It's always been acknowledged that various disciplines had significant crossover, e.g. ML and operations research, but I've never seen anyone claim that optimization is AI until recently.
Ian Goodfellow's book is, what, 10 years old at this point? The fundamentals in that book cover all of ML from classical to deep learning, and pretty clearly enumerate the different components necessary to do ML, and there's no doubt that optimization is one of them. But to say that it is AI in the way that most people would probably understand it? It's a stretch, and hinges on whether you're using AI to refer to the collection of techniques or the discipline, as opposed to the output (i.e. the "intelligence"). I, and I'd argue most people, use AI to refer to the latter, but I guess the distinction between the discipline and the product is vague enough for media hype.
And to be clear, I'm not trying to take away from the authors. Optimization is one of the tools I like to throw around, both in my own projects and professionally. I love seeing cool applications of optimization, and this definitely qualifies. I just don't agree that everything that uses optimization is AI, because it's an unnecessary blurring of boundaries.
I'm actually getting old and grumpy. And I'm talking about common usage since I was an undergraduate taking AI courses 30+ years ago and surveying CS literature, some of which predated my courses by another 10-30 years... I recall one visiting professor who was an "AI researcher" at NASA, and his work was planners and optimizers for spacecraft operations.
But getting back to the basic point: there is a semantic difference of having a grammatical article, which for others here carries more significance than you seem to admit. "Artificial intelligence" vs "An artificial intelligence".
It's always been acknowledged that various disciplines had significant crossover, e.g. ML and operations research, but I've never seen anyone claim that optimization is AI until recently.
Ian Goodfellow's book is, what, 10 years old at this point? The fundamentals in that book cover all of ML from classical to deep learning, and pretty clearly enumerate the different components necessary to do ML, and there's no doubt that optimization is one of them. But to say that it is AI in the way that most people would probably understand it? It's a stretch, and hinges on whether you're using AI to refer to the collection of techniques or the discipline, as opposed to the output (i.e. the "intelligence"). I, and I'd argue most people, use AI to refer to the latter, but I guess the distinction between the discipline and the product is vague enough for media hype.
And to be clear, I'm not trying to take away from the authors. Optimization is one of the tools I like to throw around, both in my own projects and professionally. I love seeing cool applications of optimization, and this definitely qualifies. I just don't agree that everything that uses optimization is AI, because it's an unnecessary blurring of boundaries.