betse
CfC
| betse | CfC | |
|---|---|---|
| 4 | 7 | |
| 51 | 796 | |
| - | - | |
| 4.7 | 10.0 | |
| 6 months ago | over 1 year ago | |
| Python | Python | |
| BSD 2-clause "Simplified" License | Apache License 2.0 |
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betse
- New neural network architecture inspired by neural system of a worm
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What ever happened to the first cryogenically frozen humans?
Jeanne Louise Calment lived 122 years and 164 days [1]. Doubling the lifespan, 240+ years, is most certainly not possible, not reasonable, using diets, exercises, and so forth: if it were, we would have already been there. Even if we could push the body using current technology, no one will want to live 100+ years (from age 70 to 160+) as an old person, being in pain constantly, fighting all kinds of cancers.
Therefore, the only way I can see a lifespan push, not only x2, but x10, or even x100 (10,000 years—once you get x3/x4, it probably scales trivially) is through 100% organ regeneration and 100% programmatic control over the morphospace. Broke an arm? Amputate the limb and grow another one back, your cells already did it before. Liver cancer? Regrow another liver. Heart issues? Make another heart. Spend all the years above 35 as a perpetual 35 year old, eventually in the bodyshape of Chris Hemsworth/Margot Robbie (to keep the examples in Australia). This scientific fancy is somehow grounded in the mind-enlarging perspectives coming from Dr. Michael Levin's lab [2]. Personally, I believe enough in their thesis, programmatic control over cells, that I started learning about their work, BETSE, Bio Electric Tissue Simulation Engine [3], and try to build on top a BioElectric Simulation Orchestrator, BESO [4]. Most probably, however, we won't see 100% human organ regeneration in our regular lifetimes, but never say never.
[1] https://en.wikipedia.org/wiki/Jeanne_Calment
[2] Speaking with Cells: the Electrical Future of Regenerative Medicine with Dr. Michael Levin https://www.youtube.com/watch?v=RzGaakopAKU
[3] https://github.com/betsee/betse
[4] https://github.com/daysful/beso
- Betse: Bio Electric Tissue Simulation Engine
- From Wound Healing to Regeneration
CfC
-
LNNs - Liquid Neural Networks: Seeking general advice, papers, implementations
And here's the repo: https://github.com/raminmh/CfC
- Researchers Discover a More Flexible Approach to Machine Learning
- New neural network architecture inspired by neural system of a worm
-
I keep getting several errors when running Pytorch
We tried to run this code taken from Github but we keep getting these errors in Pytorch:
- MIT solved a century-old differential equation to break 'liquid' AI's computational bottleneck
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Solving brain dynamics gives rise to flexible machine learning models
All code and materials used in the analysis are openly available at https://github.com/raminmh/CfC under an Apache 2.0 license for the purposes of reproducing and extending the analysis (https://doi.org/10.5281/zenodo.7135472).
So it seems to be pretty current.
What are some alternatives?
beso - BioElectric Simulation Orchestrator
android-file-transfer-linux - Android File Transfer for Linux (and macOS!)
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
liquid_time_constant_networks - Code Repository for Liquid Time-Constant Networks (LTCs)
tequila - A High-Level Abstraction Framework for Quantum Algorithms