61–70 of 447 posts
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Not really. Nobody expected China to produce as much solar power as it does now. What makes you think we know how much renewable energy we will produce in 2040?
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That means a ton of new power generation will need to come online. Last year > 85% of new utility scale power facilities was renewable in the US, solar is finally cheaper than natural gas.
The most likely outcome is that the new power demand will drive this cost down even further.
> It is possible that we will have superintelligence in a few thousand days (!) "a few thousand days" is such a funny and fascinating way to say "about a decade" Superficially, reframing it as "days" not "years" is a classic marketing psychology trick, i.e. 99 cents versus a dollar, but I think the more interesting thing is just the way it defamiliarizes the span. A decade means something, but "a few thousand days" f…
"humanity discovered an algorithm that could really, truly learn any distribution of data (or really, the underlying “rules” that produce any distribution of data)..." This statement is manifestly untrue. Neural networks are useful, many hidden layers is useful, all of these architectures are useful, but the idea that they can learn anything, is based less on empirical results and more on what Sam Altman needs to con…
The entire vocabulary around machine learning is and always has been really weird. We don’t personify database interactions the same way we personify setting weights in a neural network.
I like Sam's philosophy on this and I generally agree with him. However, I do not like how all the wealthy AI people are hand-waving the massive labor market shift in the coming years. > As one example, we expect that this technology can cause a significant change in labor markets (good and bad) in the coming years, but most jobs will change more slowly than most people think, and I have no fear that we’ll run out of…
For this reason I read Andrew Yang’s “The War on Normal People”. Besides UBI and “social credits”, I don’t see him offer that many other solutions to this problem. UBI also still needs to be proven as far as I’m aware. When o1 was released, I ran an internal eval and saw it plainly outperforming our highly educated colleagues. I had goosebumps, and haven’t been able to sleep well for days. This will dramatically impa…
https://intelligence.org/files/IEM.pdf
Welcome to the anxiety party, it sucks in here. As someone who's been working on AI theory full time for ~1 year, I desperately wish we could go back to the days of my faraway youth (5 years ago) before intuition was cracked on accident by spellcheck algorithms. I agree with him that it holds the key to massive prosperity, but selfishly, it's gonna upend my life and the lives of everyone I love. Already has for me, as I grapple with how to (ethically) pay rent while spending all day lighting the Warning Beacons of Gondor...
The only real answer, IMHO, is to vote for political systems that put control of society (and AI) in the hands of the public. Call it socialism, call it Georgism, call it anarcho-free-market-space-communism, call it whatever you want; there's no way that "a tiny number of people have immense inherited power" (capitalism) and "people fundamentally understand themselves as members of a tribe put in opposition to all other tribes by default" (nationalism) mesh well with an intelligence explosion.
Here's to hoping the haters are right, and we all turn out to be wrong! I'll be thrilled if Sam Altman is just a rich company leader in 10 years, and intuitive algorithms are still confined to direct usage (chatbots).
For example, I’m designing and 3D printing custom LED diffuser channels from TPU filament. My first attempt was terrible, because I didn’t have an intuition for how light propagates through a material.
After a bit of chatting with ChatGPT, I had an understanding and some direction of where to go.
To actually approach the problem properly I decided to run some Monte Carlo light transport simulations against an .obj of my diffuser exported from Fusion 360.
The problem was, the software I’m using only supports directional lights with uniform intensity, while the LEDs I’m using have a graph in their datasheet showing light intensity per degree away from orthogonal to the LED SMD component.
I copy pasted the directional light implementation from the light transport library as well as the light-intensity-by-degree chat from the LED datasheet and asked Claude to write code to write a light source that samples photons from a disc of size x with the probability of emission by angle governed by the chat from the datasheet.
A few iterations later and I had a working simulation which I then verified back against the datasheet chart.
Without AI this would have been a long long process of brushing up on probability, vector math, manually transcribing the chart.
Instead in like 10 minutes I had working code and the light intensity of the simulation against my mesh matched what I was seeing in real life with a 3D printed part.
"humanity discovered an algorithm that could really, truly learn any distribution of data (or really, the underlying “rules” that produce any distribution of data)..." This statement is manifestly untrue. Neural networks are useful, many hidden layers is useful, all of these architectures are useful, but the idea that they can learn anything, is based less on empirical results and more on what Sam Altman needs to con…
The intention of this sama post is as you said, it's to build narrative so he can raise his trillion from the Arab world or other problematic sources.
In pseudocode, this is Sam Altman:
while(alive) { RaiseCapital() }
>We can say a lot of things about what may happen next, but the main one is that AI is going to get better with scale. Could anyone elaborate on this? Further down he talks about the necessity of bringing the cost of computing down. Is that really the bottleneck?
> It is possible that we will have superintelligence in a few thousand days (!) "a few thousand days" is such a funny and fascinating way to say "about a decade" Superficially, reframing it as "days" not "years" is a classic marketing psychology trick, i.e. 99 cents versus a dollar, but I think the more interesting thing is just the way it defamiliarizes the span. A decade means something, but "a few thousand days" f…
Probably because we all know "a decade" means maybe never. They've said the same thing about fusion for 5 decades.