Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: computing – Page 303

Agency, Attractors, & Observer-Dependent Computation in Biology & Beyond

Michael Levin discusses his 2022 paper “Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework for Understanding Diverse Bodies and Minds” and his 2023 paper with Joshua Bongard, “There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-scale Machines.” Links to papers flagged 🚩below.

Michael Levin is a scientist at Tufts University; his lab studies anatomical and behavioral decision-making at multiple scales of biological, artificial, and hybrid systems. He works at the intersection of developmental biology, artificial life, bioengineering, synthetic morphology, and cognitive science.

❶ Polycomputing (observer-dependent)
1:59 Outlining the discussion.
3:50 My favorite comment from round 1 interview.
5:00 What is polycomputing?
8:50 An ode to Richard Feynman’s “There’s plenty of room at the bottom“
11:10 How/when was this discovered? Reductionism, causal power…
14:40 “It’s a view that steps away from prediction.“
16:20 From abstract: Polycomputing is the ability of the same substrate to simultaneously compute different things *but emphasis on the observer(s)*
17:05 What’s an example of polycomputing?
19:40 They took a different approach and actually did experiments with gene regulatory networks (GRNs)
23:18 Different observers extract different utility from the exact same system.
26:35 Spatial causal emergence graphs (determinism, degeneracy) | Erik Hoel’s micro/macro & effective information.
29:25 Inventiveness of John Conway’s Game of Life.

❷ Technological Approach to Mind Everywhere.
34:20 Tell me 3 things to determine intelligence (ball vs mouse on a hill)
39:50 Jeff Hawkins’ Thousand Brains Theory.
41:05 Agency is not binary, continuum of persuadability.
44:50 Where’s the bottom of agency? Plants & insects far off from 0
46:55 What is the absolute minimum amount of agency? Some degree of goal directed behavior & indeterminacy…
51:05 Life is a system good at scaling.
51:41 “To me, our world doesn’t have 0 agency anywhere.“
53:50 As an engineer, what can I take advantage of?
55:00 Surely you don’t think the weather has any intelligence to it…

❸ Attractor Landscapes.
58:35 Homeostatic loops, morphological spaces, attractor landscapes.
1:00:35 “Of course we’re living in a simulation!“
1:06:45 Attractor landscapes, topography, anatomical morphous space (D’Arcy Thompson)
1:12:28 Planaria stochastic, probability of head shape proportional to evolutionary distance between species.
1:15:15 What is the secret of the universe? Attractor landscapes, quantum fields, black holes.
1:19:05 We need a new system of ethics for unconventional minds.

🚾 Works Cited.

Continue reading “Agency, Attractors, & Observer-Dependent Computation in Biology & Beyond” | >

Future computers could be built using proteins that make up cells

Future computers could be built smaller than ever before using the tiny biological skeletons that hold our cells together.

That’s according to one team of scientists, who have devised a way to make computer chips using cytoskeletons — protein scaffolds that give cells their shape.

They claim that the silicon chips that brought computers to the masses in the 1980s are soon to be a thing of the past.

Nano-Biological Computing — Quantum Computer Alternative!

Subscribe here: https://goo.gl/9FS8uF
Check out the previous episode: https://www.youtube.com/watch?v=X5lpOskKF9I
Become a Patreon!: https://www.patreon.com/ColdFusion_TV

Here it is, the bio computer. A new type of parallel computing method that could rival the infamous quantum computer at a much lower price while being more practical to boot.

Hi, welcome to ColdFusion (formally known as ColdfusTion).
Experience the cutting edge of the world around us in a fun relaxed atmosphere.

Sources:

http://www.mind.ilstu.edu/curriculum/nature_of_computers/computer_types.php.

http://www.lunduniversity.lu.se/

Continue reading “Nano-Biological Computing — Quantum Computer Alternative!” | >

A new protocol to reliably demonstrate quantum computational advantage

Quantum computers, devices that perform computations by exploiting quantum mechanical phenomena, have the potential to outperform classical computers on some tasks and optimization problems. In recent years, research teams at both academic institutions and IT companies have been trying to realize this predicted better performance for specific problems, which is broadly known as “quantum advantage.”

To reliably demonstrate that a quantum computer performs better than a classical computer, one should, among other things, collect inside the computer and compare them to those collected in . Doing this, however, can sometimes be challenging, due to the distinct nature of these two types of devices.

Researchers at NIST/University of Maryland, UC Berkeley, Caltech and other institutes in the United States recently introduced and tested a new protocol that could help to reliably validate the advantage of quantum computers. This protocol, introduced in Nature Physics, relies on mid-circuit measurements and a cryptographic technique.

Quantum simulator helps to unlock a major science mystery

A new study exemplifies how the strides made in quantum computing are now being harnessed to unlock the secrets of fundamental science.

Scientists at Duke University have harnessed the power of quantum-based methods to unravel a puzzling phenomenon related to light-absorbing molecules, according to a new study published in Nature Chemistry.

This advancement sheds light on the enigmatic world of quantum interactions, potentially transforming our understanding of essential chemical processes like photosynthesis, vision, and photocatalysis.

Intel makes new chip more than double the power of others

In a bid to reduce data center power consumption, Intel has unveiled its new “Sierra Forest” chip with over double the power efficiency of other chips.

Intel has reported that its new chip, “Sierra Forest,” will have over double the efficiency for the same power consumption of other microchips. Designed as a new data center chip, Intel’s new double-efficiency chip is scheduled for release sometime in 2024, Reuters.

Da-kuk/iStock.

Double efficiency; same power.

Quantum device used to slow chemical reaction 100 billion times

A team of researchers has successfully simulated and” observed” a slow-motion chemical reaction at a billion times slower than “normal.”

For the first time ever, scientists have succeeded in slowing down (in simulation) a chemical reaction by around 100 billion times. Using a quantum computer, the researchers simulated and then “observed” the reaction in super slow motion.

Skynesher/iStock.

Super slow motion.

Memristors make versatile artificial synapses for neuromorphic computing

Most modern computers – from primitive room-filling behemoths like the ENIAC to the smartphone in your pocket – are built according to a set of principles laid out by the mathematician John von Neumann in 1945. This von Neumann architecture, as it is known, incorporates many familiar elements, including a central processing unit, a memory for storing data and instructions, and input and output devices. Despite its ubiquity, though, von Neumann’s model is not the only way of building a computer, and for some applications, it is not the most desirable, either.

One emerging alternative is known as neuromorphic computing. As the name implies, neuromorphic computers are inspired by the architecture of the human brain and use highly connected artificial neurons and artificial synapses to simulate the brain’s structure and functions. For researchers like Le Zhao of China’s Qilu University of Technology, this neuromorphic model offers a fantastic opportunity to develop a new paradigm for computing – as long as we can develop artificial neurons and synapses that have the right properties.

In a recent paper published in Materials Futures, Zhao and colleagues describe how to use a memristor – essentially a switch that “remembers” which electric state it was in, even after its power is turned off – to emulate the function of a synapse in the brain. Here, he explains the team’s goals and plans.