Earlier quoted context omitted.
Agreed, Yud does seem to have been right about the course things will take but I'm not confident he actually has any solutions to the problem to offer
His solution is a global regulatory regime to ban new large training runs. The tools required to accomplish this are, IMO, out of the question but I will give Yud credit for being honest about them while others who share his viewpoint try to hide the ball.
Language models can explain neurons in language models
461–470 of 497 posts
Re: Language models can explain neurons in language models
#462Re: Language models can explain neurons in language models
#463Earlier quoted context omitted.
If you spent any time with GPT-4 it should be evident.
Still a while to go. I think there's at least a couple of algorithmic changes needed before we move to a system that says "You have the world's best god-like AI and you're asking me for poems. Stop wasting my time because we've got work to do. Here's what I want YOU to do."
Re: Language models can explain neurons in language models
#464Earlier quoted context omitted.
I'm not "ignoring" them at all. I'm saying that they point to interesting questions that are not answered. > The split-brain experiments are notable because the lab experiments SUGGEST the lack of communication between two hemispheres and a split conscious however this is paradoxical with everyday experience of these patients, far from providing evidence for anything. It is not "paradoxical" but yes it does conflict…
I'm arguing against the strength of your statements based on methodologically unsound experiments that do not "very very clearly indicate" anything beyond pose a few questions for which there are several different hypothetical answers. All of which have zero evidence behind them. Similarly, the initial comment of 'does the brain know what the brain is doing. The answer so far does not seem to be "yes."' is misleading…
From your own linked article: "In short, callosotomy leads to a broad breakdown of functional integration ranging from perception to attention."
If the dopamine reward system is the full answer, then what explains drug addicts anguishing about their addiction while simultaneously actively seeking out their next hit? What part of the brain is producing the anguish if the whole behavior is conclusively described by the dopamine reward system?
Re: Language models can explain neurons in language models
#465Of note: "... our technique works poorly for larger models, possibly because later layers are harder to explain." And even for GPT-2, which is what they used for the paper: "... the vast majority of our explanations score poorly ..." Which is to say, we still have no clue as to what's going on inside GPT-4 or even GPT-3, which I think is the question many want an answer to. This may be the first step towards that, bu…
Funny that we never quite understood how intelligence worked and yet it appears that we're pretty damn close to recreating it - still without knowing how it works. I wonder how often this happens in the universe...
In human brains, language is only a way to communicate thoughts in concept form, though we also seem to use language to communicate abstract thoughts to ourselves to break them apart/down in a way (imo).
I'd love to see someone train a model on the level of GPT4 to generate abstract thoughts/ideas based on input/context and then pair this model with GPT4 co-operatively and continue to train, such that the flow of abstract ideas is parsed by GPT. But like...how do you even train a model that operates on abstract ideas, there doesn't seem to be any way to do this.
Re: Language models can explain neurons in language models
#466Earlier quoted context omitted.
Sorry, my english is not the best and I don't think there is a word for the thing I'm trying to explain. Meaning of 'consciousness' is too messy. I know brain is a neural network. I just don't understand how cold, hard matter can result in this experience of consciousness we are living right now. The experience. Me. You. Perceiving. Right now. I'm not talking about the relation between the brain and our conscious exp…
You are referring to qualia [1]: feeling something as-is , subjectively. I had similar metaphysics just a few years ago, but in the end, it's just that: bad metaphysics. And it's not even your or my fault: with 2,400+ years of bad metaphysics it's almost only luck to be able to pierce the veil into the metaphysics of tomorrow. The main point is that with the tremendous discoveries of people such as Church/Turing (mat…
> We looked insanely deep into the brain [4], there is no magic going on.
Indeed all computation and input collection and such happen in the brain. I just don't understand how I can experience anything if I'm composed only of matter. How come there happens to be a mind? Indeed the electrochemical charges from visual receptors in the eye will be transmitted and computed and memory and dopamine and all the neurons will fire regardless of whether I'm only matter or not. But how can the experiencing consciousness, 'me' arise from matter?
> only a simulation can be conscious, not physical systems
This is what I'm talking about, only that I don't see why simulations are not physical systems.
> yes, you are electrochemical charges, we all are, what else could we be?
It's nonsensical and unscientific to completely rule out the possibility that we can be something else as well, especially when we can't study it directly, like in the example of soul.
Re: Language models can explain neurons in language models
#467Earlier quoted context omitted.
> But how is any information that isn't testable trusted? I'm open to the idea ChatGPT is as credible as experts in the dismal sciences given that information cannot be proven or falsified and legitimacy is assigned by stringing together words that "makes sense". I understand that around the 1980s-ish, the dream was that people could express knowledge in something like Prolog, including the test-case, which can then…
I bet GPT is really good at prolog, that would be interesting to explore. "Answer this question in the form of a testable prolog program"
Re: Language models can explain neurons in language models
#468Earlier quoted context omitted.
I'm arguing against the strength of your statements based on methodologically unsound experiments that do not "very very clearly indicate" anything beyond pose a few questions for which there are several different hypothetical answers. All of which have zero evidence behind them. Similarly, the initial comment of 'does the brain know what the brain is doing. The answer so far does not seem to be "yes."' is misleading…
The split brain experiments clearly indicate exactly what I said they clearly indicate. To refresh: "that different parts of the brain can independently conduct behavior and gain knowledge independently of other parts". From your own linked article: "In short, callosotomy leads to a broad breakdown of functional integration ranging from perception to attention." If the dopamine reward system is the full answer, then…
Still not sure what the contradiction is, is it regret now? Cause that isn’t contradictory.
It’s pretty simple, drugs feel really good when you take them so a single consciousness prioritizes that feeling over long term interests. When one is not taking them and facing the consequences of those decisions they feel bad. To make the bad feelings go away one takes more drugs and the cycle repeats.
Re: Language models can explain neurons in language models
#469Earlier quoted context omitted.
If it performs a computation, it is by definition running some algorithm regardless of how it's implemented in hardware / wetware. How is it a stretch? The only way our brains could be not algorithmic is if something like soul is a real thing that actually drives our intelligence.
Why? Rain is not algorithmic, clouds are not algorithmic, waves in the sea are not algorithmic, yet they are entirely physical processes that have nothing to do with souls.
Re: Language models can explain neurons in language models
#470Earlier quoted context omitted.
LLM's are not a "smart human being." They are predictive statistical models capable of producing results based on training data. LLM's do not think. LLM's are algorithms.
Your brain is also basically an algorithm that produces results based on training data. It's just a much more complicated and flexible one.