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OpenAI begins rolling out GPT-6 Astra

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Re: OpenAI begins rolling out GPT-6 Astra

#231

Earlier quoted context omitted.

It's a lot more than just commercially meaningful. Even if you don't care about money, "highly autonomous systems that outperform humans at most economically valuable work" has a lot more weight on "how close we are to achieving human intelligence" than most of the 'AGI' thresholds I've seen yet.

Well, let's learn to walk first. Right now we have just massively jagged intelligence that performs stunning feats in math and single-shotting three.js games, and falls flat on it's face in many every day scenarios. And, it can't even learn.

All intelligence is jagged. Human intelligence is jagged, so is Cetacean intelligence, so is Ape intelligence, so is Corvid intelligence. You could re-orient that statement for any species of intelligence relative to the other, or even individuals within a species. The big problem here is people being so convinced of their specialness they'll just keep sticking their heads in the sand, until we essentialy create God, and by then none of this useless pedantry will even matter. If you can't see we've already learnt to walk then there's nothing more to discuss here.

Re: OpenAI begins rolling out GPT-6 Astra

#233
post #75

Earlier quoted context omitted.

It also has to do something naughty, preferably in a menacing swarm.

Honestly I find these cavalier statements to be in incredibly poor taste. Unless you are completely blind it's obvious that AI is the most significant piece of technology invented since the Atomic Bomb and could very well be the most important thing ever built by Humans full stop. This kind of dismissive attitude is childish and will likely lead to incredibly bad outcomes for humanity.

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Re: OpenAI begins rolling out GPT-6 Astra

#234

Earlier quoted context omitted.

Well, let's learn to walk first. Right now we have just massively jagged intelligence that performs stunning feats in math and single-shotting three.js games, and falls flat on it's face in many every day scenarios. And, it can't even learn.

All intelligence is jagged. Human intelligence is jagged, so is Cetacean intelligence, so is Ape intelligence, so is Corvid intelligence. You could re-orient that statement for any species of intelligence relative to the other, or even individuals within a species. The big problem here is people being so convinced of their specialness they'll just keep sticking their heads in the sand, until we essentialy create God,…

I'm not sure it's accurate to call human intelligence jagged - it seems (perhaps largely thanks to language) that we're able to make progress on anything we set our minds to, and of course we're now in process of building AI that will eventually be able to do things that we ourselves couldn't, whether due to computational demands, or memory capacity, or having sensory inputs that we don't have, etc. But at the end of the day, AI is a tool we've built, so maybe it will make us less jagged, and certainly more capable.

In any case, human intelligence as a goal is special since we live in a human world, and one of the prime goals of AI is to be able to do human jobs. If a human can do something and AI can't then that is a limitation, while if a human can't and AI can't either, that doesn't matter for the time being.

Yeah, I shouldn't have said AI can't walk yet, but most of what it can do is just due to scale - we're still just building big transformers, basically using the same 10 year old architecture that accidentally set us off on this path. I'm not sure we're really progressing towards human/animal type intelligence, just learning how much of our own capability can be realized by automating language.

Re: OpenAI begins rolling out GPT-6 Astra

#235

(Posting partly so I can revisit my predictions when they open access more widely) A big problem I have with OpenAI's models (and of course Claude) is that they tend to write the most over-engineered pieces of code, beyond the imagination of any architecture's astronaut. Just this week I asked 5.6-sol-ultra to update a 1000 LOC python script I had, to "incorporate the key lessons learned when using it for another pro…

The defaults are bad, but these models are highly steerable.

For simple scripts adding to the prompt something like "do not over engineer, do not gold plate, no CLI args, keep it simple" does wonders.

For whole projects, I have a 3 page anti-bloat.md which describes what not to do, stuff like:

> Minimize lines of code, number of files, classes, protocols, factories, wrappers, and dependency-injection objects. Prefer a coherent implementation that is easy to trace end-to-end.

> Use concrete dependencies directly. Do not create protocols, abstract base classes, or adapters unless there are already two real implementations.

> Use direct state fields or a small state dataclass; do not introduce generic lifecycle, state-machine, observer, snapshot, or event framework classes.

The funny thing it was codex which wrote this, I've asked it to analyze an over-engineered abomination that it produced, and to categorize all the bloat it could find.

Re: OpenAI begins rolling out GPT-6 Astra

#236

Earlier quoted context omitted.

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

I’m on HN almost every day advocating for a complete ban of the technology because of its risks and externalities…

Then why are we arguing? I agree with you, I'm highlighting the fact that people making light of the technology is dangerous

Re: OpenAI begins rolling out GPT-6 Astra

#237
post #49

Earlier quoted context omitted.

Would you mind posting that code to github? I'm curious about the complexity you're describing. If not, no worries!

Sure, why not: https://github.com/sergiocorreia/overengineered-rand-mcnally The original script was mostly very simple python: 1. Download some public PDFs. 2. Have a double for-loop (over PDFs and pages within PDF), 3. Use a library to call gemini-3.7-flash and ask it to run some OCR 4. Save JSON outputs, save a csv with results, validate with some Stata code New code folder was 189 files. Just the PDF download fold…

Thanks!

Re: OpenAI begins rolling out GPT-6 Astra

#238

2.5x more expensive than Sol. Can expect 2.5x more usage in Codex subscription. Sol is already brutal (even after their recent fixes, it's just a token-hungry model: I go through a full 20x account per day, on Sol Med/High standard speed, with ~2 threads). Note that Tibo recommended using Sol Med as daily driver. When I'm doing less complicated work, I can't even make it past 2-3 days with Sol Med, whereas I was able…

>token-hungry model

It's kind of funny how this is the exact opposite of the truth. It's one of the most token-efficient models ever.

The claims aren't bullshit. Every conceivable benchmark and test you can throw at it shows Sol being good for token efficiency.

Re: OpenAI begins rolling out GPT-6 Astra

#239

Earlier quoted context omitted.

> It's not meaningless. In fact, it's one of the more meaningful definitions out there. Well, it's commercially meaningful, but it's not meaningful it terms of how close we are to achieving human intelligence. But which one you care about is up to you. If you are all about the money and don't care about human intelligence then for sure go with OpenAI's definition.

It's a lot more than just commercially meaningful. Even if you don't care about money, "highly autonomous systems that outperform humans at most economically valuable work" has a lot more weight on "how close we are to achieving human intelligence" than most of the 'AGI' thresholds I've seen yet.

Traditionally, AGI means being capable of learning everything (not necessarily at once) that can be learned by the same AI agent. It differs from the commercially meaningful definition in that a standard specific-purpose-built AI can still do most tasks if you give it enough specific purposes, but it will be just as incapable of human intelligence as ever.

Re: OpenAI begins rolling out GPT-6 Astra

#240

(Posting partly so I can revisit my predictions when they open access more widely) A big problem I have with OpenAI's models (and of course Claude) is that they tend to write the most over-engineered pieces of code, beyond the imagination of any architecture's astronaut. Just this week I asked 5.6-sol-ultra to update a 1000 LOC python script I had, to "incorporate the key lessons learned when using it for another pro…

Yes, it turns out that using these machines is a littler harder than "make me the thing I want, make no mistakes, do it the way I want you to do it". This isn't "prompt better" advice, it's just to say that you can't simply set it and forget it. There is still engineering work to be done. If you're not watching the thinking traces and catching when it's about to go off the rails, it'll gladly do so. But you can stop…

Or it’s like being an engineering manager, where poor direction on your part results in the team chasing rainbows and unicorns in an attempt to please you. But sure, it’s the tool’s fault!
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