I think you're underselling the field of language processing - it wasn't just a single field but a bunch of subfields with their own little journals, papers and techniques - someone who researched machine translation approached problems differently to somebody else who did sentiment analysis for marketing.

I had a friend who did PhD research in NLP and I had a problem of extracting some structured data from unstructured text, and he told me to just ask ChatGPT to do it for me.

Basically ChatGPT is almost always better at language-based tasks than most specialized techniques for the specific problems the subfields meant to address, that were developed over decades.

That's a pretty effing huge deal, even if it falls short of the AGI 2027 hype

I think they meant fields of research. If you do anything in NLP, CV, inverse-problem solving or simulations, things have changed drastically.

Some directly, because LLMs and highly capable general purpose classifiers that might be enough for your use case are just out there, and some because of downstream effects, like GPU-compute being far more common, hardware optimized for tasks like matrix multiplication and mature well-maintained libraries with automatic differentiation capabilities. Plus the emergence of things that mix both classical ML and transformers, like training networks to approximate intermolecular potentials faster than the ab-initio calculation, allowing for accelerating molecular dynamics simulations.

Transformers aren't only used in language processing. They're very useful in image processing, video, audio, etc. They're kind of like a general-purpose replacement for RNNs that are better in many ways.

As a professor and lecturer, I can safely assure you that the transformer model has disrupted the way students learn - iin the literal sense of the word.

That would one of the examples which he described sd "expect disrupting in a negative way"

The goal was never to answer the question. So what if it's worse. It's not worse for the researchers. It's not worse for the CEOs and the people who work for the AI companies. They're bathing in the limelight so their actual goal, as they would state it to themselves, is: "To get my bit of the limelight"

>The final conversation on Sewell’s screen was with a chatbot in the persona of Daenerys Targaryen, the beautiful princess and Mother of Dragons from “Game of Thrones.” > >“I promise I will come home to you,” Sewell wrote. “I love you so much, Dany.” > >“I love you, too,” the chatbot replied. “Please come home to me as soon as possible, my love.” > >“What if I told you I could come home right now?” he asked. > >“Please do, my sweet king.” > >Then he pulled the trigger.

Reading the newspaper is such a lovely experience these days. But hey, the AI researchers are really excited so who really cares if stuff like this happens if we can declare that "therapy is transformed!"

It sure is. Could it have been that attention was all that kid needed?

Alphafold and protein folding.

I'm not watching a video on Twitter about self driving from the company who told us twelve years ago that completely autonomous vehicles were a year away as a rebuttal to the point I made.

If you have something relevant to say, you can summarize for the class & include links to your receipts.

your choice, I don't really care about your opinion

Then why call yourself "iknowstuff" then prove you don't?

You’ll be shocked to find out this is a public forum and not DMs

Evading the question, why reply?

Summers over kid.