I spoke to Anthropic’s AI agent Claude about AI collecting massive amounts of personal data and how that information is being used to violate our privacy rig...
Bernie Sanders has unfortunately been duped into thinking AI is what the evangelists (tech CEOs and doom evangelists, including the cult leader Eli Yudkowsky) have told him about it.
Here (Twitter) is a video from Bernie’s office that starts with a cult leader telling Bernie that AI will kill humanity. It is presented uncritically.
Also, LLMs are not AI (in the sense that most people would deem meaningful): there’s no reasoning involved, just a convincing illusion of it, served by extensive knowledge compaction and next token prediction. That is not to say that LLMs are useless, or that the sort of all-powerful AI people fantasize about cannot exist (I really don’t know, no people do). That is to say that it’s not for now, and that before it happens, we will see another long AI winter before the emergence of something fundamentally more convincing than LLMs.
Same goes for anything else artificial. Why expect more than a plastic stand-in useful for some purposes when talking about artificial intelligence?
The word really isn’t the problem. Yeah maybe one day we’ll be able to make artificial grass that you can feed a goat and it’ll grow back, but IKEA really isn’t interested in that.
It’s also no secret that the companies involved in the LLM craze (OpenAI, Anthropic, Microsoft, …) diligently muddy the waters as a marketing trick to sell their product for more than what it is, that’s precisely what I’m calling out here: we can collectively do better/know better than that.
Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence,
Yeah so like how astroturf is a bit of plastic with some properties usually associated with grass. I don’t see a problem with the term.
It’s gonna be much easier to reemphasize the A in AI than coming up with a new term that sticks and doesn’t have other problems.
This works and has happened multiple times before (eg chess computers). I mean, “machine learning” was a marketing term invented exactly to avoid the A in AI.
Was there even a point you wanted to make? I’m not sure exactly where you are heading with all this.
I mean, “machine learning” was a marketing term invented exactly to avoid the A in AI.
No, it’s not. ML is a sub-category within the collection of AI techniques that describes those algorithms whose behaviour is the result of fitting a training data-set to a pre-defined model by minimising an agreed-upon error function. For the longest of times, we were just calling that “statistics”, and many ML techniques and algorithms predate computers by centuries. Your mean-squares curve fitting? …qualifies as ML. That is to say, ML is all AI, but not all AI is ML.
LLMs are no different than function fitting with mean-squares. They are not magical, they are not black-boxes: they are fully described and completely predictable.
So, we’ve gone full circle. LLMs is a sub-category within the collection of ML techniques within the collection of AI techniques. Point is, AI is just a term here. A label, that indicates nothing about the abilities of LLMs to exert any form of intelligence or reasoning. In other words, the whole field of AI could (should?) have been named “computational statistics” or “mathematics applied to numerical datasets” (or whatever else you want, really…), and LLMs would absolutely belong to “CoStats”/“MAND” fields, for the same reason we say they relate to “AI” today, it’s just that nobody would be silly enough to call them “artificially intelligent”.
ML is AI too. But sales didn’t call it that because AI had the reputation of “just brute force with some heuristics”.
What sales are you even thinking about? What do even presume the market for ML algorithms to be? Nobody was shopping for support vector machines as a service, or spending tokens on linear regression, or using convolutional neural networks via API before the current LLM craze. What the field is experiencing right now is unheard of. Never before did the private sector jump gun on a niche technique and spent trillions to package, anthropomorphise and market it as if “AI has finally been figured out, and we happen not only to own it, but also to sell it to you”. This deceptive rhetoric would be a much tougher sell if some early computer scientists hadn’t happened to name their field “AI”.
Ok. You said LLMs are not AI, I didn’t agree with the nuance. You’re making a big thing out of this.
ML was huge in B2B and still going steady. Not “SVMs as a service”, but you bet sales teams were letting everybody know that their solutions learn. You can find loads of conference material about “why ML is better than AI” from a decade ago. They pivoted to calling it AI again of course, even if the product didn’t change.
Bernie Sanders has unfortunately been duped into thinking AI is what the evangelists (tech CEOs and doom evangelists, including the cult leader Eli Yudkowsky) have told him about it.
Here (Twitter) is a video from Bernie’s office that starts with a cult leader telling Bernie that AI will kill humanity. It is presented uncritically.
Also, LLMs are not AI (in the sense that most people would deem meaningful): there’s no reasoning involved, just a convincing illusion of it, served by extensive knowledge compaction and next token prediction. That is not to say that LLMs are useless, or that the sort of all-powerful AI people fantasize about cannot exist (I really don’t know, no people do). That is to say that it’s not for now, and that before it happens, we will see another long AI winter before the emergence of something fundamentally more convincing than LLMs.
Would you expect anything more than astroturf when I say artificial grass? It’s really not controversial to call it that. https://www.ikea.com/be/en/p/runnen-floor-decking-outdoor-artificial-grass-50313131/
Same goes for anything else artificial. Why expect more than a plastic stand-in useful for some purposes when talking about artificial intelligence?
The word really isn’t the problem. Yeah maybe one day we’ll be able to make artificial grass that you can feed a goat and it’ll grow back, but IKEA really isn’t interested in that.
I mean, have fun re-defining artificial intelligence to suit your narrative. Here’s what the scientific consensus stands at: https://en.wikipedia.org/wiki/Artificial_intelligence
It’s also no secret that the companies involved in the LLM craze (OpenAI, Anthropic, Microsoft, …) diligently muddy the waters as a marketing trick to sell their product for more than what it is, that’s precisely what I’m calling out here: we can collectively do better/know better than that.
Yeah so like how astroturf is a bit of plastic with some properties usually associated with grass. I don’t see a problem with the term.
It’s gonna be much easier to reemphasize the A in AI than coming up with a new term that sticks and doesn’t have other problems.
This works and has happened multiple times before (eg chess computers). I mean, “machine learning” was a marketing term invented exactly to avoid the A in AI.
Was there even a point you wanted to make? I’m not sure exactly where you are heading with all this.
No, it’s not. ML is a sub-category within the collection of AI techniques that describes those algorithms whose behaviour is the result of fitting a training data-set to a pre-defined model by minimising an agreed-upon error function. For the longest of times, we were just calling that “statistics”, and many ML techniques and algorithms predate computers by centuries. Your mean-squares curve fitting? …qualifies as ML. That is to say, ML is all AI, but not all AI is ML.
LLMs are no different than function fitting with mean-squares. They are not magical, they are not black-boxes: they are fully described and completely predictable.
Yes, the point is LLMs are AI.
ML is AI too. But sales didn’t call it that because AI had the reputation of “just brute force with some heuristics”.
Now we forget about that so it’s hype to call things AI again. Once LLMs lose their magic the next big AI thing will again not be sold as AI.
So, we’ve gone full circle. LLMs is a sub-category within the collection of ML techniques within the collection of AI techniques. Point is, AI is just a term here. A label, that indicates nothing about the abilities of LLMs to exert any form of intelligence or reasoning. In other words, the whole field of AI could (should?) have been named “computational statistics” or “mathematics applied to numerical datasets” (or whatever else you want, really…), and LLMs would absolutely belong to “CoStats”/“MAND” fields, for the same reason we say they relate to “AI” today, it’s just that nobody would be silly enough to call them “artificially intelligent”.
What sales are you even thinking about? What do even presume the market for ML algorithms to be? Nobody was shopping for support vector machines as a service, or spending tokens on linear regression, or using convolutional neural networks via API before the current LLM craze. What the field is experiencing right now is unheard of. Never before did the private sector jump gun on a niche technique and spent trillions to package, anthropomorphise and market it as if “AI has finally been figured out, and we happen not only to own it, but also to sell it to you”. This deceptive rhetoric would be a much tougher sell if some early computer scientists hadn’t happened to name their field “AI”.
Ok. You said LLMs are not AI, I didn’t agree with the nuance. You’re making a big thing out of this.
ML was huge in B2B and still going steady. Not “SVMs as a service”, but you bet sales teams were letting everybody know that their solutions learn. You can find loads of conference material about “why ML is better than AI” from a decade ago. They pivoted to calling it AI again of course, even if the product didn’t change.