Donald Hoffman: Brain vs. Computer Representation Debate

Donald Hoffman argues that brains differ fundamentally from computers, being self-organizing systems rather than digital machines.

### Understanding Donald Hoffman's Theory: Brains vs. Computers
* 🧠 Donald Hoffman proposes that our perception of the world is **fundamentally different from reality**, emphasizing that our experiences do not **accurately reflect the true nature of the world**.
* 💻 He argues that the brain should not be viewed as a computer, as the two operate on **fundamentally different principles**; while computers are **digital von Neumann machines**, brains are **self-organizing systems with oscillators**.
* 🔄 The brain's method of processing information is distinct from that of digital computers, leading to a **misunderstanding of what constitutes a computer**.
* 📊 Hoffman explains that although brains can be described as **Turing machines**, they are **more complex and indeterministic**, complicating the simulation of a brain in a digital environment.
* 🔍 Mathematically, it is possible to create mappings between digital computers and brain functions, allowing for **simulations of one within the other**, albeit with **limitations**.
* 📉 The challenge lies in the brain's **indeterministic nature**, making it difficult to maintain **stable models of large digital computers** within its framework.
* ✏ However, by using external tools like pen and paper, we can leverage our brain's capabilities to **run larger simulations of digital computers** by **externalizing memory and determinism**.

um the next thing was Donald Hoffman I by Donald Hoffman's first part of the theory which is typically the world looks nothing like what we experience it as that is obviously the case and the uh second half I don't follow it's a uh

depends on in which way you look at uh what he writes and and spells out so the second part to me is the thing that computers are an inadequate representation of what our brains are doing our brains are not computers they are something else and I think this uh

results from a misunderstanding of what a computer is there so he's driving the intuition here that the computer is a digital von Neumann machine similar to a PC and our brain is not organized in the same way as our personal computers are our brains are self-organizing systems

there are oscillators and they use very different ways of translating the information between the different parts and achieving coherence and so on then our digital computers are but this doesn't mean that they cannot be described as Turing machines the Turing machine is too general for

that thing basically you're looking at a finite state machine that can be used to compute representations and execute control functions and the brain is clearly in that category and what we can show mathematically is that these the different instances of that category are equivalent to each other which means

there are mappings you can take a digital computer and create a simulation of the brain a virtual brain in that digital computer that behaves in the same way in principle and also in principle vice versa so you can create a simulation of a digital computer in a brain

but it's this is much much more difficult because our brain is largely indeterministic so it's hard to get enough determinism from the brain to keep a model of a large digital computer stable in it and so we can only run relatively small

digital computers in our brain but using external tools for instance if you are allowed to use pen and paper we can use our analog or our chaotic and indeterministic brains to run pretty large simulations of digital computers but externalizing the memory and determinism

On Donald Hoffman's theory - @TheoriesofEverything

Joscha Bach Bits

Donald Hoffman's Theory and the limitations of computer analogies for the brain

Hoffman's theory posits that the world doesn't appear as it is experienced.

The speaker finds the second part of Hoffman's theory more challenging to understand.

The speaker argues that the brain's difference from digital computers stems from a misunderstanding of computer architecture.

Brains, unlike typical computers, are self-organizing systems with oscillators and different information translation methods.

Brains and Turing Machines: Mathematical Equivalence and Simulation

Brains can be described as Turing machines, meaning they can compute and execute control functions.

It's possible to simulate a brain on a digital computer and vice versa.

Simulating a large digital computer in the brain is difficult due to the brain's indeterministic nature.

External tools like pen and paper can aid in running larger simulations of digital computers using the brain.