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A Camera, Not an Engine
A Camera, Not an Engine
Modern AI puts us firmly into an age of exploration of computational reality
But why stop with datasets that induce languages with “grammars” that can be rendered legible to us? Could you make a “Large Solar Flares and Sunspots Model” (LSFASM) and learn to talk to the Sun and ask it where it might flare up next? How about a Large Oceanic Model that allows ships to talk to ocean currents? Or a Large History Model that works as a Prime Radiant for Asimovian psychohistory? Maybe a Large Climate Model constructed out of weather data can talk to us and supply strategies for climate change?
One reason it is hard is, once again, our tendency to mistake discoveries for inventions, or equivalently, cameras for engines. Instruments of discovery measure more than they are measured. Yes, there are a number of ways you can measure a telescope (mirror diameter or focal length for example), but the interesting measuring going on is what the telescope is doing to what it’s turned towards (the analogy to AI here is perhaps to things like floating-point precision — that’s closer to mirror diameter).
A Camera, Not an Engine
Unbundling AI — Benedict Evans
Unbundling AI — Benedict Evans
ChatGPT and LLMs can do anything (or look like they can), so what can you do with them? How do you know? Do we move to chat bots as a magical general-purpose interface, or do we unbundle them back into single-purpose software? What are the products?
Unbundling AI — Benedict Evans
Elegant and powerful new result that seriously undermines large language models
Elegant and powerful new result that seriously undermines large language models
Wowed by a new paper I just read and wish I had thought to write myself. Lukas Berglund and others, led by Owain Evans, asked a simple, powerful, elegant question: can LLMs trained on A is B infer automatically that B is A? The shocking (yet, in historical context, see below, unsurprising) answer is no:
Lukas Berglund and others, led by Owain Evans, asked a simple, powerful, elegant question: can LLMs trained on A is B infer automatically that B is A? The shocking (yet, in historical context, see below, unsurprising) answer is no
Elegant and powerful new result that seriously undermines large language models
Four pathways to an AI culture | Barcelona Metròpolis | Barcelona City Council
Four pathways to an AI culture | Barcelona Metròpolis | Barcelona City Council
Creative skills can currently be reproduced using deep learning and neural networks, but their true potential lies in the prospects of collaboration rather than replacement. Two distinct subjectivities, one human and one automated, can meet halfway and produce a captivating mutual symbolic space, brimming with possibilities, but also with dead ends. It is both too early and arrogant to hazard a guess as to the artistic impact AI will exert in the medium term.
Four pathways to an AI culture | Barcelona Metròpolis | Barcelona City Council
Shadow Visions — Ding Magazine
Shadow Visions — Ding Magazine
The eye doctor shined a bright light into my left eye as I realized, I have stopped thinking of the future. The day was hot, the air dry. I was slowly and surely going blind, from a progressive, incurable eye disease. On my way home, I could smell wildfire smoke. Shadows trailed the edges of... Read more »
Shadow Visions — Ding Magazine