this post was submitted on 15 Nov 2023
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Machine Learning

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With the advent of LLMs, multimodality and “general purpose” AIs which seat on unimaginable amounts money, computing power and data. I’m graduating and want to start a PHD, but feel quite disheartened given the huge results obtained simply by “brute-forcing” and by the ever-growing hype in machine learning that could result in a bubble of data scientists, ML researchers and so on.

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[–] Grouchy-Friend4235@alien.top 1 points 10 months ago (7 children)

The bubble is about to burst. Six more months, tops. At that point people will realize that next word prediction while impressive is just not very useful in most business contexts, and that the use cases that might be interesting don't need a universe-sized model. Useful applications of natural language processing are quite limited despite what everyone says right now. The idea to replace workers in large numbers is a pipedream, if the idea has merit at all it will be for those who promote it the most (talking heads).

[–] MyPetGoat@alien.top 1 points 10 months ago (1 children)

All technology will have a natural language interface within 10 years. We will have embodied reasoning machines at most a decade later. Your perspective is skewed by your business context perhaps

[–] damhack@alien.top 1 points 10 months ago

Divide those timescales by 4 and you are on the mark.

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