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First, you have to define "AGI". Next, you have to have a clear path to reaching it. Then, you have to have the resources to actually walk that path. Only wi

by danaris 7mo ago

First, you have to define "AGI". Next, you have to have a clear path to reaching it. Then, you have to have the resources to actually walk that path. Only with all three of those can you make any credible claim that AGI is near. As it stands, we have none of them—and the lack of the second is the most damning. It's very, very clear at this point that just scaling up the existing LLMs is not going to reach some critical mass and result in AGI, like the serendipitous sapience of Mycroft in The Moon Is A Harsh Mistress. Given that, any path to AGI necessarily includes some new breakthrough on it (or more than one). And by their essential nature, breakthroughs are not something you can predict or schedule. Indeed, you cannot even be guaranteed that they will ever happen. (It is likely, assuming that it is physically possible to build AGI, that we will figure out how at some point...but not guaranteed.)

tim333 7mo ago
On the other hand approx human brain equivalence in computers has been predicted fairly accurately since about 1990 based on Moore's law type projections - mid 2020s by Moravec, 2029 by Kurzweil. The underlying assumption is once the hardware is widely available, hackers will hack something together.
- danaris 7mo ago
  But Moore's Law went out the window over a decade ago. Oh, sure, we're still getting things smaller and faster—but nowhere near the same rate we were before. Nowadays most (not all, but most) of the advances we're getting are in more and better parallelisation, rather than faster performance on each core. And my (rough, limited) understanding is that based on much more recent projections, it would take several orders of magnitude more computing power to genuinely simulate a human brain than what we have.
  - tim333 7mo ago
    The main Moore's law like metric they track is compute in instructions per second, per dollar. That's kept on a fairly steady exponential for a century or so and doesn't seem to be slowing. (https://www.bvp.com/assets/uploads/2024/03/price-performance-slide-ray-kurzweil-atlas-image.jpg https://www.bvp.com/assets/uploads/2024/03/price-performance...) We are probably not near simulating a brain but near enough for similar functionality. Moravec estimated it by looking at the retina which was fairly well understood and seeing how much compute was needed for similar object detection etc. in his robots.

by danaris 7mo ago

tim333 7mo ago

On the other hand approx human brain equivalence in computers has been predicted fairly accurately since about 1990 based on Moore's law type projections - mid 2020s by Moravec, 2029 by Kurzweil. The underlying assumption is once the hardware is widely available, hackers will hack something together.

danaris 7mo ago
But Moore's Law went out the window over a decade ago. Oh, sure, we're still getting things smaller and faster—but nowhere near the same rate we were before. Nowadays most (not all, but most) of the advances we're getting are in more and better parallelisation, rather than faster performance on each core. And my (rough, limited) understanding is that based on much more recent projections, it would take several orders of magnitude more computing power to genuinely simulate a human brain than what we have.
- tim333 7mo ago
  The main Moore's law like metric they track is compute in instructions per second, per dollar. That's kept on a fairly steady exponential for a century or so and doesn't seem to be slowing. (https://www.bvp.com/assets/uploads/2024/03/price-performance-slide-ray-kurzweil-atlas-image.jpg https://www.bvp.com/assets/uploads/2024/03/price-performance...) We are probably not near simulating a brain but near enough for similar functionality. Moravec estimated it by looking at the retina which was fairly well understood and seeing how much compute was needed for similar object detection etc. in his robots.