This article is from Big Technology, a newsletter by Alex Kantrowitz. You can already see the machine at work. Corporations, politicians, threadbois, and "thought leaders" are probing and prodding, searching desperately for ways to use surging curiosity about all things artificial intelligence to mask problems, gain favor with the public, and monetize attention. This A.I.-PR industrial complex is growing larger and worse than its predecessors--even crypto!--because the technology is making anything seem possible. With so much opportunity, vacuousness fills the gaps, and exploitation follows.

Most of the articles about AI predicting the stock markets focus on a more or less complicated model which tries to predict the move of the next timestep. And almost all of them are just focussing on architecture and layers like LSTM or CNN. But then they are just using the Mean Squared Error (MSE) as a loss function -- and this is a problem and this article shows you why. Assume we have the following Deep Neural Network (DNN) implemented in PyTorch. Note that we use log returns because these should follow more closely a Normal Distribution which is an important detail for this article, as you will find out in a minute.

Can machines (or computers) think? What did Alan Turing have to say to that question? Well, he believed that the question is too "meaningless to answer". "The original question, 'Can machines think?', I believe to be too meaningless to deserve discussion." In other words, how can we even answer that question if we don't really know what thinking actually is in the first place?

In science fiction, the promise or threat of artificial intelligence is tied to humans' relationship to conscious machines. Whether it's Terminators or Cylons or servants like the "Star Trek" computer or the Star Wars droids, machines warrant the name AI when they become sentient--or at least self-aware enough to act with expertise, not to mention volition and surprise. What to make, then, of the explosion of supposed-AI in media, industry, and technology? In some cases, the AI designation might be warranted, even if with some aspiration. Autonomous vehicles, for example, don't quite measure up to R2D2 (or Hal), but they do deploy a combination of sensors, data, and computation to perform the complex work of driving.