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Comment by bjourne | Hacker News Reader

> I am convinced

What evidence are you basing your conviction on?

It is fundamentally based on initial hype and mania of other HN ChatGPT posts. Other than that, nothing.

Ask ChatGPT to solve unsolved mathematical and computer science problems or any basic international mathematical olympiad (IMO) questions and it falls before the starting line and will give incoherent answers.

Even if it moves an inch past the line, it cannot transparently explain as to how it got there in the first place.

Well, it wasn't designed to generate novel math proofs.

True but either way it's like encryption newbies worrying about quantum computing or the general public thinking our energy issues will soon be solved with fusion power. Just five more years...

In reality, we don't have artificial intelligence and until we create a machine that can be called intelligent we don't even know for sure if it's possible at all. In the foreseeable future human programmers will be needed, when the day comes that machines archive general intelligence all bets are off anyway.

This question seems to me a bit like asking what field should I specialize in if I believe we'll make first contact with an alien race in the next 10 years. Who knows?

Time for schools to start offering an Intergalactic Relations major to prepare us ;p

Just ask it the definition of a mathematical term and watch it get it wrong. For example, I asked it to define the Kronecker product and it gave me a lot of correct information, but the actual equations were wrong.

Don’t look at where we are now, look at the rate of improvement. I don’t think it’ll be long before it has an understanding of advanced mathematics.

This has always been the argument for technologies that failed too. In many cases it turns out that it is rather "easy" to get the first 90% working but the remanining 10% are not only exponentially more difficult to get going, but also what is the difference between a tool and a toy.

>Ask ChatGPT to solve unsolved mathematical and computer science problems

or alternatively just ask it to solve simple addition. It can't reliably add large numbers together either. As good as it is at producing plausibly sounding language it has virtually no facilities to reason or learn axiomatic rules.

> It can't reliably add large numbers together either

That's fine. It can always use a computer if need be.

> As good as it is at producing plausibly sounding language it has virtually no facilities to reason or learn axiomatic rules.

I've never been hired on the basis of learning axiomatic rules.

For it to be able to use other agents it needs to understand when a problem requires deductive reasoning, and when probabilistic inference is appropriate. So that's just moving the goalpost. And of course in that case the intelligence and capacity is then in the system the task is outsourced to, so it still needs to be solved over there.

>I've never been hired on the basis of learning axiomatic rules.

Nope but you'd be fired really quickly if you couldn't communicate or follow some. I don't think you were trained to not throw coffee cups off the table like a cat via reinforcement, B.F. Skinner style. Which is really how we have to interact with these models (i.e. prompt 'engineering'). For humans to put artificial systems in task of really complex systems there needs to be a way to interact at a high level reliably and put boundaries (that is, rules) in place. As of today we largely have those outside of the models when necessary.

Frankly I don't understand what all the fuss is about. It vomits coherent sentences. It is fundamentally unsuitable for the majority of "proclaimed" use cases.

how is this relevant to OP's concern?

most software engineers today are employed to solve unsolved mathematical and computer science problems or IMO-style problems.

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