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0 pointsoldandtired2y ago0 comments

You make a claim here with "Each answer displayed astonishing understanding of what occurs." and the question you fail to ask is: Whose understanding?

The responses are based on the accumulated knowledge of humans and not machines. The systems have not thought through anything and understand nothing. A process of analysing or pattern matching the input question with the data stored retrieves an answer. But that data stored is human knowledge and human effort not machine.

If you look very carefully at the results obtained, it either contains "interesting errors" (for which an intelligent human would pick up) or it is a summation of human knowledge.

The answers still have to be tested and confirmed for rationality and applicability by humans. In other words, this is a tool like all tools created by humans.

I have seen too many examples of what are supposed to be correct answers that contained subtle and not so subtle errors.

Like every system we have ever made, Garbage in gets us Garbage out. We are the ones responsible to checking those answers and making sure that they make sense in the real world.

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IanCal2y ago

> A process of analysing or pattern matching the input question with the data stored retrieves an answer.

They're not just retrieving stored text like pulling the most relevant passage from a database. If they were they'd not be able to deal with things outside the training set. They couldn't write code for a custom library that was created after the cutoff (they can with a description), and they couldn't write about terms made up in the question.

worksonmine2y ago

I don't see why not. It's not taking a single answer from a database no, it's taking several based on probability and merging them into what it thinks we're looking for. If you learn to multiply with code to perform one task, you can then apply that knowledge for a completely different task. It may look like solving a completely new problem but the LLM doesn't even see the difference.

When you use the term "custom library" that might be you over-complicating the task. It's still just looking up function to do x, function to do y and applying it to the output. Don't get me wrong it's impressive where we're at but there's no need to exaggerate it as magic.

IanCal2y ago

> . It's still just looking up function to do x, function to do y and applying it to the output.

I mean no, no it isn't.

I'm giving it info on how to construct data models with a custom library, so interacting with that is not using anything previously stored, and then giving it businesses/tasks to model as simple human descriptions.

If you tell me that something which

* Takes a human description of a problem

* Describes back to me the overall structure and components required to solve it with a hierarchy

* Converts that into code, correctly identifying where it makes sense for an address to be contained within a model or distinct and referenced

* Correctly reuses previously created classes that are obviously not in its original dataset

has no understanding or reasoning and it just regurgitating things it's seen before simply mashed together, I don't know what to say.

Frankly

> it's taking several based on probability and merging them into what it thinks we're looking for. I

Sounds pretty much like understanding and reasoning to me.

> but there's no need to exaggerate it as magic.

I'm absolutely not saying there's magic. Humans aren't magic and they can do reasoning. I'm saying it's not just looking up text and regurgitating it.

I think this is supported by things like othello-gpt, which builds an internal world model and outputs based on that.

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corethree2y ago

> You make a claim here with "Each answer displayed astonishing understanding of what occurs." and the question you fail to ask is: Whose understanding?

The answer is obvious. The LLM is understanding the concepts. The last question was unique. The resulting answer was also unique.

It was not a "retrieved" answer. It was a unique answer. A correct composition of several underlying concepts. A correct composition can only be formulated if the machine had correct understanding of each concept and how they relate to one another.

This thing understands you. It wholly owns this understanding. It is not regurgitating knowledge. It is inventing new answers.

Wake up man. I had the LLM invent 6 regions and heat the cup of coffee to plasma levels of heat. The answer and composition of concepts was remarkable.

You're calling it a parlor trick because of subtle errors? Bro. Come on.

oldandtiredOP2y ago

> The answer is obvious. The LLM is understanding the concepts

Who created the LLM? Whose understanding underpins the LLM?

Certainly not the LLM.

> This thing understands you.

Does it? Or is this a result of the intelligence of the human beings involved in building the LLM?

> I had the LLM invent 6 regions and heat the cup of coffee to plasma levels of heat.

Did the LLM actually invent anything? Or was this result directly based on you and your intelligence with the recorded knowledge of all the human sources involved in the solution?

> You're calling it a parlor trick because of subtle errors?

I haven't called it a parlour trick. All I am saying is that there is no intelligence in these systems. Human intelligence built them, but these systems in and of themselves have no intelligence.

We do of course build many intelligent systems all the time, they are called children.

corethree2y ago

>Who created the LLM? Whose understanding underpins the LLM?

Who created you? Whose understanding underpins you? Asking these questions about you is as irrelevant as asking it about the LLM.

Just because books, educations your teachers, the internet and your parents and the environment shaped everything you know doesn't preclude your membership into the category of things that are capable of understanding.

>Does it? Or is this a result of the intelligence of the human beings involved in building the LLM?

It does understand you. The intelligence of human beings who built it aren't directly involved as it was trained on external data.

>Did the LLM actually invent anything? Or was this result directly based on you and your intelligence with the recorded knowledge of all the human sources involved in the solution?

Does a human actually invent something or is it directly based on recorded knowledge?

You're asking irrelevant questions. Humans do not create things out of thin air either. Humans also invent things by composing existing knowledge to form concepts. The inventing that LLMs can do is equivalent in totality to our understanding of the word "invent"

>I haven't called it a parlour trick. All I am saying is that there is no intelligence in these systems. Human intelligence built them, but these systems in and of themselves have no intelligence.

Totally false. Not only are you wrong but experts in AI including the father of modern AI disagree with you completely and utterly.

If I copied your brain and replicated exactly that brain is "from human intelligence" but that copy of your brain is still an intelligence independent of it's origins and where it got it's knowledge.

>We do of course build many intelligent systems all the time, they are called children.

It's like you're eating your own logic. We also build intelligent systems called LLMs. Same concept.

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IanCal2y ago

It's generating code for a brand new library based on explanations from me, it can write poems about the current news headlines and it can answer hypotheticals with words I've made up. I agree it cannot be just looking up stored answers.

Gpt Othello is a good discussion about this that's more constrained too.

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