it took a while, but it allowed building models of things previously unmodelable. I do think it’s a good representation of how economic transformations from new technology take so long that you can’t get a clear immediate causal economic signal from a new technology’s introduction, usually.
If you look at the blog posts [2] coming out of Meta’s Reality Labs, they place a heavy emphasis on “ultra-low-friction input and adaptive interfaces powered by contextualized AI”. Consumer hardware [1] already has GPUs for graphics performance and Neural Engines for video analysis and image processing. With the WebGPU API [3] launching this year, high-performance general-purpose GPU compute will be available in the browser. Traditionally, it has been difficult to create high production quality interactive visualizations [4], but with the power of generative AI, the skill ceiling for becoming a creator drops a lot. 3D/VR/AI data analysis would indeed qualify as a mathematical microscope [7], allowing us to better understand measurements of complex phenomena. The development of transformative tools for thought [6] is one of the primary promises of current models, with future “next-action prediction” models enabling an “AI Workforce” (can’t link to this one since the source is not public), and the largest platforms will shift from recommendation to generation [5].
Hmm. Interesting results, agreed on all points except the video, and that video is great, but I think you’ve misunderstood somewhat if you interpreted wavelets as an example of ai; they’re a tiny component. Very good video, and it does give an intuition for why ai could be microscope-like, but ai is incredibly much larger than that.
it took a while, but it allowed building models of things previously unmodelable. I do think it’s a good representation of how economic transformations from new technology take so long that you can’t get a clear immediate causal economic signal from a new technology’s introduction, usually.
If you look at the blog posts [2] coming out of Meta’s Reality Labs, they place a heavy emphasis on “ultra-low-friction input and adaptive interfaces powered by contextualized AI”. Consumer hardware [1] already has GPUs for graphics performance and Neural Engines for video analysis and image processing. With the WebGPU API [3] launching this year, high-performance general-purpose GPU compute will be available in the browser. Traditionally, it has been difficult to create high production quality interactive visualizations [4], but with the power of generative AI, the skill ceiling for becoming a creator drops a lot. 3D/VR/AI data analysis would indeed qualify as a mathematical microscope [7], allowing us to better understand measurements of complex phenomena. The development of transformative tools for thought [6] is one of the primary promises of current models, with future “next-action prediction” models enabling an “AI Workforce” (can’t link to this one since the source is not public), and the largest platforms will shift from recommendation to generation [5].
[1] Apple unveils MacBook Pro featuring M2 Pro and M2 Max—Apple
[2] Inside Facebook Reality Labs: Wrist-based interaction for the next computing platfor
[3] Origin Trials (chrome.com)
[4] Explorable Explanations
[5] Instagram, TikTok, and the Three Trends – Stratechery by Ben Thompson
[6]Introducing our first investments · OpenAI Startup Fund
[7]
Hmm. Interesting results, agreed on all points except the video, and that video is great, but I think you’ve misunderstood somewhat if you interpreted wavelets as an example of ai; they’re a tiny component. Very good video, and it does give an intuition for why ai could be microscope-like, but ai is incredibly much larger than that.