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> not particularly convincing It wasn't meant to "convince." It's an assertion. So, it's going to land humans on Mars in the 2020s, too? How about cheap nucle

> not particularly convincing It wasn't meant to "convince." It's an assertion. So, it's going to land humans on Mars in the 2020s, too? How about cheap nuclear fusion? Some problems are amenable to AI approaches, including many that were thought not to be. Some are not.

lern_too_spel 4y ago
Machine learning is already contributing to figuring out how to get energy from a fusion reactor. https://spectrum.ieee.org/can-ai-make-a-better-fusion-reactor https://spectrum.ieee.org/can-ai-make-a-better-fusion-reacto... and https://www.deepmind.com/blog/accelerating-fusion-science-through-learned-plasma-control https://www.deepmind.com/blog/accelerating-fusion-science-th...
- AlbertCory 4y ago
  You're changing the question. OP said "they've crushed multiple problems that were viewed as being decades away in just a few years." "contributing to figuring out how" is not the same as "crushing the problem." It's helpful, of course.
  - lern_too_spel 4y ago
    Containment is the hardest problem with fusion reactors, and ML directly addresses it. (Obviously, ML doesn't directly solve fusion.) Now it's likely that there will be a commercially viable fusion reactor in the 2030s, whereas it used to be the case that a proof of concept was perpetually 30 years away.
qualudeheart 4y ago
We could have landed on Mars already if we had funding. There’s no incentive for the state to fund it so Musk has to do it while still relying on government funding for other SpaceX projects. If we get the National Security elites on board we’ll be there so fast it’ll make your head spin. We could have AGI 2-5 years sooner than we otherwise will (2030) if the government wasn’t run by geriatric humanities majors. These problems are mosyly downsyream from money, lots of it, and you need Manhattan project scale budgets for them. AGI and fusion also require some theoretical breakthroughs but Mars? Mars doesn’t. Making it livable is hard but just landing there just means scaling up the moon landing.
- AlbertCory 4y ago
  So... AI can solve every problem, but not that one, because reasons.
deleted 4y ago
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lern_too_spel 4y ago

Machine learning is already contributing to figuring out how to get energy from a fusion reactor. https://spectrum.ieee.org/can-ai-make-a-better-fusion-reactor https://spectrum.ieee.org/can-ai-make-a-better-fusion-reacto... and https://www.deepmind.com/blog/accelerating-fusion-science-through-learned-plasma-control https://www.deepmind.com/blog/accelerating-fusion-science-th...

AlbertCory 4y ago
You're changing the question. OP said "they've crushed multiple problems that were viewed as being decades away in just a few years." "contributing to figuring out how" is not the same as "crushing the problem." It's helpful, of course.
- lern_too_spel 4y ago
  Containment is the hardest problem with fusion reactors, and ML directly addresses it. (Obviously, ML doesn't directly solve fusion.) Now it's likely that there will be a commercially viable fusion reactor in the 2030s, whereas it used to be the case that a proof of concept was perpetually 30 years away.

qualudeheart 4y ago

We could have landed on Mars already if we had funding. There’s no incentive for the state to fund it so Musk has to do it while still relying on government funding for other SpaceX projects. If we get the National Security elites on board we’ll be there so fast it’ll make your head spin. We could have AGI 2-5 years sooner than we otherwise will (2030) if the government wasn’t run by geriatric humanities majors. These problems are mosyly downsyream from money, lots of it, and you need Manhattan project scale budgets for them. AGI and fusion also require some theoretical breakthroughs but Mars? Mars doesn’t. Making it livable is hard but just landing there just means scaling up the moon landing.

AlbertCory 4y ago
So... AI can solve every problem, but not that one, because reasons.

deleted 4y ago

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