An explosion by definition happens in a very short period of time. How long is supposed to be this explosion we already are? It reads like a Tom Clancy book.

LLMs seem quite similar to the part of the human brain where you speak quickly without thinking. They don't do the thinking and learning bit that brains do well though. Something needs to be changed or added on I guess.

Can artificial intelligence truly become wise? In this landmark lecture, John Vervaeke explores the future of AI through a lens few dare to examine: the limits of intelligence itself. He unpacks the critical differences between intelligence, rationality, reasonableness, and wisdom—terms often used interchangeably in discussions around AGI. Drawing from decades of research in cognitive science and philosophy, John argues that while large language models like ChatGPT demonstrate forms of generalized intelligence, they fundamentally lack core elements of human cognition: embodiment, caring, and participatory knowing.

By distinguishing between propositional, procedural, perspectival, and participatory knowing, he reveals why the current paradigm of AI is not equipped to generate consciousness, agency, or true understanding. This lecture also serves as a moral call to action: if we want wise machines, we must first become wiser ourselves.

00:00 Introduction: AI, AGI, and the Nature of Intelligence 02:00 What is General Intelligence? 04:30 LLMs and the Illusion of Generalization 07:00 The Meta-Problems of Intelligence: Anticipation & Relevance Realization 09:00 Relevance Realization: The Hidden Engine of Intelligence 11:30 How We Filter Reality Through Relevance 14:00 The Limits of LLMs: Predicting Text vs. Anticipating Reality 17:00 Four Kinds of Knowing: Propositional, Procedural, Perspectival, Participatory 23:00 Embodiment, Consciousness, and Narrative Identity 27:00 The Role of Attention, Care, and Autopoiesis 31:00 Culture as Niche Construction 34:00 Why AI Can’t Participate in Meaning 37:00 The Missing Dimensions in LLMs 40:00 Rationality vs. Reasonableness 43:00 Self-Deception, Bias, and the Need for Self-Correction 46:00 Caring About How You Care: The Core of Rationality 48:00 Wisdom: Aligning Multiple Selves and Temporal Scales 53:00 The Social Obligation to Cultivate Wisdom 55:00 Alter: Cultivating Wisdom in an AI Future

Please don't just link to another video or article without a comment or at least a short description. Why should I watch this 1 hour long video?

o3 pro doesn't have a 1M context window, unfortunately. GPT-4.1 and Gemini 2.5 do, though.

Thats nice to know.

What's that got to do with this post though.

Patel isn't saying that AGI is still very, very far away. He says his best estimate is 2032 and "ASI" in 2028 is "a totally plausible outcome".

(He thinks it might be quite a long way away: "the 2030s or even the 2040s", and it seems to me that the "2040s" scenarios are ones in which substantially longer than that is also plausible.)

Maybe - anecdotally, HN at least is not very receptive to the idea that transformers are not (or with more data will never be) sentient somehow, and almost every post I see about this is followed up by the idiotic "how do we know human intelligence isn't the same thing", as if there's some body of commentators whose personal experience with consciousness somehow leads them to believe it might be achievable with matrix math.

Anyway, I don't think we're over the peak yet, the tech adjacent pseudo intellectuals that feed these bubbles (VCs etc) still very much think that math that generates a plausible transcript is alive.