This by no means a definitive list, so don’t @ me! AI is an inescapable subject. There’s obviously an incredible headwind behind the computing progress of the last handful of years — not to mention the usual avarice — but there has also been nearly a century of thought put toward artificial intelligence. If you want to have a more robust understanding of what is at work beneath, say, the OpenAI chat box, pick any one of these texts. Each one would be worth a read — even a skim (this is by no means light reading). At the very least, familiarizing yourself with the intellectual path leading to now will help you navigate the funhouse of overblown marketing bullshit filling the internet right now, especially as it pertains to AGI. Read what the heavyweights had to say about it and you’ll see how many semantic games are being played while also moving the goalposts. Steps to an Ecology of Mind (1972) — Gregory Bateson. Through imagined dialogues with his daughter, Bateson explores how minds emerge from systems of information and communication, providing crucial insights for understanding artificial intelligence. The Sciences of the Artificial (1969) — Herbert Simon examines how artificial systems, including AI, differ from natural ones and introduces key concepts about bounded rationality. The Emperor’s New Mind (1989) — Roger Penrose. While arguing against strong AI, provides valuable insights into consciousness and computation that remain relevant to current AI discussions. Gödel, Escher, Bach: An Eternal Golden Braid (1979) — Douglas Hofstadter weaves together mathematics, art, and music to explore consciousness, self-reference, and emergent intelligence. Though not explicitly about AI, it provides fundamental insights into how complex cognition might emerge from simple rules and patterns. Perceptrons (1969) — Marvin Minsky & Seymour Papert. This controversial critique of neural networks temporarily halted research in the field but ultimately helped establish its theoretical foundations. Minsky and Papert’s mathematical analysis revealed both the limitations and potential of early neural networks. The Society of Mind (1986) — Marvin Minsky proposes that intelligence emerges from the interaction of simple agents working together, rather than from a single unified system. This theoretical framework remains relevant to understanding both human cognition and artificial intelligence. Computers and Thought (1963) — Edward Feigenbaum & Julian Feldman (editors) This is the first collection of articles about artificial intelligence, featuring contributions from pioneers like Herbert Simon and Allen Newell. It captures the foundational ideas and optimism of early AI research. Artificial Intelligence: A Modern Approach (1995) — Stuart Russell & Peter Norvig. This comprehensive textbook defined how AI would be taught for decades. It presents AI as rational agent design rather than human intelligence simulation, a framework that still influences the field. Computing Machinery and Intelligence (1950) — Alan Turing’s paper introduces the Turing Test and addresses fundamental questions about machine intelligence that we’re still grappling with today. It’s remarkable how many current AI debates were anticipated in this work. Cybernetics: Or Control and Communication in the Animal and the Machine (1948) — Norbert Wiener established the theoretical groundwork for understanding control systems in both machines and living things. His insights about feedback loops and communication remain crucial to understanding AI systems.

My thoughts about the Zettelkasten (Slip box) note taking methodology invented by the German sociologist Niklas Luhmann.

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John Gruber has a post about how Google’s search results now require JavaScript[1]. Why? Here’s Google: the change is intended to “better protect” Google Search against malicious activity, such as bots and spam Lol, the irony. Let’s turn to JavaScript for protection, as if the entire ad-based tracking/analytics world born out of JavaScript’s capabilities isn’t precisely what led to a less secure, less private, more exploited web. But whatever, “the web” is Google’s product so they can do what they want with it — right? Here’s John: Old original Google was a company of and for the open web. Post 2010-or-so Google is a company that sees the web as a de facto proprietary platform that it owns and controls. Those who experience the web through Google Chrome and Google Search are on that proprietary not-closed-per-se-but-not-really-open web. Search that requires JavaScript won’t cause the web to die. But it’s a sign of what’s to come (emphasis mine): Requiring JavaScript for Google Search is not about the fact that 99.9 percent of humans surfing the web have JavaScript enabled in their browsers. It’s about taking advantage of that fact to tightly control client access to Google Search results. But the nature of the true open web is that the server sticks to the specs for the HTTP protocol and the HTML content format, and clients are free to interpret that as they see fit. Original, novel, clever ways to do things with website output is what made the web so thrilling, fun, useful, and amazing. This JavaScript mandate is Google’s attempt at asserting that it will only serve search results to exactly the client software that it sees fit to serve. Requiring JavaScript is all about control. The web was founded on the idea of open access for all. But since that’s been completely and utterly abused (see LLM training datasets) we’re gonna lose it. The whole “freemium with ads” model that underpins the web was exploited for profit by AI at an industrial scale and that’s causing the “free and open web” to become the “paid and private web”. Universal access is quickly becoming select access — Google search results included. If you want to go down a rabbit hole of reading more about this, there’s the TechCrunch article John cites, a Hacker News thread, and this post from a company founded on providing search APIs. ⏎ Email :: Mastodon :: Bluesky #generalNotes

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