 500s.

just because they have smart AI, it does not mean they are great at software and cdn.

Their entire sales pitch is based on the idea that no one will need to be any good at anything, because the AI will do it for them.

If they can't ask the AI to configure their CDN correctly, it undermines the validity of their claims. Maybe it's trivial, but any Omnipotent Machine-God deserving of the name wouldn't forget to zip up his fly.

Re: OpenAI begins rolling out GPT-6 Astra

#208

Earlier quoted context omitted.

Please tell me that’s satire, it’s literally impossible to differentiate from actual AI boosters

You have blinders on. AI is becoming more dangerous by the day.

Sorry the open sourcers cannot ever come to that believe as it sets up a conflict that cannot be resolved by their moral framework. Exactly like libertarians saying "just a little less regulation and we'll reach utopia".

Re: OpenAI begins rolling out GPT-6 Astra

#209
post #23

Am I the only that thinks that anything similar to AGI will come not from raw model capacity but from model speed and efficiency? In my experience the harness is more important than the model, and anything able to run at 700tps will be the "next big thing". PS: assuming the current architecture is the right one

Why would speed matter? Surely an AGI could think slowly but still be an AGI

Currently AGI has been re-defined mostly as "can do any tasks (of the same modality) a human can, equal or better". I feel the "equal or better" includes properties like how fast they can get the task done, not just that eventually they can succeed at it. If you want to have AGI stock buy/sell for example, speed of decision will matter, and there are many other use-cases for which it would matter, not all, but definitely for many tasks, speed does matter.

Re: OpenAI begins rolling out GPT-6 Astra

#210
post #82

Earlier quoted context omitted.

The cost-per-task in the charts from the now-remove blog post put it more at Sol-level cost per task, however. It seems like the model is significantly more token efficient in the benchmarks

that's all openai models but i'm very happy openai continues to focus on efficiency rather than reasoningtokenmaxxing

My assumption is in the long term that efficiency will break interpretability, which will lead to questionable alignment. As efficiency drives capitalism and evolution we'll run headlong at it and try to deal with the risk as a side effect.
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