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[D] What is the future for ML researchers and startups? (alien.top)

submitted 2 years ago by francMesina@alien.top to c/machinelearning@academy.garden

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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 2 years 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).

[–] damhack@alien.top 1 points 2 years ago

Depends on if the bubble you are referring to is the current crop of Transformers. Which will keep running for a good while. However, the bubble will be made larger once Karl Friston’s group start releasing and low power Transformer-optimised optical chips start production next year. I can’t see an end to it as most current issues are in the process of being solved, including smaller, faster, less hallucinatory low compute models. We’re only just hitting the multimodal on-ramp and that journey has far to go.

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