Comment by massung
2 days ago
I know LLMs are getting the majority of the attention of late, but there are others of us training and using AI to…
…reads MRIs and video to detect cancer
…analyze genomics for early target discovery
…assisting surgeons
…folding proteins
And the list goes on in other fields as well. Just hoping the recent AI counterculture doesn’t stigmatize other uses of AI.
Am I a fan of Claude code? Not particularly, but I have used it on occasion. And I’ll never understand someone using an LLM to write anything (especially a comment on a site like HN) intended for consumption by other people. Not because I think it’s subpar, but because the point - IMO - is to make human connections, learn, teach, and debate. That’s hard (impossible?) to do if you’re just typing a 30 second prompt and then copy/pasting the output.
This problem only exists because of the marketing move to call anything even slightly ML related "AI".
I see it as a double edged sword. People that want the category of AI to succeed can claim a victory when someone uses it to approximate protien folding and invent new drugs. But that also means the entire field is constantly being dragged down by low quality vibe coded sites, slop videos on social media, whatever horrific thing Grok is doing this week, etc.
>This problem only exists because of the marketing move to call anything even slightly ML related "AI".
We need to remember what "Artificial Intelligence" actually means. It refers to the field of research starting in the 1950's developing algorithms related to combinatorial search, planning, and reasoning. Machine Learning isn't AI in the sci-fi movie sense, but it's among the topics you'll find in a textbook like Russell and Norvig.
A problem like protein folding isn't tangentially related to AI, it's at the heart of the kinds of problems the field has been trying to tackle for decades. Yet when there are legitimate breakthroughs, people deride it as "not real AI."
AI effectively has always been "currently best methods that mimic human decision making".
That isn't how we break up the field of AI. ML are the algorithms that are based on statistics and other numeric methods. The other algorithms are based on logic and perhaps some philosophical methodologies. We don't really have a name for that second group, its just part of AI. Then there is Reinforcement Learning which is a sub-field of ML and incorporates a Pavlovian methodology.
AI is the sum of all of these groups. Also, the "not real AI" thing is more about not real AGI. That's a very different target.
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I thought the point of HN was to help venture capitalists find ~~marks~~ projects to fund