891–900 of 1001 posts
> ScreenSpot-Pro tests whether models can locate the correct interface element in high-resolution screenshots of professional software.
I 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…
1) First, you are talking about positive forward transfer in continual learning. I've been giving talks for the past 6-7 years about how that community (I was one of the founders) went astray and wasn't focusing enough on that topic, but continual learning of the kind you are thinking isn't in any of these systems right now. I think some people left the Grok team to make a start-up to focus on that. By forward transfer, what I mean is weights update over time and past learning improves future learning such that we get better sample efficiency.
2) Psychologists distinguish among different kinds of intelligence for Spearman's g (IQ). Crystalized intelligence is using already acquired knowledge (frontier models probably have maxed out that). Fluid intelligence is reasoning and finding solutions in novel situations or without the necessary crystalized knowledge. [Giving colloquial definitions]
3) Now, interestingly, neither of those are correlated with _creativity_ (just they are independent, note some have this threshold theory but it hasn't held up in recent papers). That's what the AI's really are terrible at -- creativity. But I'd argue the vast majority of humans aren't very creative, with truly out-of-the-box ideas. Given that this is HN, and a non-trivial number of us have ADHD, creativity is positively correlated with ADHD.
I did a bunch of research on these topics for my AGI course that I teach each Spring (where I then point out conflicting definitions and start using multiple alternative terms rather than AGI to distinguish among the different definitions).
What does 'Astra' here mean? Surely they must be referring to the Latin word. Because in another dead language of antiquity, Sanskrit, it means "weapon". Which would be a bit too on-the-nose.
Heck, ask ChatGPT where the name comes from :-)
I feel that for some time now, the biggest constraint when working with models is not their intelligence, but their speed. It does not matter how smart the model is, it will make mistakes, because the instructions are ambiguous and new facts are found during implementation. The biggest problem I've had working with software developers has always been the lag between seeing the results and steering towards the right d…
I think the thing I'm most excited about is the increase in _user prompting_. If I give a poorly constrained/ambiguous prompt, I don't want the model one-shotting assumptions left and right. The demos of Fable/GPT-6 are impressive, but "real AGI" should act more like a collaborator than either a peon or overachiever. It's a tough balance to get right, and although this has been possible to achieve with additional pro…
What I think should happen is that it should update its memory with notes on the proficiency level of the user, so it gets the balance right over time.
This is a problem if you allow your kids to use your ChatGPT account for homework (and silly pictures), like I do.
I feel that for some time now, the biggest constraint when working with models is not their intelligence, but their speed. It does not matter how smart the model is, it will make mistakes, because the instructions are ambiguous and new facts are found during implementation. The biggest problem I've had working with software developers has always been the lag between seeing the results and steering towards the right d…
AI models do not live and learn - it's worse. They actually get DUMMER if you don't start with a clean slate. This is important. One has to curate the context carefully.
It'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?
IMO there has been a regime shift to building things for yourself and what is cool is the output of the tools you make. I have started building my own Digital Audio Workstation. The point is not to build something to compete with Ableton. The point is to build something and make music with it. If it is a good tool then I should be able to make good music with it and release the music. Actually, the DAW should be the…
There's got to be someone to listen to your music in order for that secret sauce to have any meaning.
What's the use of any "secret sauce" in something that only you listen to, because everyone else is either content with AI slop "music", or better yet "create" it for themselves just like you "create" your secret DAW?
- OpenAI claims Astra beats all benchmarks (compared to Fable and Opus, except "Humanity's Last Exam (w/ tools)"): https://openai.com/index/gpt-6-astra/ - Artificial Analysis scores Astra (max effort) as 61 points on intelligence, behind Opus 5. https://artificialanalysis.ai/models/gpt-6-astra Who is wrong here? Some benchmark results in Astra page for Fable and Opus are blank (-). What is Artificial Analysis intelli…
If you scroll down in the Artificial Analysis page you linked, you'll see all the individual benchmarks.
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…
Currently there's a Google Pixel ad where a grandma takes a photo of a board and Gemini automatically fills her calendar with all the events. Yeah sure.