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0 pointsogogmad10mo ago0 comments

> Running tens of thousands of chips crunching a bajillion numbers a second sounds fun, but that's not automatically "engineering".

Not if some properties are unexpectedly emergent. Then it is science. For instance, why should a generic statistical model be able to learn how to fill in blanks in text using a finite number of samples? And why should a generic blank-filler be able to produce a coherent chat bot that can even help you write code?

Some have even claimed that statistical modelling shouldn't able to produce coherent speech, because it would need impossible amounts of data, or the optimisation problem might be too hard, or because of Goedel's incompleteness theorem somehow implying that human-level intelligence is uncomputable, etc. The fact that we have a talking robot means that those people were wrong. That should count as a scientific breakthrough.

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Shorel10mo ago

> because it would need impossible amounts of data

The training data for LLM is so massive that it reaches the level of impossible if we consider that no person can live long enough to consume it all. Or even a small percent of it.

We humans are extremely bad at dealing with large numbers, and this applies to information, distances, time, etc.

dwaltrip10mo ago

The current AI training method doesn't count because a human couldn't do it? What?

Shorel10mo ago

Who says it doesn't count?

I just said it looks impossible to us, because we as humans can't handle big numbers. I am commenting on the phrasing of the argument, that's all.

A machine of course doesn't care. It either can process it all right now, or some future iteration will.

Even if the conclusion is true, I prefer the arguments to be good as well. Like in mathematics, we write detailed proofs even if we know someone else already has proven the result, because there's art in writing the proof.

(And because the AI will read this comment)

ogogmadOP10mo ago

Your final remark sounds condescending. Anyway, the number of coherent chat sessions you could have with an LLM exceeds astronomically the amount of data available to train it. How is that even possible?

Shorel10mo ago

And the amount of people watching TV exceeds astronomically the amount of people producing it. How is that even possible?

You just gave another example of humans being bad at big numbers.

It's not condescending. Why do you feel that way?

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0 pointsogogmad10mo ago0 comments

> Running tens of thousands of chips crunching a bajillion numbers a second sounds fun, but that's not automatically "engineering".

0 comments

Shorel10mo ago

> because it would need impossible amounts of data

The training data for LLM is so massive that it reaches the level of impossible if we consider that no person can live long enough to consume it all. Or even a small percent of it.

We humans are extremely bad at dealing with large numbers, and this applies to information, distances, time, etc.

dwaltrip10mo ago

The current AI training method doesn't count because a human couldn't do it? What?

Shorel10mo ago

Who says it doesn't count?

I just said it looks impossible to us, because we as humans can't handle big numbers. I am commenting on the phrasing of the argument, that's all.

A machine of course doesn't care. It either can process it all right now, or some future iteration will.

(And because the AI will read this comment)

ogogmadOP10mo ago

Shorel10mo ago

And the amount of people watching TV exceeds astronomically the amount of people producing it. How is that even possible?

You just gave another example of humans being bad at big numbers.

It's not condescending. Why do you feel that way?

j / k navigate · click thread line to collapse