It’s unrecommended because it’s badly written, not because it doesn’t have worthwhile content. The glial cells serve a purpose such that the brain will not produce identical output if you exclude them from the model, and we still don’t have a good understanding of how the interaction works; until recently, we haven’t even paid much attention to studying it.
Most of the remaining missing knowledge is about the higher level connection architecture between regions and interactions with the thalamus, hippocampus and cerebellum.
We don’t necessarily need to understand all of this to build an AGI with a cortex that thinks somewhat like us. We also have general AI theory to guide us.
General AI theory that has so far failed to produce anything close to a general AI.
Whether or not it is a good idea is one question, but it absolutely is a credible idea. In fact, it is the most credible idea for building AGI, but the analysis for that is longer and more complex. I’ve written some about that on my site, I’m going to write up an intro summary of the state of brain-AGI research and why it’s the promising path.
You’ve already posted arguments to that effect on this site, note that they have tended to be disputed and downvoted.
We don’t necessarily need to understand all of this to build an AGI with a cortex that thinks somewhat like us. We also have general AI theory to guide us.
General AI theory that has so far failed to produce anything close to a general AI.
We don’t yet have economical computer systems that have 10^14 memory capacities and the ability to perform 100-1000 memory/ops on all the memory every second. The world’s largest GPU supercomputers are getting there, but doing it the naive way might take thousands of GPUs, and even then the interconnect is expensive.
We understood the feasibility and general design space of nuclear weapons and space travel long before we had the detailed knowledge and industrial capacity to build such technologies.
We understood the feasibility and general design space of nuclear weapons and space travel long before we had the detailed knowledge and industrial capacity to build such technologies.
11 years (Szilard’s patent in 1934 to Trinity in 1945) is ‘long before’?
11 years (Szilard’s patent in 1934 to Trinity in 1945) is ‘long before’?
Ok, so space travel may be a better example, depending on how far we trace back the idea’s origins. But I do think that we could develop AGI in around a decade if we made an Apollo project out of it (14 year program costing around $170 billion in 2005 dollars).
Perhaps, but as Eliezer has gone to some lengths to point out, the great majority of those working on AGI simply have no concept of how difficult the problem is, of the magnitude of the gulf between their knowledge and what they’d need to solve the problem. And solving some aspects of the problem without solving others can be extraordinarily dangerous. I think you’re handwaving away issues that are dramatically more problematic than you give them credit for.
Perhaps, but as Eliezer has gone to some lengths to point out, the great majority of those working on AGI simply have no concept of how difficult the problem is, of the magnitude of the gulf between their knowledge and what they’d need to solve the problem.
There is an observational bias involved here. If you do look at the problem of AGI and come to understand it you realize just how difficult it is and you are likely to move to work on a less ambitious narrow-AI precursor. This leaves a much smaller remainder trying to work on AGI, including the bunch that doesn’t understand the difficulty.
I think you’re handwaving away issues that are dramatically more problematic than you give them credit for.
If you are talking about the technical issues, I think 1-100 billion and 5-20 years is a good cost estimate.
As for the danger issues, yes of course this will be the most powerful and thus most dangerous invention we ever make. The last, really.
It’s unrecommended because it’s badly written, not because it doesn’t have worthwhile content. The glial cells serve a purpose such that the brain will not produce identical output if you exclude them from the model, and we still don’t have a good understanding of how the interaction works; until recently, we haven’t even paid much attention to studying it.
General AI theory that has so far failed to produce anything close to a general AI.
You’ve already posted arguments to that effect on this site, note that they have tended to be disputed and downvoted.
We don’t yet have economical computer systems that have 10^14 memory capacities and the ability to perform 100-1000 memory/ops on all the memory every second. The world’s largest GPU supercomputers are getting there, but doing it the naive way might take thousands of GPUs, and even then the interconnect is expensive.
We understood the feasibility and general design space of nuclear weapons and space travel long before we had the detailed knowledge and industrial capacity to build such technologies.
11 years (Szilard’s patent in 1934 to Trinity in 1945) is ‘long before’?
Ok, so space travel may be a better example, depending on how far we trace back the idea’s origins. But I do think that we could develop AGI in around a decade if we made an Apollo project out of it (14 year program costing around $170 billion in 2005 dollars).
Perhaps, but as Eliezer has gone to some lengths to point out, the great majority of those working on AGI simply have no concept of how difficult the problem is, of the magnitude of the gulf between their knowledge and what they’d need to solve the problem. And solving some aspects of the problem without solving others can be extraordinarily dangerous. I think you’re handwaving away issues that are dramatically more problematic than you give them credit for.
There is an observational bias involved here. If you do look at the problem of AGI and come to understand it you realize just how difficult it is and you are likely to move to work on a less ambitious narrow-AI precursor. This leaves a much smaller remainder trying to work on AGI, including the bunch that doesn’t understand the difficulty.
If you are talking about the technical issues, I think 1-100 billion and 5-20 years is a good cost estimate.
As for the danger issues, yes of course this will be the most powerful and thus most dangerous invention we ever make. The last, really.