did I mention 2x speed? hit play on many, pause on almost as many.

This is a big list of the youtube videos I find myself linking to people most often. These are all from the same playlist: https://www.youtube.com/playlist?list=PLgx5WuezywJMj_JS47QIqcn8_3UiiEwPs - comment here if you'd like edit access, I give it out readily. I'd love to have people moving the most important and insightful videos towards the beginning. I'd also love to see people clone the playlist and just make their own version.

These vary wildly in topic and difficulty level. I generally do not try to avoid watching things above my level, I just use it as inspiration for how to fill in what I'm missing. If something sounds basic to you, it probably is.

Many of these videos are quite short, many are quite long.

1min: neuron clip

23min: neuroscience overview (bio neuron interpretation)

or 10min with 2x speed!

10min: overview of learning techniques (bit clickbaity title but I include because I like it plenty anyhow)

or 5min with 2x speed!

2min: visual intuition - details of how one particular chaotic fluid flow move

11min: research talk on what collective intelligence is. (see also many more cool talks from MITCBMM!)

or 5min with 2x speed!

2min: visualization of a volume of neurons in a (mouse?) amygdala

8min: cognitive biases in practice

33min: absolutely incredible visual intro to physics sims focusing towards fluid simulation

or 15min with 2x speed!

15min: cs101 "ok, but what does it mean to abstract over the matter of a computer"

or 7min with 2x speed!

1min: visualization of particle lenia

20min: overview of Michael Levin's research on the bioelectric communication of cells for morphogenesis and morphogenic editing without genetic change

or 10min with 2x speed

11min: cs101 how a neural network is actually just line segments (with relu, anyway)

12min: nice intro to what chaos theory is actually about

18min: overview of ways visual proofs can mislead

4min: overview of some important additional notes on how to learn efficiently. this playlist does not satisfy them all.

14min: Visual intro to why neural networks work. goes into detail about the geometric interpretation of neural networks.

15min: geometric interpretation of bayes' rule. Useful for intuition building even if you get the math.

See also chris olah's blog post on the same topic from a few years prior.

4min: visualization of atoms that better communicates what the probability fields are fields of.

6min: nice intro to what claim the manifold hypothesis of neural network effectiveness makes about the structure of natural data.

20min: a perspective on why anecdotes are important for natural communication (very rough summary: humans natively think in sequences of embodied events)

20min: intro to the clocks of the brain

43min: visualization of inventing math from only physical shapes

As a strict philosophical materialist, this is what made me start believing in math again ;)

20min on 2x speed!

7min: visualization of one rather narrow simulation of abstract market agents and the effect that interest-bearing loans have on a simulation

There are several more videos in will ruddick's playlists that go over the various configuration changes to this sim, and he also has a version you can try online

35min: more steps through even larger scale abstractions of fluid behavior for simulation

10min: intro to why you'd want to know category theory - all math is secretly category theory (but not an intro to the actual math in detail)

15min: overview of some results from evolutionary game theory

25min: overview of a very common abstract model of phase transitions

37min: rehash of the percolation video but with slightly less grokkable explanation, but then gets into connection to how this exists in brains

16min: overview of what and why regarding physical symmetries

16min: quick intro to graph theory

7min: unnarrated animation showing the behavior of DNA-reading molecules

21min: overview of representation theory and why all math is secretly linear algebra

17min: overview of the brain's spatialized mapping

4min: demonstration of why high dimensionality is weird

17min: intro to dynamical systems lecture from one of the very best lecturers I've ever seen

20min: another overview research talk from MITCBMM

4min: surprisingly educational overview of the path from quantum to chemistry to biochem to cellular, as an at-least-theoretically memorable song parody

15min: intro to the way quantum substrate is different from sound medium

3min: another incredible overview of a field as a song

11min: intro to the mechanistic details of mass being energy

30min: research talk by michael levin on some of the details of communication between cell networks to build body shapes

4min: intro overview of evolutionary developmental biology and modern synthesis as a song

These songs are great openers for a college class on the topics they cover. very worth watching to get a quick rundown of the field. despite being a song. also they're catchy as hell. I can't remember the originals of these songs anymore.

15min: another intro to neural networks from a geometric perspective

7min: another bio behavior stepthrough

5min: another song, this one is about CRISPR-CAS9. Crispr-cas9, bring me a gene!

30min: Overview of why wavelets are much more useful for frequency analysis in neuroscience than fourier transforms

1min: very fast visual introduction to what a normalizing flow (a type of model formulation and training objective) is doing

1h30m: research discussion from the cooperative ai foundation about cultural evolution as a Cooperative AI Generating Algorithm

5min: overview of the biological pathway of neuron communication, in a fair amount of mechanistic and visual detail, for one pathway

36min: a dry but thorough overview of what is known about brain behavior as a sound is heard and processed

1min: chaos visualization

9min: focused visualization of evo game theory around natural selection of altruism 

55min: highly technical overview of key factors of shared variation, basis vectors, of nervous system structure

26min: intro to category theory that actually aims to introduce the math

45min: automatic end-to-end formal verification of RISC-V processors

(risc-v is a new open source initiative to build high end processors with fully open source architecture)


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5 comments, sorted by Click to highlight new comments since: Today at 1:37 PM

I'd recommend this extension that allows you to conveniently watch videos faster than 2x.

Michael Levin's video is wild! I'm speechless.

His research just keeps getting wilder. It's so wild I've begun to really wonder how much he's going to turn out to be right about, but his hypotheses and evidence for them are really quite something.

I am reminded of the debate over "junk DNA" and noncoding RNA, i.e. parts of the genome that get transcribed, but never get translated into protein. The null hypothesis is that neither does anything, they are just there because evolution only optimizes things just enough to work, and so there can be genome sections that don't do anything and RNA transcripts that just get recycled. The maximum hypothesis (I have heard this from Ron Maimon and I think from John Mattick) is that the population of noncoding RNAs in a cell, forms an intelligent state-machine that controls everything the cell does. The current understanding seems to be, that noncoding DNA and noncoding RNA do often matter for cell function, but only as a kind of supplement to the old central dogma (DNA -> RNA -> protein), and most of the time they really are epiphenomenal. 

The standard paradigm for morphogenesis seems to be a combination of genetic regulatory networks and Turing-style self-organization by chemical gradients, causing cell differentiation to occur in the appropriate parts of the embryo. The null hypothesis about "bioelectricity" would be that it's irrelevant. The maximum hypothesis is that the "body electric" is the dominant factor in morphogenesis, and that e.g. limb regeneration is a matter of appropriately shaping electric gradients in tissue at the regeneration site... A unified approach might look at interactions among chemical gradients, electric gradients, and gene expression. The ion channels are important not just because they create the voltages, but they are also involved in chemical signaling. Perhaps there's an interaction with G proteins

yeah I think realistically what we're actually seeing is that interaction networks are neuron-like redundant communication of morphogenic targets, and every cell is a complex redundant state machine which communicates using a variety of methods with neighbors. Bioelectricity is one of those network channels, and due to being able to react fast, is an important one, but chemical signaling will also be involved for slower messages or more precise messages or what have you. it does seem like he's shown strong evidence for bioelectric signaling being probably the dominant cell role tag, with other signaling networks being involved in a different role than bioelectric, though this field isn't where I've gone deep and I'm missing a lot of existing knowledge that probably answers many of these questions.

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