51–60 of 74 posts
Fun fact: I took the photo she used as a cover for one of her books, she asked me if she could use it and I said I'd like to be compensated and her response was something akin to "oh I was just asking assuming you'd say yes, I'm going to do it anyway". Nobody's perfect, maybe she regrets it, and it hasn't really crossed my mind in years, but I guess it still sort of irks me to be reminded of it. Anyway if anyone need…
"Never before in my life had I seen so many smart people working on the same goal" I'm not sure why but the assumptions and naivety in this opening line bothers me. There are plenty of goals and problems that orders of magnitude more people are working on today.
"Never before in my life had I seen so many smart people working on the same goal" I'm not sure why but the assumptions and naivety in this opening line bothers me. There are plenty of goals and problems that orders of magnitude more people are working on today.
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Sounds like a great motivation for academic researchers to find a way to train LLMs with less compute. Or maybe invent something better than transformers. A brain trains on 20 Watts after all.
That's a hardware difference. Brains run at a very low clock speed and make up for it with massive parallelism. They also don't suffer from the vonn neumann bottleneck - today's computers spend most of their time and energy shuffling the network in and out of memory. I believe that better hardware architectures will have more impact on AI than better neural network architectures.
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My feeling is that GOFAI had a real problem with representing uncertainty, and handling contradiction. So, we tried to approach it theoretically, with fuzzy logic and probability and so on. But the theoretical research on uncertainty didn't reach any clear conclusion. Meanwhile, the neural nets (and ML) researchers just trucked on, with more compute power, and pretty much ignored any theoretical issues with uncertain…
I think that ascribes way too much meaning to hallucinations, which are the artifact of a big fancy markov chain doing what you'd expect a big fancy markov chain to do.
Fun fact: I took the photo she used as a cover for one of her books, she asked me if she could use it and I said I'd like to be compensated and her response was something akin to "oh I was just asking assuming you'd say yes, I'm going to do it anyway". Nobody's perfect, maybe she regrets it, and it hasn't really crossed my mind in years, but I guess it still sort of irks me to be reminded of it. Anyway if anyone need…
Just another random anecdotal experience with Chip. I was interviewing with Claypot.ai and when I met her for my first conversation, she was on a walking treadmill and very clearly was more interested in a Slack conversation she was having. She moved me on to the next round which I irrefutably bombed and was respectfully told that I wouldn't be moving on which was the right decision, but I'll never forget watching he…
Earlier quoted context omitted.
Just another random anecdotal experience with Chip. I was interviewing with Claypot.ai and when I met her for my first conversation, she was on a walking treadmill and very clearly was more interested in a Slack conversation she was having. She moved me on to the next round which I irrefutably bombed and was respectfully told that I wouldn't be moving on which was the right decision, but I'll never forget watching he…
It’s possible they were taking notes on the second monitor. Many interview coaches recommend taking notes during the interview to capture the response, largely verbatim, so that candidates can be fairly compared afterwards.
I think it's not possible to get rid of hallucinations given the structure of LLMs. Getting rid of hallucinations requires knowing how to differentiate fact from fiction. An analogy from programming languages that people might understand is type systems. Well-typed programs are facts and ill-typed programs are fictions (relative to the given typing of the program). To eliminate hallucinations from LLMs would require…
While I'm definitely not going to argue that LLMs are inherently 'thinking' like people do, one thing I do find pretty interesting is that all this talk about hallucinations and bias seems to often conveniently ignore the fact that people are often even more prone to these exact same problems - and as far as I know that's also unlikely to be solved. ChatGPT is often 'confidently wrong' - I'm pretty sure I've been con…
I think it's not possible to get rid of hallucinations given the structure of LLMs. Getting rid of hallucinations requires knowing how to differentiate fact from fiction. An analogy from programming languages that people might understand is type systems. Well-typed programs are facts and ill-typed programs are fictions (relative to the given typing of the program). To eliminate hallucinations from LLMs would require…