Microsoft has Copilot Plus PCs loaded with AI, and rumors are that Apple is all in on AI, too, but if you don't want AI in everything you do, there is another option: Linux.
That’s a pretty big joke, but I think the bigger joke is calling LLMs AI. We taught linear algebra to talk real pretty and now corps want to use it to completely subsume our lives.
Frankly, LLMs (which are based on neural networks) seem a Hell of a lot closer to how actual brains work than “classical AI” (which basically boils down to a gigantic pile of if statements) does.
I guess I could agree that LLMs are undeserving of the term “AI”, but only in the sense that nothing we’ve made so far is deserving of it.
Let’s agree to disagree then. An LLM has no notion of semantics, it’s just outputting the most likely word to follow up to what it’s already written and the user’s input.
On the contrary, expert systems from back in the 90s for, say, predicting the atomic structure of an element, work like a human brain on steroids. It features an arbitrary large search tree that the software knows how to iterarively prune according to a well known set of chemical rules. We do the same when analyzing a set of options.
Debugging “current” AI models, on the other hand, is impossible because all we’re doing is prescripting a composition of functions and forcing it to minimize a loss function. That’s all we’re doing. How can you currently tell that a certain model is going to work? Unless the mathematical theory ever catches up with the technology, we’ll never know until we execute the code.
Oh I agree. I typically put “AI” in quotation marks when using that term regarding LLMs, because to me they simply are not intelligent in anyway. In my mind an AI would need an actual level of consciousness of sorts, the ability to form actual thoughts and learn things freely based on whatever senses it has.
But AI is a term that’s good for marketing as well as fear mongering, which we see a lot of in current news cycles and on social media. The problem is that most people do not even understand the basic principles of how LLMs work, which lead to a lot of misconceptions about its uses & misuses and what we should do about it.
Weirdly enough this makes LLMs both completely overhyped as a product and completely stigmatized as some nefarious tool as well. But I guess it fits into our today’s societies that kinda seem to have lost all nuance and reason.
That’s a pretty big joke, but I think the bigger joke is calling LLMs AI. We taught linear algebra to talk real pretty and now corps want to use it to completely subsume our lives.
I have to disagree.
Frankly, LLMs (which are based on neural networks) seem a Hell of a lot closer to how actual brains work than “classical AI” (which basically boils down to a gigantic pile of
ifstatements) does.I guess I could agree that LLMs are undeserving of the term “AI”, but only in the sense that nothing we’ve made so far is deserving of it.
Let’s agree to disagree then. An LLM has no notion of semantics, it’s just outputting the most likely word to follow up to what it’s already written and the user’s input.
On the contrary, expert systems from back in the 90s for, say, predicting the atomic structure of an element, work like a human brain on steroids. It features an arbitrary large search tree that the software knows how to iterarively prune according to a well known set of chemical rules. We do the same when analyzing a set of options.
Debugging “current” AI models, on the other hand, is impossible because all we’re doing is prescripting a composition of functions and forcing it to minimize a loss function. That’s all we’re doing. How can you currently tell that a certain model is going to work? Unless the mathematical theory ever catches up with the technology, we’ll never know until we execute the code.
Oh I agree. I typically put “AI” in quotation marks when using that term regarding LLMs, because to me they simply are not intelligent in anyway. In my mind an AI would need an actual level of consciousness of sorts, the ability to form actual thoughts and learn things freely based on whatever senses it has. But AI is a term that’s good for marketing as well as fear mongering, which we see a lot of in current news cycles and on social media. The problem is that most people do not even understand the basic principles of how LLMs work, which lead to a lot of misconceptions about its uses & misuses and what we should do about it. Weirdly enough this makes LLMs both completely overhyped as a product and completely stigmatized as some nefarious tool as well. But I guess it fits into our today’s societies that kinda seem to have lost all nuance and reason.