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GPT-6 Astra

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Re: GPT-6 Astra

#471

Post by maherbeg »

Centigonal wrote: post #453
maherbeg wrote: post #349

Ok, but can I bring GPT-6 in as an agent as a software engineer, tell it to talk to these people and have it start solving engineering problems and continue on for a full year career wise? maybe call it EngEmployeeBench

The moment this is possible, you will lose your job.

I imagine the first year we'll be at the Junior eng level, and then after a while make our way up to Staff Engineer. Then we'll have a bunch of staff engineers arguing and protecting their domains and then we'll need a new benchmark.

Re: GPT-6 Astra

#473

Post by shostack »

brokencode wrote: post #423
jdprgm wrote: post #320

Is anyone else just exhausted by the pace of all this. The models change constantly and relentlessly and so does the pricing, basically weekly at this point between all the labs. It feels nearly impossible to have any rigorous approach when choosing a particular model and price point for a task and more like blindly picking one. The time period needed to actually get familiar with various models to a degree you can i…

You really don’t need to watch it that closely. If the model you’re using today is working well, just stick with it. If one day you open up Claude Code and it’s Opus 5.1 now instead of Opus 5, no big deal. It probably will work about the same as it did before. Maybe a little better. Or if you’re on Codex and some new cool Claude model comes out, no worries. There will probably be a similar new model for Codex within…

One suggestion is to make a list or make a skill to have your agent keep a list of things you do not feel work well with today's models. And then, when new models come out, periodically, revisit items on that list to see if you get better results.

Re: GPT-6 Astra

#474

Post by epolanski »

jdprgm wrote: post #320

Is anyone else just exhausted by the pace of all this. The models change constantly and relentlessly and so does the pricing, basically weekly at this point between all the labs. It feels nearly impossible to have any rigorous approach when choosing a particular model and price point for a task and more like blindly picking one. The time period needed to actually get familiar with various models to a degree you can i…

If model X fits your need, you don't need to upgrade.

I have released applications on Gemini 3.5 flash that make real money and I don't see any particular reason to upgrade.

Re: GPT-6 Astra

#475

Post by Zizizizz »

jdprgm wrote: post #320

Is anyone else just exhausted by the pace of all this. The models change constantly and relentlessly and so does the pricing, basically weekly at this point between all the labs. It feels nearly impossible to have any rigorous approach when choosing a particular model and price point for a task and more like blindly picking one. The time period needed to actually get familiar with various models to a degree you can i…

It feels like this every day

https://youtube.com/shorts/vGKC9LpGnOQ?is=iCG7qvAIL9oI5-_d

Re: GPT-6 Astra

#476

Post by [deleted] »

drusepth wrote: post #302
intrasight wrote: post #284

Earlier quoted context omitted.

It has to pass the Turing test

LLMs started meaningfully passing the Turing test a year or two ago, around GPT-4.5. Is there another version or bar for "passing" you're looking for? [0] https://arxiv.org/pdf/2503.23674

[deleted]

Re: GPT-6 Astra

#477

Post by flockonus »

jdprgm wrote: post #320

Is anyone else just exhausted by the pace of all this. The models change constantly and relentlessly and so does the pricing, basically weekly at this point between all the labs. It feels nearly impossible to have any rigorous approach when choosing a particular model and price point for a task and more like blindly picking one. The time period needed to actually get familiar with various models to a degree you can i…

It is exhausting to keep up with model releases yes, much like it was for a while during the Cambrian explosion of FE frameworks, eventually tech seems to work out to consolidation.

But more so it seems there is Fear of missing out (FOMO) in our behaviours. The reality is, if whatever model you are using are good for your purpose, well, keep on it.

Re: GPT-6 Astra

#478

Post by dom96 »

intenex wrote: post #274

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 to me is reached once the intelligence is self motivated, i.e. it doesn't rely on us prompting it into action. I don't see how LLMs will ever get to that stage.

Re: GPT-6 Astra

#479

Post by mbesto »

intenex wrote: post #274

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…

> For the many people who resist the AGI label possibly ever being achieved, I'd be curious to hear takes on what would make you think Astra is yet to be AGI, and what would still need to be achieved for this to effectively be AGI from this point forward.

Simple. AGI is undefinable and benchmarks are notoriously flawed.

Re: GPT-6 Astra

#480

Post by mNovak »

zug_zug wrote: post #433
intenex wrote: post #274

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…

> I'd be curious to hear takes on what would make you think Astra is yet to be AGI, and what would still need to be achieved for this to effectively be AGI from this point forward. To me AGI is all about the "G" general (we already had the AI part). General meaning universal, everything. It's not a function of knowledge or specific hardcoded tests, it's that you could give it a test it's never heard of before and nev…

So the goalposts have moved to include continual learning.

In a sense I think no one will agree on a definition of AGI until it becomes impossible to construct any benchmark under which an AI underperforms "average" humans. That or it's defined retrospectively, after it's overwhelmingly obvious it met any such definition.

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