oh thanks lol

Primary myoblasts double on average every 4 days! So if given infinite nutrients, and you started with 1 gram of meat, it would take .... 369 days to equal the mass of earth!

Doesn't the futurism/hopium idea of building an ideal city go back to Disney? Who does more or less have feudal stronghold rights over florida?

https://en.wikipedia.org/wiki/EPCOT_(concept)

Because of these two modes of transportation, residents of EPCOT would not need cars. If a resident owned a car, it would be used "only for weekend pleasure trips."[citation needed] The streets for cars would be kept separate from the main pedestrian areas. The main roads for both cars and supply trucks would travel underneath the city core, eliminating the risk of pedestrian accidents. This was also based on the concept that Walt Disney devised for Disneyland. He did not want his guests to see behind-the-scenes activity, such as supply trucks delivering goods to the city. Like the Magic Kingdom in Walt Disney World, all supplies are discreetly delivered via tunnels.

Or The Line in Saudi Arabia.

Definely Sneer-worthy, though it's sometimes worked. Napoleon redesigned Paris, which is probably a good thing. But they are stuck with that design to this day, which is probably bad.

Real talk: a real doll with the brain of a calculator would be a substantial product improvement.

Just I think to summarize your beliefs: rationalists are wrong about a lot of things and assholes. And also the singularity (which predates yuds existence) is not in fact possible by the mechanism I outlined.

I think this is a big crux here. It's one thing if its a cult around a false belief. It's kind of a problem to sneer at a cult if the core S of it happens to be a true law of nature.

Or an analogy. I think gpt-4 is like the data from the Chicago pile. That data was enough to convince the domain experts then a nuke was going to work to the point they didn't test Fat Man, you believe not. Clearly machine generality is possible, clearly it can solve every problem you named including, with the help of humans, ordering every part off digikey and loading the pick and place and inspecting the boards and building the wire harnesses and so on.

Sure, but they were 4 function calculators a few months ago. The rate of progress seems insane.

My experience in research indicates to me that figuring shit out is hard and time consuming, and “intelligence” whatever that is has a lot less to do with it than having enough resources and luck. I’m not sure why some super smart digital mind would be able to do science much faster than humans.

That's right. Eliezer's LSD vision of the future where a smart enough AI just figures it all out with no new data is false.

However, you could...build a fuckton of robots. Have those robots do experiments for you. You decide on the experiments, probably using a procedural formula. For example you might try a million variations of wing design, or a million molecules that bind to a target protein, and so on. Humans already do this actually in those domains, this is just extending it.

1, 2 : since you claim you can't measure this even as a thought experiment, there's nothing to discuss 3. I meant complex robotic systems able to mine minerals, truck the minerals to processing plants, maintain and operate the processing plants, load the next set of trucks, the trucks go to part assembly plants, inside the plant robots unload the trucks and feed the materials into CNC machines and mill the parts and robots inspect the output and pack it and more trucks...culminating in robots assembling new robots.

It is totally fine if some human labor hours are still required, this cheapens the cost of robots by a lot.

4. This is deeply coupled to (3). If you have cheap robots, if an AI system can control a robot well enough to do the task as well as a human, obviously it's cheaper to have robots do the task than a human in most situations.

Regarding (3) : the specific mechanism would be AI that works like this:

Millions of hours of video of human workers doing tasks in the above domain + all video accessible to the AI company -> tokenized compressed description of the human actions -> llm like model. The llm like model thus is predicting "what would a human do". You then need a model to transform the what to robotic hardware that is built differently than humans, and this is called the "foundation model": you use reinforcement learning where actual or simulated robots let the AI system learn from millions of hours of practice to improve on the foundation model.

The long story short of all these tech bro terms is robotic generality - the model will be able to control a robot to do every easy or medium difficulty task, the same way it can solve every easy or medium homework problem. This is what lets you automate (3), because you don't need to do a lot of engineering work for a robot to do a million different jobs.

Multiple startups and deepmind are working on this.

I'm trying to find the twitter post where someone deepfakes eliezer's voice into saying full speed ahead on AI development, we need embodied catgirls pronto.

academic AI researchers have passed him by.

Just to be pedantic, it wasn't academic AI researchers. The current era of AI began here : https://www.npr.org/2012/06/26/155792609/a-massive-google-network-learns-to-identify

Academic AI researchers have never had the compute hardware to contribute to AI research since 2012, except some who worked at corporate giants (mostly deepmind) and went back into academia.

They are getting more hardware now, but the hardware required to be relevant and to develop a capability that commercial models don't already have keeps increasing. Table stakes are now something like 10,000 H100s, or about 250-500 million in hardware.

https://www.semianalysis.com/p/google-gemini-eats-the-world-gemini

I am not sure MIRI tried any meaningful computational experiments. They came up with unrunnable algorithms that theoretically might work but would need nearly infinite compute.

It would be lesswrongness.

Just to split where the gap is :

1. lesswrongers think powerful AGI systems that can act on their own against humans will soon exist, and will be able to escape to the internet.
2. I work in AI and think powerful general AI systems (not necessarily the same as AGI) will exist soon and be powerful, but if built well will be unable to act against humans without orders, and unable to escape or do many of the things lesswrongers claim.
3. You believe AGI of any flavor is a very long way away, beyond your remaining lifespan?

Hi David. Reason I dropped by was the whole concept of knowing the distant future with too much certainty seemed like a deep flaw, and I have noticed lesswrong itself is full of nothing but 'cultist' AI doomers. Everyone kinda parrots a narrow range of conclusions, mainly on the imminent AGI killing everyone, and this, ironically, doesn't seem very rational...

I actually work on the architecture for current production AI systems and whenever I mention approaches that do work fine and suggest we could control more powerful AI this way, I get downvoted. So I was trying to differentiate between:

A. This is a club of smart people, even smarter than lesswrongers who can't see the flaws!

B. This is a club of well, the reason I called it boomers was I felt that the current news and AI papers make each of the questions I asked a reasonable and conservative outcome. For example posters here are saying for (1), "no it won't do 25% of the jobs". That was not the question, it was 25% of the tasks. Since for example Copilot already writes about 25% of my code, and GPT-4 helps me with emails to my boss, from my perspective this is reasonable. The rest of the questions build on (1).