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THE VIDEO SHELF · bioelectricity and regeneration

What Bodies Think About: Bioelectric Computation Outside the Nervous System - NeurIPS 2018

Michael Levin's NeurIPS 2018 talk on bioelectric computation outside the nervous system, showing how cell electrical networks shape development and regeneration. It covers morphological information processing in living tissue.

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Why HN readers recommended it

HN regularly calls it mind-blowing and recommends it as an introduction to Levin's work on bioelectricity and regeneration.

This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.

Video & recommendation details

Creator / channel
The Artificial Intelligence Channel
Topic
bioelectricity and regeneration
Format
talk
Level
intermediate
HN recommenders in dataset
12
HN mentions in dataset
20
Recommendation years in dataset
2018–2024

These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.

From the original HN conversations

Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.

  • Was recently floored by Michael Levin's (one of this papers authors) talk at NIPS. Possibly the most amazing talk I have ever seen. [VIDEO]

    leesec on Hacker News · 2018-12
    In On Having No Head: Cognition Throughout Biological Systems (2016)

  • What bodies think about - by Michael Levin at NeurIPS 2018. [VIDEO] I dont really know anything about biology, but this piqued my interest.One of the most interesting talks of 2018.

    gt5050 on Hacker News · 2018-12
    In Ask HN: Best talks of 2018?

  • Recent but great talk posted here, What Bodies Think About: Bioelectric Computation Outside the Nervous System [1] by Prof. Michael Levin. He talks about how long term low energy electrical networks between all cells in living organisms shape how the organism grows. I think what …

    aeleos on Hacker News · 2018-12
    In Ask HN: Best talks of 2018?

Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.

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