The main assumption of techno-optimism is that a large enough computer can do anything people can do and it can do it better. The goal of techno-optimism is to create a mechanical god that will rule the planet and scaling LLMs is a stepping stone to that goal.
I, of course, already know how to do all this for a mere $80B.
I think I can do it far, far cheaper than that... and I've been talking about it, in public, for over a decade.[1] I could easily be wrong, of course. It really all depends on how much power a 4x4 LUT and 4 bit latch Latch Leak, and how much energy it takes to clock data through them for a cycle, and how fast they can be cycled. If the number are good, this thing will be amazingly cool. I can't find good numbers anywhere.
If you've made chips with latches and LUTS, any performance data you can share, no matter how old, would be helpful
It's an idea that's been bouncing around in my head since reading George Gilder's call to waste transistors. Imagine the worst possible FPGA, no routing hardware, and slow it down even more with a latch on every single LUT. Optimize it slightly, by making cells with 4 bits in, 4 bits out (64 bits of programming per cell), with the cells clocked in 2 phases, like the colors of a chess board. This means that each white cell has static inputs from the black cells.... and is thus fully deterministic, and easy to reason about. The complement happens on the other phase. Together, it becomes turning complete.
The thing is, it does computing with NO delays between compute and memory. All the memory is effectively transferred to compute every clock cycle. The latency sucks because you'll take n/2 cycles to get data across an N*N grid. However, you'll get an answer every clock cycle after that.
Imagine a million GPT-4 tokens/second.... not related to each other, of course, but parallel streams, interleaved as the data streams across the chips.
Imagine a bad cell.... you can detect it, and route around it. Yields don't have to be 100%.
The extreme downside is that tools for programming this thing don't exist. VHDL, etc... aren't appropriate. I'm going to have to build them. I've been stuck in analysis paralysis, but I've decided to try to get Advent of Code done using my bitgrid simulator. I hope to be done before it starts again next December. ;-)
I think $80B is very cheap because the outcome is going to be a technological utopia. Honestly, I think my price is a bargain deal for the inhabitants of Earth.
> I think $80B is very cheap because the outcome is going to be a technological utopia.
I wish I shared your optimism. However I've seen no evidence that society is prepared to deal with a large swath of jobs being obsoleted by AI. I have no doubt that the "haves" will call it a technological utopia, but I strongly suspect the "have nots" will be larger than ever.
In my architecture everyone is treated equally like an idiot so there are no haves and have not because the machine god treats all people the same and provides for all their needs within the "panoptic computronium cathedral"™.
They don't. They say things like "infinite resources for everyone" and "compute/electricity too cheap to meter" and so on and so forth. I have distilled the techno-optimist manifesto down to what it actually looks like in reality, i.e. a global panopticon that controls everything with algorithms.
Per usual, I can build this technological panopticon/utopia for a bargain price of $80B. Some people think it can be done for cheaper but they haven't spent as much time as I have on this problem. I have the architecture ready to go, all I need is the GPUs, cameras, microphones, speakers, and wireless data network. The software is the easy part but the panoptic infrastructure is what requires the most capital. The software/brain can be done for maybe $2B but it needs eyes, ears, and a mouth to actually be useful.
The second stage is building up the actuators to bypass people but once the panopticon is ready it won't be hard to build up the robot factories to enact the will of AGI directly via robots acting on the environment.
I, of course, already know how to do all this for a mere $80B.