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GPT-6 Astra

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Re: GPT-6 Astra

#611

Post by sensanaty »

thi2 wrote: post #596
manlymuppet wrote: post #403

I have nothing to say about the actual model, but unrelated--why do so many of these demos include people buying things autonomously? Even if I did trust an AI to get everything right, it's not like the AI can read my mind. If I was ordering food normally and without AI, I would want more control over the process--looking over the options, prices, thinking about what I really want. People don't know what they really…

I work for a larger german retail chain and agentic shopping is already on the "near future vision". No one thinks this will be used but somehow shareholders love it.

Lol same story here, I work in payments and 0 people within the company (including the team working on it!) are convinced at all about the viability

Re: GPT-6 Astra

#612

Post by lwansbrough »

intenex wrote: post #248

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…

To me AGI has always meant sentience. And only since we’ve discovered that you can have something that is intelligent without it being apparently sentient that we’ve changed the definition to being, I suppose, more exactly aligned with the namesake.

A real AGI, like the ones from science fiction, would make Astra look like a child’s toy. And I guess more concretely I would expect it to inhibit the following properties: one shot learning - fully (and always) online, perfectly efficient (through self improvement), no context limitations ie. persistently thinking, not just awaiting input.

So for me, no, not AGI yet. But still very intelligent and capable (and perhaps it’s safer this way?)

Re: GPT-6 Astra

#613

Post by GPerson »

manlymuppet wrote: post #403

I have nothing to say about the actual model, but unrelated--why do so many of these demos include people buying things autonomously? Even if I did trust an AI to get everything right, it's not like the AI can read my mind. If I was ordering food normally and without AI, I would want more control over the process--looking over the options, prices, thinking about what I really want. People don't know what they really…

I’m guessing the marketing must mean the AI-shops-for-you use case is a pretty big market, much bigger than AI-makes-life-easier.

Re: GPT-6 Astra

#614

Post by avaer »

Eliezer wrote: post #463
intenex wrote: post #248

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…

> even with Fable, I've been at the point personally where I am reasonably confident that there's essentially nothing that I am better than Fable at despite generally being substantively above average on human benchmarks If I asked you to write fiction, you'd be much better at keeping track of which characters knew which facts.

You could script this in with a time database, illustrations, and appropriate harness, tests, and editing passes. It's a massive problem with human authors too, which is why they do a lot of lorekeeping and editing, so the AI should be afforded the same tools if we are debating human level ability.

I agree on the one-shot (which is not a fair comparison because nobody oneshots a good story), but I'm not convinced this part hasn't reached AGI already.

Re: GPT-6 Astra

#616

Post by Banditoz »

bakies wrote: post #458
pandinus wrote: post #184

Lol their page finally loaded. They added an example scenario of "Filling in Form 1040" - which made me laugh out loud. That is indeed something most US citizens cannot accurately do even with expensive proprietary tax software services. Kind of a Hitchhiker's Guide to the Galaxy meme but where the tax code is so complicated we're implementing powerful AIs to be able to do it (hopefully) right.

i tried to get claude to do my taxes for last year and it refused :( now that i'm a gpt subscriber maybe I'll have luck when i'm filing next year

Are your taxes complicated such that you feel the need to have an LLM do them for you?

Re: GPT-6 Astra

#617

Post by NothingAboutAny »

dingdong2026 wrote: post #485
intenex wrote: post #248

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…

yeah for me it's "I wanna add this new thing to an existing system" and the AI responds "we should just add some arbitrary state here to facilitate this feature". The real issue is the existing system needs to change entirely to facilitate, I know this, Good developers know this, The AI however knows the shitty solution would solve the immediate problem because it's been trained on shitty solutions. the problem could simply be the AI doesn't have all nebulous loose context I have about the goals of the project and future plans, but I would have to write a novel to give it that context.

Re: GPT-6 Astra

#618

Post by ShinyLeftPad »

driverdan wrote: post #247
abixb wrote: post #227

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…

> If this is truly AGI (subject to one's definition of AGI still) Scoring well in a benchmark that's called AGI does not make an LLM AGI.

talking about self proclaimed, it's about as much AGI as openAI is open.

Re: GPT-6 Astra

#619

Post by dgunay »

uludag wrote: post #302
intenex wrote: post #248

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…

Wouldn't "general intelligence" require so much more than scoring well (or even amazingly) on benchmarks? Like what about having some "AGI model" embodied in something (maybe humanoid), and test it by having it step in an assortment of cars and park them. Does bodily-kinesthetic intelligence account for nothing? Humans are intelligent creatures and can dynamically adapt to the physical shape of a variety of vehicles…

This is a big reason why I feel like even though LLMs are _effectively_ AGI in some regard, they also are a hack around what most people figured AGI would look like before the advent of LLMs. Humans can do metacognition, output multimodally at the same time (verbal _and_ physical intelligence go together to produce an expressive face while one talks), have a good sense for what they do and don't know, continuously take in and respond to the world around them in a (mostly) uninterrupted fashion without "turns", learn knew knowledge and retain it for their whole lives, etc. When you reduce a human to a text generator, yes obviously SOTA LLMs perform way better, but rather than invent something that can operate as an always-running "being", we've grafted a harness around an intelligence that is bound purely to speak only when spoken to. Maybe organic intelligence is already that, playing out at a super high refresh rate, but I don't know.

Re: GPT-6 Astra

#620

Post by m0zzie »

XCSme wrote: post #320
GodelNumbering wrote: post #270

The most interesting part, even more than ARC 3 score, to me is that this is the first model I recall seeing that scores lower on Max than High reasoning effort on some coding benchmarks: Terminal-Bench 4.0: High (57.9%), Max (56.7%) DeepSWE: High (73.3%), Max (71.5%) It _loses_ 1-2% performance going to High from Max

That's quite common with many models, after "High" reasoning, over-thinking starts occurring and the model skips over the right solution by convincing itself otherwise.

I find this very amusing, given we humans are also highly susceptible to this.
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