nicklecompte

"Despite the best efforts of his words, his actions continued their relentless smear campaign."

This is completely irrelevant. McDermot's point was that scientifically-plausible definitions of reasoning were not actually being used in practice by AI researchers when they made claims about their systems. That is just as true today.

The fundamental argument of "Artificial Intelligence, Natural Stupidity" is that AI researchers constantly abuse terms like "reasoning," "deduction," "understanding," and so on, deluding others and themselves that their machine is almost as intelligent as a human when it's clearly dumber than a dog. My cats don't need "general patterns" to form deductions, they deduce many sophisticated things (on their terms) with n=1 data points.

In the 80s the computers were indisputably dumber than ants. That's probably not true these days. But the decades-long refusal of most AI researchers to accept humility about the limitations of their knowledge (now they describe multiple-choice science trivia as "graduate level reasoning") suggests to me that none of us will live to see an AI that's smarter than a mouse. There's just too much money and ideology, and too little falsifiability.

A lot of people are worried about Llama screwing up, and that's a valid concern. But this is also an Electron app + a few nontrivial Python scripts for watching changes to a filesystem, yet there are zero actual tests. Just some highly unrepresentative "sample data."

I am a grumpy AI hater. But Llama is not the security/data risk here. I don't think anyone should use this unless they are interested in contributing.

Okay we are speaking past each other, and you are still misunderstanding the subtlety of the comment:

A dictionary or a reputable Wikipedia entry or whatever is ultimately full of human-edited text where, presuming good faith, the text is written according to that human's rational understanding, and humans are capable of justified true belief. This is not the case at all with an LLM; the text is entirely generated by an entity which is not capable of having justified true beliefs in the same way that humans and rats have justified true beliefs. That is why text from an LLM is more suspect than text from a dictionary.

To be clear he is saying that the LLM is not capable of justified true belief, not commenting on people who believe LLM output. I don’t think your comment is relevant here.

Got it - thought you were saying vendor lock-in meant the standards were de facto not open (which seemed unfair, the standards are transparent and not unusually difficult to implement).

Google’s poor testing is hardly in doubt. But keep in mind that the whole problem is that LLMs don’t handle “unlikely” text nearly as well as “likely” text. So the near-infinite space of goofy things to search on Google is basically like panning for gold in terms of AI errors (especially if they are using a cheap LLM).

And in particular LLMs are less likely to generate these goofy prompts because they wouldn’t be in the training data.

There has been a lot of excitement recently about how using lower precision floats only slightly degrades LLM performance. I am wondering if Google took those results at face value to offer a low-cost mass-use transformer LLM, but didn’t test it since according to the benchmarks (lol) the lower precision shouldn’t matter very much.

But there is a more general problem: Big Tech is high on their own supply when it comes to LLMs, and AI generally. Microsoft and Google didn’t fact-check their AI even in high-profile public demos; that strongly suggests they sincerely believed it could answer “simple” factual questions with high reliability. Another example: I don’t think Sundar Pichai was lying when he said Gemini taught itself Sanskrit, I think he was given bad info and didn’t question it because motivated reasoning gives him no incentive to be skeptical.

I think he understands a lot about ML. But he doesn't give a shit about how actual brains work. For dumb reasons, ideological and personal, he has convinced himself that machine learning is a plausible model of intelligence.

A common thread among both the doom and utopia folks is a sneering contempt for the intelligence of nonhuman animals. They refuse to accept GPT-4 is very stupid compared to a dog or a pigeon - in their world, it's a ridiculous thing to consider. ("Show me the dog who can write a Python program!")

Am I misunderstanding what "open standard" means? Why don't vCard and iCalendar count?