The intellectual poverty extends to the economics. Acemoglu has found that only 4.6 percent of tasks in the economy are currently cost-effective to automate with AI. His estimate for AI’s total productivity impact over the next decade: 0.66 percent. Goldman Sachs projected seven percent in 2023, before we began to see the shape of this thing. McKinsey projects between 0.5 and 3.5 percent annually.

Yeah this is the thing I keep saying and everyone on social media keeps saying "Boo, AI bad."

The reality is that AI presents a very real, very use thing a combination of linear algebra, calculus, and probability. There's lot of use cases for it. For putting it in all those use cases is not undoing the entire economy. We don't need anywhere near the AI data centers that techbros keep saying we need.

Things like Bayes theorem have uses, I hate that it's gotten lumped into AI. Optimization via loss function is incredibly useful in a lot of domains. But none of can one-to-one replace human beings and it's wild watching all these "captains of industry" lose their collective shit.

Someone is catastrophically wrong, and the people spending the money are not the ones with the Nobel Prize.

Yeah, it's the techbros. They're taking really useful mathematical operations and functions and doing neat albeit useless tricks with it. Anyone who understands that actual fundamental math behind these models and does get too carried away with it will tell you, the reason...

Over ninety percent of firms surveyed in 2025 reported no measurable impact on employment or productivity despite a quarter-trillion dollars in AI investment.

is because people are being handed something that they have no idea how to use and the way they're being told to use it, is actually wrong.

Engineers who did the spec for 802.11be (wifi 7) understood the nature of a channel matrix operation in MU-MIMO. Singular value decomposition benefits from vector dot multiplication and gradient descent minimization. This is absolutely perfect for AI, it's dang near what you'd want to use it for. And that's why Wifi 7 routers come with an embedded model and NPU to run the model onboard. 4096-QAM benefits from linear transformations through a Euclidean space. Mass matrix operations to perform those transformations are ideal with AI.

Which is why I hate this notion that we've called these specific, highly useful operations, AI. Because they have way more application than neural networks, but since you have the hardware, Wifi 7 LDPC uses GAANs, because you've got the hardware. MLO and studying the interference in a particular space are also perfect for neural networks.

There are all these uses and honestly it's crazy watching this insanity that is people like OpenAI, Claude, and so on. There's no way they're going to make good on their promises of being able to fire everyone. It just doesn't make any logical sense when you look at the various domains of math that underpin AI.

And maybe that's because, the people who fly off the handle with AI, are people who take this math and see the human brain in those formulas. I think that's wild take, but my understanding of biology is limited. But I feel our brains are bit more complex than a two year study in College Calculus and Linear Algebra. But that's just my, not very well studied in biology, opinion. But I think that's where these people fly off the handle, they see activation equations, ANN layer transformation equations, and what not and think "human brain". And it's that thinking that's drove them to this insanity.

There's no way the AI industry as it is can keep up. It is bound for collapse. But in all of that, the underlying math is still very important and very useful, and maybe that will get relabeled to neural networking or linear optimization? But what we are seeing is a party trick that can be done with these equations and it's apparently a trillion dollar party trick?