> the details are hard to predict What does not feel too risky to predict, though, are some general directions: a) the era of "GPU"-style computing is here to

> the details are hard to predict What does not feel too risky to predict, though, are some general directions: a) the era of "GPU"-style computing is here to stay. During the long era of exponential CPU speedups the architectures of vectorized computing were very niche (HPC). Going forward its clear there are potentially various economically viable "mass-market" applications of linear algebra. This may even change the economics building of silicon chips from the ground up. Which brings us to the other main point, b) the era of algorithmic computing is also just starting. Right now there is an almost maniacal obsession with LLM's. Its not an entirely useless hype as it is trailblazing a path where much else can follow. But conceptually its just one little corner in the vast space of data processing algorithms. While the general direction of travel seems reasonably established (for now), the details of what comes to pass depend a lot both on the aforementioned economics and the governance around the use of algorithms. Thus far the tech industry had a free pass. Its unlikely that this will continue.