Name: A Thousand Brains
ISBN: 9781541675810

A Thousand Brains

author, neuroscientist, and computer engineer unveils a theory of intelligence that will revolutionize our understanding of the brain and the future of AI For all of neuroscience's advances, we've made little progress on its biggest question: How do simple cells in the brain create intelligence? Jeff Hawkins and his team discovered that the brain uses maplike structures to build a model of the world-not just one model, but hundreds of thousands of models of everything we know. This discovery allows Hawkins to answer important questions about how we perceive the world, why we have a sense of self, and the origin of high-level thought. A Thousand Brains heralds a revolution in the understanding of intelligence. It is a big-think book, in every sense of the word.

What Hacker News says

moonuJun 2026

My favorite explanation for what consciousness is one I read in a Thousand Brains, I found it quite elegant. It posited that consciousness is a natural derivation of embodiment + memory + the ability to create reference frames (which the book lays forth as the fundamental basis by which our brains work). Essentially, the idea is that just as we create reference frames to understand the world around us, because of memory, we begin to develop one for ourselves as well. Because of this, without a more integrated memory (built into weights), it seems unlikely that LLMs might "gain" consciousness.

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whattheheckheckJun 2026

Yeah folks can also look into the Jeff Hawkins and a thousand brains

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ninjagooApr 2026

>> If you pay attention to cats, you figure out they are fuzzy little “difference engines.”

> That must be a mechanism in the brain rather than the eye

Check out "A Thousand Brains: A New Theory of Intelligence" [1] by Jeff Hawkins [2], of PalmPilot fame. This theory postulates, in part, and with evidence, that brains are continuously comparing sensory input and movement context with learned models. I found the book to be mind-blowing, so to speak ...

[1] https://www.amazon.com/Thousand-Brains-New-Theory-Intelligen...

[2] https://en.wikipedia.org/wiki/Jeff_Hawkins

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K0SM0SAug 2024

Agreed.

Anecdotal (but deep) research led me to postulate that our entire "inner world", for lack of a better word, is an emergent construction based on a fundamentally spatiotemporal encoding of the external world. This assumes that feeding and motility, i.e., a geometric interpretation of the external world, is among the first 'functions' of living organisms in the evolutionary order. They subsequently became foundational for neuronal systems when these appeared about 500 million years ago.

The hypothesis was informed by language notably, where most things are defined in spatial terms and concepts (temporal too, though more rarely), as if physical experiences of the world were the building blocks of thinking, really. A "high" council, a "sub" culture, a "cover", an "adjacent" concept, a "bigger" love, a "convoluted" or "twisted" idea, etc.

Representations in one's inner world are all about shape, position, and movement of things in some abstract space of sorts.

This is exactly how I'd use a 4D modeling engine to express a more 'Turing-complete' language, a more comprehensive experience (beyond movement: senses, intuitions, emotions, thoughts, beliefs…): use its base elements as a generator set to express more complex objects through composition in larger and/or higher-dim space. Could nature, Evolution, have done just that? Iteratively as it conferred survival advantages to these genes? What would that look like for each layer of development of neuronal—and later centralized "brain"—systems?

Think as in geometric algebra, maybe; e.g., think how the metric of a Clifford algebra may simply express valence or modality, for those neuronal patterns to trigger the proper neurotransmitters. In biological brains, we've already observed neural graphs up to 11 dimensions (with a bimodal distribution peak around ~2.5D and ~3.8D iirc… Interestingly for sure, right within the spatiotemporal ballpark, seeing as we experience the spatial world in 2.5D more than 3, unlike fishes or birds).

Jeff Hawkins indeed strongly shaped my curiosity, notably in "A Thousand Brains" and subsequent interviews. The paper here immediately struck me as very salient to that part of my philosophical and ML research—so kinda not too surprised there's history there.

And I'm really going off on a tangent here, but I'm pretty sure the "tokenization problem" (as expressed by e.g. Karpathy) may eventually be better solved using a spatiotemporal characterization of the world. Possibly much closer to real-life language in biological brains, for the above reasons. Video pretraining of truly multimodal models may constitute a breakthrough in that regard, perhaps to synthesize or identify the "ideal" text divisions, a better generator set for (any) language.

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bun_at_workMar 2024

I have a similar view to you and not much to add to your comment, other than to reference a couple books that you might like if you enjoyed 'Thinking, Fast and Slow'.

'The Righteous Mind' by Jonathan Haidt. Here, Haidt describes a very similar 2-system model he describes as the Elephant-rider model.

'A Thousand Brains: A New Theory of Intelligence' by Jeff Hawkins. Here Jeff describes his Thousand Brains theory, which has commonality with the 2-system model described by Kahneman.

I think these theories of intelligence help pave the way for future improvements on LLMs for sure, so just want to share.

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metanonsenseJan 2024

You should read „A thousand brains“ by Jeff Hawkins (if you haven’t already done so). A large part of their theory is that the brain has evolved to orient and move in a 3D world and that this is the basis of our abstract thinking.

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