Lifeboat Foundation

In this introduction to quantum consciousness, Justin Riddle presents six arguments that quantum consciousness is an important theory of mind.\
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To summarize them briefly, People always identify as their latest technology and so most people believe that they are a digital computer. Time to update those models of self, because… Quantum computers are here. We wouldn’t want the brick of metal in our pocket to have greater computational power than our brain. People say the brain is too warm, wet, and noisy for quantum effects; yet, evidence keeps emerging for quantum effects in biology (such as photosynthesis). Where do we draw the line? Evolution might be selecting for quantum systems that can maintain quantum coherence. The debate around the role of quantum mechanics in consciousness has been raging for 100 years. Many key historical figures like Bohr, Schrodinger, Heisenberg, von Neumann entertained the idea that quantum mechanics might relate to our mind. Physical theories that are purely deterministic have failed to account for key aspects of subjective experience. There may be novel answers from a perspective that incorporate new physics.\
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0:00 Introduction\
1:26 1. People identify as their latest technology\
4:07 2. Quantum computers are here\
7:30 3. Biology utilizes quantum properties\
12:00 4. Evolution selects for quantum systems\
14:10 5. Historical precedent for quantum consciousness\
16:30 6. Failure of physical theories to explain\
a. Sense of self\
b. Freewill\
c. Meaning\
21:07 Outro\
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#quantum\
#consciousness\
#philosophy\
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Website: www.justinriddlepodcast.com\
Email: justinriddlepodcast@gmail.com\
Twitter: @JRiddlePodcast\
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Music licensed from and created by Baylor Odabashian. BandCamp: @UnscrewablePooch\
Painting behind me by Paul Seli. IG: @paul.seli.art\
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Relevant external link:\
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A new biohybrid computer combining a “brain organoid” and a traditional AI was able to perform a speech recognition task with 78% accuracy — demonstrating the potential for human biology to one day boost our computing capabilities.

The background: The human brain is the most energy efficient “computer” on Earth — while a supercomputer needs 20 mega watts of power to process more than a quintillion calculations per second, your brain can do the equivalent with just 20 watts (a megawatt is 1 million watts).

This has given researchers the idea to try boosting computers by combining them with a three-dimensional clump of lab-grown human brain cells, known as a brain organoid.

Though highly capable – far outperforming humans in big-data pattern recognition tasks in particular – current AI systems are not intelligent in the same way we are. AI systems aren’t structured like our brains and don’t learn the same way.

AI systems also use vast amounts of energy and resources for training (compared to our three-or-so meals a day). Their ability to adapt and function in dynamic, hard-to-predict and noisy environments is poor in comparison to ours, and they lack human-like memory capabilities.

Our research explores non-biological systems that are more like human brains. In a new study published in Science Advances, we found self-organising networks of tiny silver wires appear to learn and remember in much the same way as the thinking hardware in our heads.

How the brain adjusts connections between #neurons during learning: this new insight may guide further research on learning in brain networks and may inspire faster and more robust learning #algorithms in #artificialintelligence.

Researchers from the MRC Brain Network Dynamics Unit and Oxford University’s Department of Computer Science have set out a new principle to explain how the brain adjusts connections between neurons during learning. This new insight may guide further research on learning in brain networks and may inspire faster and more robust learning algorithms in artificial intelligence.

The essence of learning is to pinpoint which components in the information-processing pipeline are responsible for an error in output. In artificial intelligence, this is achieved by backpropagation: adjusting a model’s parameters to reduce the error in the output. Many researchers believe that the brain employs a similar learning principle.

Continue reading “New insight into how brain adjusts synaptic connections during learning may inspire more robust AI” »

Scientists at the Max Planck Institute have developed a synthetic pathway that can capture CO₂ from the air more efficiently than in nature, and shown how to implement it into living bacteria. The technique could help make biofuels and other products in a sustainable way.

Plants are famous for their ability to convert carbon dioxide from the air into chemical energy to fuel their growth. With way too much CO₂ in the atmosphere already and more being blasted out every day, it’s no wonder scientists are turning to this natural process to help rein levels back in, while producing fuels and other useful molecules on the side.

In the new study, Max Planck scientists developed a brand new CO₂-fixation pathway that works even better than nature’s own tried-and-true method. They call it the THETA cycle, and it uses 17 different biocatalysts to produce a molecule called acetyl-CoA, which is a key building block in a range of biofuels, materials and pharmaceuticals.

Watch behind the scenes, get early access and join the private Discord by supporting us on Patreon: \
/ mlst (public discord)\
/ discord \
/ mlstreettalk \
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DOES AI HAVE AGENCY? With Professor. Karl Friston and Riddhi J. Pitliya\
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Agency in the context of cognitive science, particularly when considering the free energy principle, extends beyond just human decision-making and autonomy. It encompasses a broader understanding of how all living systems, including non-human entities, interact with their environment to maintain their existence by minimising sensory surprise.\
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According to the free energy principle, living organisms strive to minimize the difference between their predicted states and the actual sensory inputs they receive. This principle suggests that agency arises as a natural consequence of this process, particularly when organisms appear to plan ahead many steps in the future. \
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Riddhi J. Pitliya is based in the computational psychopathology lab doing her Ph.D at the University of Oxford and works with Professor Karl Friston at VERSES. \
/ riddhijp \
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References:\
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THE FREE ENERGY PRINCIPLE—A PRECIS [Ramstead]\
https://www.dialecticalsystems.eu/con…\
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Active Inference: The Free Energy Principle in Mind, Brain, and Behavior [Thomas Parr, Giovanni Pezzulo, Karl J. Friston]\
https://direct.mit.edu/books/oa-monog…\
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The beauty of collective intelligence, explained by a developmental biologist | Michael Levin\
• The beauty of collective intelligence… \
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Growing Neural Cellular Automata\
https://distill.pub/2020/growing-ca\
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Carcinisation\
https://en.wikipedia.org/wiki/Carcini…\
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Prof. KENNETH STANLEY — Why Greatness Cannot Be Planned\
• #038 — Prof. KENNETH STANLEY — Why Gr… \
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On Defining Artificial Intelligence [Pei Wang]\
https://sciendo.com/article/10.2478/j…\
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Why? The Purpose of the Universe [Goff]\
https://amzn.to/4aEqpfm\
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Umwelt\
https://en.wikipedia.org/wiki/Umwelt\
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An Immense World: How Animal Senses Reveal the Hidden Realms [Yong]\
https://amzn.to/3tzzTb7\
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What’s it like to be a bat [Nagal]\
https://www.sas.upenn.edu/~cavitch/pd…\
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COUNTERFEIT PEOPLE. DANIEL DENNETT. (SPECIAL EDITION)\
• COUNTERFEIT PEOPLE. DANIEL DENNETT. (… \
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We live in the infosphere [FLORIDI]\
• WE LIVE IN THE INFOSPHERE [Prof. LUCI… \
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Mark Zuckerberg: First Interview in the Metaverse | Lex Fridman Podcast #398\
• Mark Zuckerberg: First Interview in t… \
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Black Mirror: Rachel, Jack and Ashley Too | Official Trailer | Netflix\
• Black Mirror: Rachel, Jack and Ashley… \
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Prof. Kristinn R. Thórisson\
https://en.wikipedia.org/wiki/Kristin…

UCLA department of integrative biology and physiologyluskin endowment for leadership symposiumpushing the boundaries: neuroscience, cognition, and lifemarta…

UCLA Department of Integrative Biology and PhysiologyLuskin Endowment forLeadership SymposiumPushing the Boundaries: Neuroscience, Cognition, and LifeKarl Fris…

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