Language models can explain neurons in language models • Hacker News Board

Re: Language models can explain neurons in language models

#471

Post by hypertele-Xii » Fri, May 12, 2023, 5:09 AM UTC

int_19h wrote: post #448

hypertele-Xii wrote: post #396

Earlier quoted context omitted.

If by "survive" you mean "age and die leaving nothing behind", then sure. But the same is true for an ant.

No, it is not true for an ant. A solitary worker ant will not die from old age. Many species will literally starve to death within a few days because they cannot properly digest their food without trophallaxis.

You're right, it seems ants need each other to digest food, though scientists don't yet know why exactly.

From the New Yorker [1]:

> The researchers aren’t yet sure exactly what causes the digestive slowdown. Maybe it’s stress. Maybe the fluid that ants exchange when they share food stimulates digestion. Maybe they die still looking for a relative to break bread with.

[1] https://www.newyorker.com/tech/annals-of-technology/lonely-a...

Re: Language models can explain neurons in language models

#472

Post by ly3xqhl8g9 » Fri, May 12, 2023, 7:43 AM UTC

Aerbil313 wrote: post #466

ly3xqhl8g9 wrote: post #446

Earlier quoted context omitted.

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…

I did not mean qualia, I knew qualia. I meant that my experience is not matter. Matter is matter and charges are charges, my experience right now is neither. Your perception, the act of you experiencing life right now is not matter. > 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 exper…

Simulations are physical systems just as much as running a "Hello World" program on your computer is a physical system: somewhere some transistors flip, but they are not relevant for the level of description we are interested when running the program, the program output, as simple or complex as it could be. Somewhere in the brain some molecules do "stuff", as a result of the "stuff" the brain sustains one agent, or more [1]. How exactly, in an engineering sense, the agent is constructed is yet to be discovered, hopefully we are only a few years, a few decades, away from building synthetic agents.

Sure, we have about 2,700 years of tradition speaking of souls (considering the major religions: Christianity, Islam, Buddhism, Hinduism, and Judaism). Where did those 2,700 years got us? Has any religion been able to build a conscious agent starting from basic materials (whatever they consider basic, pixie dust if they will)? Have all this years speaking of souls managed to achieve something meaningful, even as a side effect, that actually improves the quality of life? I'm talking hay [2], indoor plumbing, hook-and-loop fasteners, ibuprofen, GPS, voltmeters, extreme ultraviolet lithography, things that you and I can use and rely on daily. I have read pretty much all the major texts of the major traditions, from Mahābhārata to Summa Theologiae, call it intellectual curiosity. If not for the "bragging rights" to say that I know what filioque or bodhipakkhiyādhammā means, I would regret it, wasted time and pointless eye strain. So no, it's not nonsensical and unscientific to rule out a not even hypothesis such as the "soul" after 2,700+ years without any kind of results and absolute incompatibility with the way we actually interact with the world, scientifically or not: photons, atoms, electromagnetic fields and the like.

[1] https://en.wikipedia.org/wiki/Dissociative_identity_disorder

[2] "The technologies which have had the most profound effects on human life are usually simple. A good example of a simple technology with profound historical consequences is hay.", https://quotepark.com/quotes/1924489-freeman-dyson-like-many...

Re: Language models can explain neurons in language models

#473

Post by afarviral » Fri, May 12, 2023, 1:05 PM UTC

poulpy123 wrote: post #362

p1esk wrote: post #357

Earlier quoted context omitted.

Do you have any example of how it cannot reason?

It's a neural network. Neural network are not symbolic AI and are not designed to reason

Its not designed to reason but it does reason. Thats whats so impressive about it; emmergent properties like factuality and reasoning.

Re: Language models can explain neurons in language models

#474

Post by afarviral » Fri, May 12, 2023, 1:11 PM UTC

p1esk wrote: post #285

Culonavirus wrote: post #280

Earlier quoted context omitted.

Its vast limitations in anything reasoning-based are indeed evident.

GPT-4 is better at reasoning than 90% of humans. At least. I won't be surprised if GPT-5 is better than 100% of humans. I'm saying this in complete seriousness.

I intuit the same given the jumps we've seen from gpt 3.5 fo 4. The next jump will feature considerably more general intelegence than any one human being, though I think it will have certain weaknesses.

Re: Language models can explain neurons in language models

#475

Post by YeGoblynQueenne » Fri, May 12, 2023, 3:02 PM UTC

int_19h wrote: post #469

YeGoblynQueenne wrote: post #456

Earlier quoted context omitted.

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.

None of these are computational processes, unlike intelligence. Unless you're trying to argue that intelligence isn't, either?

Heaven forbid. I'd go to jail for such a blasphemous transgression of common law, wouldn't I? Thank you kind stranger for reminding me of the legislation.

Re: Language models can explain neurons in language models

#476

Post by xcv123 » Sat, May 13, 2023, 3:10 AM UTC

YeGoblynQueenne wrote: post #458

p1esk wrote: post #319

Earlier quoted context omitted.

OK, you have a point. But, if you replace "GPT-4" with "an average human" in your response - it still makes sense.

When you ask a question of "an average human", they will reply with a sentence answering your question, or maybe asking for clarifications, etc. When you ask a question of GPT-4, it generates one token. One. Token. One token, that is not an answer to your question, that is not asking for clarifications, that is not trying to reason about your question, or how to answer it, because it's just one token. One. Token. For…

Prompt: What is the sieve of Eratosthenes? Speak in chicken

Answer from GPT-4:

Sure, here's the explanation of the sieve of Eratosthenes explained in a simplified "chicken" style:

Imagine you are a chicken. You have lots of chicken friends. Let's say there are 100 of you. Now, you all stand in a line. Each chicken is numbered, from 2 up to 100. Chicken number 1 decided to stay at home because he's a bit special in this game.

Chicken number 2, a very important chicken, starts to crow. Every chicken in line after number 2 who has a number that is a multiple of 2 (so every second chicken from chicken number 2) gets scared and runs away.

Then chicken number 3, the next chicken in line who didn't run away, starts to crow. Every chicken in line after number 3 who has a number that is a multiple of 3 (so every third chicken from chicken number 3) also gets scared and runs away.

This continues with the next chicken in line who didn't run away, and so on. Each chicken scares away all the chickens whose numbers are multiples of their own number.

At the end, the chickens that are still in line, who didn't run away, are very special chickens. Their numbers are what humans call prime numbers. These are numbers that can only be divided by 1 and themselves.

This whole chicken game is like the Sieve of Eratosthenes. It's a way that humans have figured out to find prime numbers. You start from the lowest number (2) and eliminate multiples of each number. The numbers that are left over are the primes.

And that, in chicken speak, is the Sieve of Eratosthenes!

Re: Language models can explain neurons in language models

#477

Post by xcv123 » Sat, May 13, 2023, 3:22 AM UTC

YeGoblynQueenne wrote: post #458

p1esk wrote: post #319

Earlier quoted context omitted.

OK, you have a point. But, if you replace "GPT-4" with "an average human" in your response - it still makes sense.

When you ask a question of "an average human", they will reply with a sentence answering your question, or maybe asking for clarifications, etc. When you ask a question of GPT-4, it generates one token. One. Token. One token, that is not an answer to your question, that is not asking for clarifications, that is not trying to reason about your question, or how to answer it, because it's just one token. One. Token. For…

> There's no thinking, no reasoning, no calculation, no logic, no deduction, no intelligence, no anything. It's only token, token, token.

False. The neural network inside the transformer LLM contains a hierarchical semantic model, and has inferred some rules of reasoning from the training set. It can apply those rules to new input.

There are semantic layers above the "token token tokens".

Explore them here: https://openaipublic.blob.core.windows.net/neuron-explainer/...

Re: Language models can explain neurons in language models

#478

Post by [deleted] » Sat, May 13, 2023, 9:03 AM UTC

xcv123 wrote: post #477

YeGoblynQueenne wrote: post #458

Earlier quoted context omitted.

When you ask a question of "an average human", they will reply with a sentence answering your question, or maybe asking for clarifications, etc. When you ask a question of GPT-4, it generates one token. One. Token. One token, that is not an answer to your question, that is not asking for clarifications, that is not trying to reason about your question, or how to answer it, because it's just one token. One. Token. For…

> There's no thinking, no reasoning, no calculation, no logic, no deduction, no intelligence, no anything. It's only token, token, token. False. The neural network inside the transformer LLM contains a hierarchical semantic model, and has inferred some rules of reasoning from the training set. It can apply those rules to new input. There are semantic layers above the "token token tokens". Explore them here: https://o…

[deleted]

Re: Language models can explain neurons in language models

#479

Post by YeGoblynQueenne » Sat, May 13, 2023, 9:04 AM UTC

xcv123 wrote: post #476

YeGoblynQueenne wrote: post #458

Earlier quoted context omitted.

When you ask a question of "an average human", they will reply with a sentence answering your question, or maybe asking for clarifications, etc. When you ask a question of GPT-4, it generates one token. One. Token. One token, that is not an answer to your question, that is not asking for clarifications, that is not trying to reason about your question, or how to answer it, because it's just one token. One. Token. For…

Prompt: What is the sieve of Eratosthenes? Speak in chicken Answer from GPT-4: Sure, here's the explanation of the sieve of Eratosthenes explained in a simplified "chicken" style: Imagine you are a chicken. You have lots of chicken friends. Let's say there are 100 of you. Now, you all stand in a line. Each chicken is numbered, from 2 up to 100. Chicken number 1 decided to stay at home because he's a bit special in th…

Bad prompt. Try "Only use the word chicken" instead of "Speak in chicken".

Re: Language models can explain neurons in language models

#480

Post by YeGoblynQueenne » Sat, May 13, 2023, 9:12 AM UTC

xcv123 wrote: post #477

YeGoblynQueenne wrote: post #458

Earlier quoted context omitted.

When you ask a question of "an average human", they will reply with a sentence answering your question, or maybe asking for clarifications, etc. When you ask a question of GPT-4, it generates one token. One. Token. One token, that is not an answer to your question, that is not asking for clarifications, that is not trying to reason about your question, or how to answer it, because it's just one token. One. Token. For…

> There's no thinking, no reasoning, no calculation, no logic, no deduction, no intelligence, no anything. It's only token, token, token. False. The neural network inside the transformer LLM contains a hierarchical semantic model, and has inferred some rules of reasoning from the training set. It can apply those rules to new input. There are semantic layers above the "token token tokens". Explore them here: https://o…

What you're commenting here is simply repearting, without critical intent, the baseless claims connectionists have made about their systems for many decades. Similarlly those claims have been criticised but connectionsists simply ignore the criticisms and continue with the same old nonsense, as if nothing happened. For example, that ridiculous conceit that their systems have "neurons", or that the weights of functions in a neural net somehow represent semantic categories recognised by humans. These are all complete fantasies.

If you are not aware of the long history of debunking such fabrications, I suggest you start here:

Connectionism and Cognitive Architecture: A Critical Analysis

https://ruccs.rutgers.edu/images/personal-zenon-pylyshyn/pro...