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Can you explain wherein it is asserted directly or indirectly that using a neural network serves to repeal the laws of computer science?

astrange 3y ago
I think the article is claiming that other people think neural networks are Turing slash human complete, which they aren't, for instance because they're not capable of using unbounded external storage slash "memory", and because they only execute in finite time. However the example at the top of the page isn't quite right. You could implement something like this. An LLM's memory only exists in its context window of its own prior output[0], but you could train it to tag its "chain of thoughts" and just not show them - now it looks like it's "thinking". [0] this is not exactly true because you could also implement non-greedy search, ie back up and start again if you think it's gone down the wrong path. Now it doesn't execute in finite time either.
- cameronh90 3y ago
  There are approaches to add "memory" to LLMs. Either the memory can be used to find relevant information and append it to the prompt - I believe LangChain can do this - or the LLM can be used as a controller to retrieve and store information in a database, for example by using ChatGPT's tool integration. I don't think it works amazingly, but purely technically you could argue that gives it access to unbounded external storage. I don't think an LLM can be considered as capable of becoming an AGI on its own with the current architecture, but potentially combined with other techniques, models and supervision, I can see the potential for it to evolve in that direction. Frankly, for what LLMs are right now, they're _surprisingly_ effective. If you chopped the Broca's area out of my brain and hooked it up to an API, I suspect it wouldn't do half as good of a job.
PaulHoule 3y ago
Look at the average “Ask HN” on the subject. Or look at the kind of speculations that followers of Eliezer Yudkowsky make in the name of big-R Reason. (thank God we hear about him about as often as we hear about Threads these days) To be fair a lot of people speculating about AI aren’t aware of the foundations of computer science, but some of them are vaguely aware and just forgot. Actually LLMs do have a way to break some of those constraints, in their own way, in that those constraints don’t apply to systems that don‘t always get the right answer. You can sort a list in O(1) some of the time but not all of the time.

astrange 3y ago

I think the article is claiming that other people think neural networks are Turing slash human complete, which they aren't, for instance because they're not capable of using unbounded external storage slash "memory", and because they only execute in finite time. However the example at the top of the page isn't quite right. You could implement something like this. An LLM's memory only exists in its context window of its own prior output[0], but you could train it to tag its "chain of thoughts" and just not show them - now it looks like it's "thinking". [0] this is not exactly true because you could also implement non-greedy search, ie back up and start again if you think it's gone down the wrong path. Now it doesn't execute in finite time either.

cameronh90 3y ago
There are approaches to add "memory" to LLMs. Either the memory can be used to find relevant information and append it to the prompt - I believe LangChain can do this - or the LLM can be used as a controller to retrieve and store information in a database, for example by using ChatGPT's tool integration. I don't think it works amazingly, but purely technically you could argue that gives it access to unbounded external storage. I don't think an LLM can be considered as capable of becoming an AGI on its own with the current architecture, but potentially combined with other techniques, models and supervision, I can see the potential for it to evolve in that direction. Frankly, for what LLMs are right now, they're _surprisingly_ effective. If you chopped the Broca's area out of my brain and hooked it up to an API, I suspect it wouldn't do half as good of a job.

PaulHoule 3y ago

Look at the average “Ask HN” on the subject. Or look at the kind of speculations that followers of Eliezer Yudkowsky make in the name of big-R Reason. (thank God we hear about him about as often as we hear about Threads these days) To be fair a lot of people speculating about AI aren’t aware of the foundations of computer science, but some of them are vaguely aware and just forgot. Actually LLMs do have a way to break some of those constraints, in their own way, in that those constraints don’t apply to systems that don‘t always get the right answer. You can sort a list in O(1) some of the time but not all of the time.