GPT-6 Astra
841–850 of 1001 posts
Re: GPT-6 Astra
#842That 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)
Of course they're mercilessly mocking you instead, but hey.
Re: GPT-6 Astra
#843If it's AGI then can it replace Sam Altman yet?
Re: GPT-6 Astra
#844I 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…
Re: GPT-6 Astra
#845I 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…
Define novel intelligence in a way that would not exclude 95% of humans, yourself included.
Re: GPT-6 Astra
#846I 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…
Chollet writes he expects AGI now sooner than 2030, "given progress is happening faster than I expected." https://x.com/fchollet/status/2095607046129463577
The RL phase is the most similar mechanism I know of that comes to my mind, but I'm not sure it could be adapted to fill that gap.
My totally unsubstantiated theory is that this is the missing link towards what most humans would consider AGI. I don't see this as intractable, but it may require some substantial change in architecture.
Re: GPT-6 Astra
#847I 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…
Define novel intelligence in a way that would not exclude 95% of humans, yourself included.
Re: GPT-6 Astra
#848I'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 tone of the marketing video is a bit irritating to me as someone who has been laid off and feels cheated and fearful of AI. It shows people who seem to have very full and rich lives, and the reason they do is because they use ChatGPT. These are the people smart enough to say things like "do what needs to be done", or "change the background to make it look better"--insights like these are why they make the big buc…
Or because being a (well known) CEO is a terminal career position. It's a bit like being a top sports star. The wages are high because once they're out, they're out for good. Whatever they earned needs to last them a long time. Screwing up in the CEO position is, when boards are doing their jobs at least, pretty much the end of the road for them because nobody wants to hire an ex-CEO into a middle management or IC position.
Random example: Marissa Mayer. She did well at Google, but once she became CEO of Yahoo! and failed her career was effectively over. Since then her career history is: did a startup with a friend that produced an iPhone app for cleaning your contact lists, and later a photo sharing app. I guess she's nice and pleasant enough, so she also did the usual post-CEO thing of sitting on a few boards, NGO work and investing. It's not a bad life. But in terms of actually running things that matter again - no.
Lots of cases like that.
Who wants to sign up for a job that's high pressure, high hours, and will probably the last real job you'll ever have, and one where your success is often entirely out of your hands? Not that many. So the pay has to be good.
Re: GPT-6 Astra
#849I 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…
Define novel intelligence in a way that would not exclude 95% of humans, yourself included.
Still a hard philosophical, to know whether we have intelligence/free will, or just really complex algorithms that combine existing knowledge.
Re: GPT-6 Astra
#850I 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…
Define novel intelligence in a way that would not exclude 95% of humans, yourself included.