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I'll bite.

I received my PhD in Computer Science focused on NLP and creative text generation last year and I think the hype around LLMs is ridiculous (academics are no better than industry on chasing hype). They're trained to predict the next token given a context, and that's exactly what they're good at.

How old do you think I am?



A transistor is just a way of connecting some wires, and that's exactly what it's good for. It's reducing a phenomenon into some core essence and pretending like there's not a bigger picture.


Doesn’t that feel a little bit like saying that the hype around transistor-based logic gates is ridiculous because they’re designed to execute Boolean logic, and that’s exactly what they’re good at? The simple mechanism isn’t what’s exciting. The exciting part is composing that into a symphony of functionality, running fast and cheap, to better our lives.


no, because before transistors we had vacuum tubes so the functionality of a transistor was well understood and the breakthrough was in size and power consumption.

the analogy would be more apt if tomorrow I could run ChatGPT 4o, the hosted model, on my wrist watch, and run it indefinitely for pennies.


3.5 turbo?


I was in my 20s when crypto was "it" and I was definitely on the last group about it, so it's definitely not just about age, even thought there's probably some correlation.


> "is new and exciting and revolutionary and you can probably get a career in it."

Does this not explain why you just got your PhD in this? ("This" being broad, but "NLP and creative text generation" sounds like it's in the same ballpark as LLMs.)


Nope. I did it purely due to long-term intellectual curiosity.

I first pursued "AI" in undergrad during the last AI winter. For example, the only professor who taught neural networks at Purdue was in the EE dept, not CS, and was retiring the semester I was first qualified to study it. There weren't enough seats in the class, and since it was graduate level, I wasn't allowed to take it as an undergrad.

I really tried every avenue I could think of at the time to pursue AI — taking part in Robocup, taking classical AI (also from the EE dept), etc. None of what I was exposed to seemed like it was pushing the the intellectual boundaries, so I instead got into video game AI as a way to pursue AI (a number of famous ML researchers like Demis Hassabis got their start in video games).

When I started my PhD a very tiny group of researchers were looking at text generation, let alone for creative text. The idea was very niche.

Note, I only pursued a PhD after I got an interview at OpenAI in 2017 that made me realize a PhD was likely necessary to pursue research.


Thanks. Sometimes I feel like I'm going insane attempting to ŕeason with people who think the opposite. That these are oracles imbued with human level intellect and creativity.

Now, sure, these models can be impressive - but it's a warped lens of humanities own impressive (selected) corpuses.




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