[flagged]
GPT-6 Astra
811–820 of 1001 posts
Re: GPT-6 Astra
#812It'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 depressing thing about tennis is that no matter how good I get, I'll never be as good as a wall.“ -Mitch Hedberg
I don’t like being this person, but you can very easily beat a wall at tennis.
Re: GPT-6 Astra
#813The launch video is incredibly cringe.
Humans adapt to change oddly fast. If you saw that video in 2022 you'd be 100% positive you were watching a sci-fi movie.
Re: GPT-6 Astra
#814The 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…
If you define AGI as "can do the work of a human sitting at a computer, end to end", then I'd say comparing yourself to it on a specific skill is the wrong test. Can you hand it a role and walk away for a day/week/month? I can’t yet. I think that I'd want at least two things it doesn't have: the ability to retain what it learned yesterday (without me carrying it in the context window and thus micromanaging it), and t…
To be fair, I think you can't hand a role over to someone you just hired and walk away for a week. No matter how much of a SME they are. Let's not forget human onboarding takes months. With the advantage of their knowledge not going into the void multiple times a day. That's likely the last missing piece, a solid system of memories that produces the same effect as short/long term memories in a person.
Re: GPT-6 Astra
#815I 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…
>The harder question, in Chollet’s framing, is: how efficiently can a system learn to do something genuinely new?
The more diverse stuff it knows, the easier it will be to learn something new.
Re: GPT-6 Astra
#816What is going to become of life for those of us who do not work at AI labs and are unlikely to be hired by AI labs, despite all the years we put into learning coding, math, etc, as we were told to do? Those of us who made the mistake of studying anything other than machine learning. How will we make a living? (We don't live in a world that seems likely to distribute gains widely instead of largely to the handful of a…
> How will we make a living? Don't be selfish. Think first of all the jobs that are already dead. A friend of mine she's a translator: like translating financial documents between french/english/spanish. It's over for her: she doesn't get 10% of the gigs she used to get and the 10% she gets is... Verifying AI output. Think of the artists: I'm sorry for those too, for for many it's already game over today . > How will…
> Think of the artists: I'm sorry for those too, for for many it's already game over today.
No it's not??? People want human made art. Abstract artists didn't paint anything technically challenging and they sold art for millions because art is about human connection and human inventiveness, not whatever prompt you could feed into an AI.
> he'll also help your company fix the mess LLMs created.
Hugely valuable. I keep a list of every PR I halted which was AI generated with AI commit summaries and AI tests and no human reviewer till me. It's very easy to convince people to keep me around. AIs are smarter than ever but the people using them and putting the prompts in and not reading the output are still as dumb as before
Re: GPT-6 Astra
#817That hero video is interesting. A projector and speech. Maybe I'm in the minority here, but I find speech to text / text to speech (but not live audio mode) is quite comfortable and effective for coding now. The speech to text part can be frustrating if your local tts model does not have word match context for coding. Codex desktop does this remotely well but is slow. I've been experimenting with local software for m…
given the fact that we've moved in my office from 3-people offices to open-plan office to flex desk now I'm not exactly sure I would want my coworkers to speak all day to their computers and gesturing / walking in front of a projector (provided there will still be coworkers with IA)
Re: GPT-6 Astra
#818Re: GPT-6 Astra
#819I'm sure it's going to do great on all sorts of benchmarks, but the video--the actual marketing video that if anything is incentivised to overstate things--is full of careful cuts just before it would do anything that still wouldn't actually be that impressive. It's AGI, and it's going to upload photos, or change a background slide colour. Even the people hyping it up, who believe that it's really artificial intellig…
The rocket they 3D print at the end isn't even the same as the one in the game. It has a curved body, but the game asset is a cylinder.
Re: GPT-6 Astra
#820The 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…
In my view, intelligence includes an ability to learn and adapt to never-before-seen situations. And then general intelligence is an ability to apply that across a wide variety of domains.
Machines can certainly recognize patterns and achieve goals through brute force trial and error. They can also use the results of previous iterations to change their behavior in future iterations, which we could call learning. I wouldn’t necessarily say they are good at brand new situations, but there has definitely been progress.
However, last I checked, a seemingly very intelligent LLM still struggles to play Chess at a basic level, let alone drive a robot or other non-language tasks. Its architecture and ability to learn seem a long way off from being general.
Vision models, being able to encompass language and much more, seem to me like a theoretically closer step to AGI. Yet, there is a lot more to the world than just what we can see.
On the other hand, in humans, vision certainly is not necessary for intelligence. So there is something more fundamental, neither vision nor language, that high levels of intelligence are based upon. Once we figure that out, I think we will be able to build AGI.