60
Mistral AI's CEO says Europe has 2 years to stop becoming America's AI 'vassal state'
(www.businessinsider.com)
"We did it, Patrick! We made a technological breakthrough!"
A place for all those who loathe AI to discuss things, post articles, and ridicule the AI hype. Proud supporter of working people. And proud booer of SXSW 2024.
AI, in this case, refers to LLMs, GPT technology, and anything listed as "AI" meant to increase market valuations.
AI is needed in science, medicine, meterology and industry, eg.investigations by the CERN are not possible without AI, some meta-materials which we use wouldn't exist without AI. AI itself isn't the problem, but as hype inbuild even in a Fridge, it's use by any idiot, tankie and big (US) corps with selfish intentions. Europe has good own AI alternatives, eg. the one used, among others, by the CERN, the OpenSource Apertus.
Part of the problem is people generally confusing Machine Learning and other actually useful forms of AI with the generative LLM slop, biometric mass surveillance and autonomous weapon systems these tech bros are pushing for. So no, we don't need that kind of "AI".
Agree. Well LLM is inherent to make possible an interaction with the AI and asociate machine learning. But certainly it isn't the same using a biased chatbot with an LLM to analyze, interprete and summarize a given text or data set. Bad is when the generative AI invent datas when it don't figure in his lenguage model causing this slops. This often ocurre in alround AI which pretend to do everything (text, image,......), not so in AI specialized in certain tasks. Like a swiss army knife never can substitute a normal knife suissors, saw, screwdriver......, it will always only be an reduced emergency solution.
You don't need an LLM to interact with machine learning algorithms.
In fact, one might argue one should not use an LLM to interact with machine learning algorithms. 😆
That's a very exotic take. Language (semantic embeddings) is a good mediator for a lot of tasks, which makes it easier for ML models to generalize. The intersection of old school ML and LLMs is a fascinating place, I've never seen it dismissed like that. Do you have any reading you'd recommend on the subject?
Just as a professional communication tip here: When the general public is speaking of "AI" right now, they are referring to degenerative AI, not to the older waves of AI hype and collapse.
The older waves have found their niches and perform admirably in them. (My phone's camera was "AI" before LLMs became a thing, for example.) But that's not what anybody but a pedant (who is only barely better than a pedarast) means when they say "AI" outside of very specific technological communication contexts.