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Bernie Sanders spoke to AI agent Claude
(www.youtube.com)
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this post was submitted on 20 Mar 2026
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Technology
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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.