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naraburns  nihil supernum  1yr ago (text post)   16084 thread views

Culture War Roundup for the week of December 19, 2022

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AI has now understanding. It is like letting a person who grew up in a village in the amazon observe a nucit lear power plant operator push buttons and then giving the villagers the controls. They might be able to mimic the behaviour but there is no understanding. AI doesn't understand and it doesn't reason, Just guessing the next chess move by observing what elite players have played is one thing. Interacting with the real world without any actual understanding will never work. There is a reason why dentists learn chemistry, engineers learn math and why education has hands on labs. Without real world experience and intuition one can never become proficient.

Actual understanding and context are AI problems that haven't really progressed at all and until they do AI is going to be stuck in the realm of tools used in specific circumstances.

Username checks out :)

The death of GOFAI is a tragedy, however humans also mostly learn by mimetism however they build a model of reality based on mimetics insights and that, a neural network cannot reliably.

However, while I still believe chatgpt is a data illusion, for the first time in my life I fail to explain the illusion as chatgpt is able to do things reliably that goes far beyong an ability to flexibly scrap existing datasets.

The other tragedy is that neural networks based on precise emulation of the architecture of an animal brain are completely non-funded and conversely the funding on retro-engineering of simple animal brains is of close to zero. We are very close to a full observability and mapping of the c-elegans brain, however nobodys working on the remaining gaps (e.g. GABA neurons). As I have disocovered in my life, almost all key blockers to scientific disruption share a similar issue: nobody's working on them. Nobody's funding them.

Hence when people forecast AGI progress on metaculus, they systematically fail to understand that the forecast is not a number of pending years but the infinity of time.

But that's the thing, it isn't capable of accomplishing all sorts of goals as seen in this thread, because it lacks understanding. It will need that understanding to ever get to a point where it becomes an X-risk.

Nobody can ever define what "understanding" means

This is an appeal to ignorance.

Understanding something is having a causal model of it.

It allows to analyze such system and reliably predicts it and its consequences.

A system with a reliable understanding should be able to output argumentative text/syllogisms showing said understanding, free of logical fallacies and with source to the truth values of the premises.

To mysticize what understanding is really shows once again the truism that epistemology should be taught in schools.

The point is, it does not matter whether you think it is really really deeply understanding, as long as it is capable of accomplishing goals and having real impact.

At the end of the day, the result is what matter indeed, but without understanding a system is non-reliable and cannot be trusted for many serious needs.

That is a geat comment, I will answer it properly when I get the time.

Observe the nuclear power plant operator long enough and you can plausibly gain enough understanding to run the power plant while never figuring out what fission is.

No, I don't think so, there are likely way too many edge cases that all require genuine understanding to solve.

Until you run in a situation you never encountered before as the world is highly variadic and then the system pathetically fail.

Yes, which is a problem solved by more training data.

That is not a solid solution to any dataset changing in real time. More data can only do so much, as a metaphor, see the limits of AOT versus JIT for compilers.

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