Seagull Algorithms and Cloud Computing.

New to me.   Have a strong interest in bird flight and further behavior.   Biomimicry

ACM TECHNEWS

Seagull Algorithms Could Hide Secret to Greener Cloud Computing,  By Fast Company, April 5, 2023

Modeling the motions of seagulls. 

The researchers say that the way seagulls behave when they’re on the hunt for food or prey is one of the most ruthlessly efficient examples of an entity zeroing in on its target, with minimal excess energy expenditure.

British, Chinese, and Austrian researchers say that more sustainable cloud computing systems can be achieved by algorithmically mimicking seagulls' hunting and migration behavior.

The researchers contend a "seagull optimization algorithm" can slash cloud computing's power consumption by 5.5% and its network traffic by 70%.

They said the meta-heuristic algorithm would determine the best locations for virtual machines within a server communications network to optimize network traffic efficiency.

This would mirror the seagulls' ability to stalk and plot a route to prey without colliding with each other.

The researchers believe seagull-based algorithms could reduce the total number of physical supercomputers worldwide, while also cutting the machine-to-machine communications network's power consumption by 80%.

From Fast Company

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Robotic Echolocaton

More examples of biomimicry here and hint at possible mapping application, 

Flying Robot Echolocates Like a Bat to Avoid Hitting Walls,  By New Scientist, February 6, 2023

This drone uses a buzzer and microphone set-up to navigate by echolocation.

A robot using the echolocation technique can make a map of its environment and localize itself at the same time.

Frederike Dümbgen and colleagues at Canada's University of Toronto and the Swiss Federal Institute of Technology, Lausanne have equipped a flying robot to use bat-like echolocation to map its surroundings using a simple microphone and speaker.

The robot’s speaker emits sound bursts infused with a range of frequencies, which bounce off walls and are recorded by the microphone when they come back., An algorithm then uses interference patterns caused by the sound waves to model the environment's surfaces.

The researchers tested the system on a drone rigged with a buzzer and four microphones, and on a wheeled robot with a built-in speaker and microphone. The drone could map walls with up to 2-centimeter (0.7-inch) accuracy from 0.5 meters away when stationary, and with 8-centimeter (3.1-inch) accuracy when airborne.

From New Scientist

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Flying Snakes to Help Design Robots

Always interested in examples of biomimicry ... here an unusual direction.

 Flying Snakes Help Scientists Design Robots

AIP Publishing, December 13, 2022

Researchers at the University of Virginia (UVA) and Virginia Polytechnic Institute and State University modeled the dynamics of flying snakes, in order to design robots that can replicate their gliding motion. Flying snakes undulate side-to-side as they glide from the tops of trees to the ground; the researchers analyzed the reptiles' lift production mechanism using a computational model based on data from high-speed video. The model includes the cross-sectional shape of the snake's body, through which the researchers learned leading edge vortices last longer at the curves in the body before being shed. The researchers hope such insights will improve their understanding of gliding motion, leading to a more optimal design for gliding snake robots.  ... '

Tricking Termites to Generate New Materials

 A new kind of biomimicry

Mimicking Termites to Generate Materials

California Institute of Technology

Ben Peltz,  August 26, 2022

California Institute of Technology (Caltech) scientists have developed a framework for the design of new materials that was inspired by termite nest-building. Caltech's Chiara Daraio said the researchers approached the challenge by considering limited resources, an architectural approach based on local rules. "We created a numerical program for materials' design with similar rules that define how two different material blocks can adhere to one another," she explained. The virtual growth program models the natural growth of biological structures, connecting L-shaped, I-shaped, T-shaped, and +-shaped virtual blocks whose availability is assigned a limit, mimicking the limited resources termites might encounter. The algorithm constructs an architecture on a grid, which can be rendered as two-dimensional or three-dimensional models. ... 

3D-Printed Surfaces Inspired by Nature

Interesting idea, biomimicry directly linked to 3D Printing, then back to human needs.  How deep can this go? 

 3D-Printed Surfaces Inspired by Nature

Ruhr-Universität Bochum (Germany)

Meike Drießen, September 12, 2022

Scientists at Germany's Ruhr-Universität Bochum and Kiel University three-dimensionally (3D)-printed surfaces that mimic the color of blue Morpho butterflies via two-photon polymerization (2PP). The 2PP laser-based printing technology allows 3D processing of photosensitive resins, enabling the generation of complex structures from virtual computer models without the need for support structures. The technology also facilitates high resolution, because single structural features can measure as small as 100 nanometers (billionths of a meter). The researchers produced hierarchically composed micro- and nanometer-scale structures, and the resulting surfaces emulated the butterflies' blue iridescence. ...'

Dead Spiders for Robot Grippers.

 Clever Biomimicry Example.  Necrobiotic use of forms, 

Necrobotics: Dead Spiders Reincarnated as Robot Grippers That microhydraulic gripper you’ve always wanted, thanks to an ex-spider   By EVAN ACKERMAN

Bugs have long taunted roboticists with how utterly incredible they are. Astonishingly mobile, amazingly efficient, super robust, and in some cases, literally dirt cheap. But making a robot that’s an insect equivalent is extremely hard—so hard that it’s frequently easier to just hijack living insects themselves and put them to work for us. You know what’s even easier than that, though?

Hijacking and repurposing dead bugs. Welcome to necrobotics.

Spiders are basically hydraulic (or pneumatic) grippers. Living spiders control their limbs by adjusting blood pressure on a limb-by-limb basis through an internal valve system. Higher pressure extends the limb, acting against an antagonistic flexor muscle that curls the limb when the blood pressure within is reduced. This, incidentally, is why spider legs all curl up when the spider shuffles off the mortal coil: There’s a lack of blood pressure to balance the force of the flexors.

This means that actuating all eight limbs of a spider that has joined the choir invisible is relatively straightforward. Simply stab it in the middle of that valve system, inject some air, and poof, all of the legs inflate and straighten. ... ' 

Scientists emulate Quantum Nature

 Deeper yet Biomimicry, even to quantum?

ACM TECHNEWS  

Scientists Emulate Nature in Quantum Leap Towards Future Computers

By UNSW Sydney Newsroom (Australia), June 24, 2022

Scientists at Australia's University of New South Wales, Sydney (UNSW) have constructed an atomic-scale silicon quantum processor to model the behavior of an organic molecule.

UNSW's Michelle Simmons said the researchers assembled a quantum integrated circuit using a chain of 10 quantum dots to simulate the location of atoms in a chain of polyacetylene.

Simmons said they addressed theoretical physicist Richard Feynman's challenge to emulate nature by building matter at the same length scale in "mimicking the polyacetylene molecule by putting atoms in silicon with the exact distances that represent the single and double carbon-carbon bonds."

The team modeled two distinct strands of the polymer chains and measured electric current passing through them, which matched theoretical predictions.

From UNSW Sydney Newsroom (Australia)

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Brain Has a Built-in System to Keep Unwanted Memories Out

 Potential applications?

The Brain Has a Built-in System to Keep Unwanted Memories Out, Study Finds

By Shelly Fan in SiggularityHub

We all have memories we’d rather forget. Yet too often they bubble up into our consciousness. That gaffe at work or during an interview? A faceplant after slipping on ice on a first date? An accidental reply-all to the whole family? (Cringe).

For most, a quick jab of embarrassment, anger, or fear is all we feel and it quickly dissipates. But for people with post-traumatic disorders (PTSD) or depression, unwanted memories from their trauma can seriously derail their lives.

So how is it that these memories only sometimes invade unsuspecting minds?

A new study in the Journal of Neuroscience has some answers. By scanning the brains of 24 people actively suppressing a particular memory, the team found a neural circuit that detects, inhibits, and eventually erodes intrusive memories.

A trio of brain structures makes up this alarm system. At the heart is the dACC (for “dorsal anterior cingulate cortex”), a scarf-like structure that wraps around deeper brain regions near the forehead. It acts like an intelligence agency: it monitors neural circuits for intrusive memories, and upon discovery, alerts the “executive” region of the brain. The executive then sends out an abort signal to the brain’s memory center, the hippocampus. Like an emergency stop button, this stops the hippocampus from retrieving the memory.

The entire process happens below our consciousness, suppressing unwanted memories so that they never surface to awareness.

But what happens if memories do break into our thoughts? Here, the dACC has another task. When proactive surveillance fails, the brain region increases its alert signal to the executive—think DEFCON1—probing it to further damp down activity in the hippocampus.

“Preventing unwanted memories from coming to mind is an adaptive ability of humans,” wrote the authors, led by Dr. Michael C. Anderson at the University of Cambridge and Dr. Xu Lei at Southwest University in Chongqing, China. .... '

Drone Spotting With Fly Eyes

Biomimicry example

AIs Spot Drones with Help from Fly Eye

Scientific American, Monique Brouillette, April 20, 2022

Researchers at the University of South Australia, defense firm Midspar Systems, and Australia's Flinders University have developed an artificial intelligence (AI) algorithm for visual drone detection. The researchers reverse-engineered the visual system of the hoverfly—whose compound eyes can separate relevant information from noise—to develop a tool that filters out noisy data. They fed the algorithm spectrograms based on acoustic data from outdoors as drones flew by. The algorithm was able to amplify data related to the frequencies emitted by drones, while reducing background noise from other sources. The researchers found that it could identify drones up to 50% farther away than conventional AI systems..... ' 

Roboticized Insect Rescue

Interesting application,  Will the small size work for typical applications?  Note these are actual insects being used! So this is bio-augmentation rather then mimicry.   A considerable result if it works practically    An example of using small size to enable search and rescue. 

Robotized Insects May Search Collapsed Buildings for Survivors   By The Economist, March 28, 2022

Researchers at Singapore's Nanyang Technological University have developed robotized insects that could be used to search for survivors in collapsed buildings.  The researchers outfitted Madagascar hissing cockroaches with backpacks featuring a communications chip, a carbon dioxide sensor, a motion sensor, an infrared camera, and a small battery.

The cockroaches are controlled by algorithms that respond directly to the backpack sensors. The researchers tested the so-called cyber-roaches in a simulated disaster zone spanning 25 square meters, which contained concrete blocks, people, and decoys like a microwave oven and a laptop.

Artificial intelligence programmed into the camera identified signs of life such as movement, body heat, and elevated carbon dioxide levels, sending alerts to rescuers if a survivor has been detected.

The researchers found the software correctly recognized humans 87% of the time.

From The Economist     

AI Sheds Light on How Brain Processes Language

Closer looks at the Brains intelligence towards biomimicry.

 Surprisingly Smart Artificial Intelligence Sheds Light on How the Brain Processes Language

By SciTechDaily, November 5, 2021

Neuroscientists find the internal workings of next-word prediction models resemble those of language-processing centers in the brain.

In the past few years, artificial intelligence models of language have become very good at certain tasks. Most notably, they excel at predicting the next word in a string of text; this technology helps search engines and texting apps predict the next word you are going to type.

The most recent generation of predictive language models also appears to learn something about the underlying meaning of language. These models can not only predict the word that comes next, but also perform tasks that seem to require some degree of genuine understanding, such as question answering, document summarization, and story completion.

Such models were designed to optimize performance for the specific function of predicting text, without attempting to mimic anything about how the human brain performs this task or understands language. But a new study from MIT neuroscientists suggests the underlying function of these models resembles the function of language-processing centers in the human brain.

From SciTechDaily

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Bio Neurons versus Computational

When we first learned of the use of the patterns of brain neurons to potentially use as reasoning devices, we took a course from actual neuroscientists.  We very quickly learned that human bio neurons were very much more complex that neurons in our feeble  'neural networks'.   Always been intrigued by the concept, so how could they be more useful 'reasoners"? Tried to augment  our nets with this new complexity.  Here is another case why they are very different.  We can ask ourselves, can we use these aspects of neurons to improve reasoning?  Note the indication that timing matters.  What embedded information  could make us learn faster?   Still unclear, 

Neurons Unexpectedly Encode Information in the Timing of Their Firing

Elena Renken  Quanta Mag     Contributing Writer

A temporal pattern of activity observed in human brains for the first time may explain how we can learn so quickly.

For decades, neuroscientists have treated the brain somewhat like a Geiger counter: The rate at which neurons fire is taken as a measure of activity, just as a Geiger counter’s click rate indicates the strength of radiation. But new research suggests the brain may be more like a musical instrument. When you play the piano, how often you hit the keys matters, but the precise timing of the notes is also essential to the melody.

“It’s really important not just how many [neuron activations] occur, but when exactly they occur,” said Joshua Jacobs, a neuroscientist and biomedical engineer at Columbia University who reported new evidence for this claim last month in Cell.  ... ' 

Evolving Bio Intelligence

Can this kind of generalized AI take us towards more generalized AI?   A new shift in direction? 

Potcast:  Bio Eats World: Evolving Embodied Intelligence    

by Li Fei-Fei, Surya Ganguli, Vijay Pande, and Lauren Richardson  By Andreessen, A16z

On today’s episode, we are making the full arc from the theoretical and borderline philosophical to the applied. Let’s start with the theory: embodied intelligence posits that the body, or the physical form, plays an active and significant role in shaping an agent’s mind and cognitive capacities. For example, human intelligence is not just the function of our brain, but a combination of our brain, our body, and the environment in which we exist. But when it comes to designing artificial intelligence (AI), a physical form and an environment are typically not part of the equation. It’s a disembodied cognition. Our guests, Li Fei-Fei and Surya Ganguli of the Stanford Institute for Human-Centered AI,   set out to develop what they call an “evolutionary playground” to explore the development of embodied intelligence in AI and its connection with the environment and with learning using in silico experiments. They discuss with a16z general partner Vijay Pande and host Lauren Richardson how they created a suite of virtual environments in which agents evolve through a process that mimics aspects of Darwinian evolution. These agents, called the unimal, or universal animal, start off as a central node, and with each generation can add or subtract limbs and change various properties of their physical forms, like how flexible their joints are. Just like in real evolution, different forms arose based on the particularities of the environment, but what is really exciting is what Fei-Fei, Surya, and colleagues discovered about the intelligence encoded in some of these forms, such as an increased ability to learn a novel task. Which brings us to the applied section of our discussion. These results provide new insights for how we think about designing robots capable of performing unique tasks, and for understanding the possible limitations of disembodied AI models, like GTP-3.

The results are described in the pre-print “Embodied Intelligence via Learning and Evolution” posted on arXiv.org.

Synthetic Biology

Touched on Synthetic Biology way back, though it never was used directly in the enterprise.  Apparently reemerging.  A revisit to something that is apparently reemerging.  Beyond Biomimicry.

Biodesign and Synthetic Biology

What Is Biodesign?

By Daniel Grushkin  in Issues.org

In 2009 Nature Biotechnology asked a group of synthetic biologists to define “synthetic biology.” None of the scientists could agree on a definition. Yet today the synthetic biology market—a field evidently without a widely accepted understanding of itself—is worth $9.5 billion. When Nature Biotechnology posed its question I was a reporter covering the emerging discipline. I soon realized that definitions are less important than the groups of people who gather around and advance a particular set of ideas.

So what, then, is “biodesign”? Today I would say it’s a big tent where everyone who self-identifies as a biodesigner can hang out. Of course before I founded the Biodesign Challenge in 2015, I probably would have said that it’s a design practice that incorporates biotechnology, or one that uses design to critique the biotech industry. Both of these definitions are accurate, but today I see the unbounded potential of the community of people as much as the possibilities within the ideas themselves.  .... ' 

Bats Hunting

Good example of the potential use of biomimicry

 Tiny Computers Reveal How Wild Bats Hunt So Efficiently

Aarhus University (Denmark), Peter F. Gammelby; Laura Stidsholt March 3, 2021

Researchers at Denmark's Aarhus University and Germany's Max Planck Institute of Ornithology used 3-gram computers attached to wild greater mouse-eared bats in Bulgaria to study how they hunt. The miniature tags record each bat's echolocation calls and movement in three dimensions. The institute's Holger Goerlitz said, "We found that hunting bats narrow their sensory volumes by more than a thousand times to only focus on the prey, and thereby reduce the clutter from other echoes. It's like an acoustic version of a tunnel vision that briefly makes their world much simpler." Said Aarhus University's Mark Johnson, who developed the tags, "It was a real challenge to make a computer so small that it could work on a flying bat and still be sensitive enough to pick up these weak sounds."

Soft Robot Swims in the Mariana Trench

An example of extreme exploration, using a soft biomimicking design.  Considerable possibilities here.

Soft robot swims in the Mariana Trench  in Techexplore by Bob Yirka 

A team of researchers affiliated with multiple institutions in China has developed a soft robot that can successfully swim in the Mariana Trench. In their paper published in the journal Nature,, the group describes their soft robot and its capabilities. Cecilia Laschi and Marcello Calisti with the National University of Singapore and the University of Lincoln, respectively, have published a News & Views piece in the same journal issue outlining the work by the team in China. ... " 

Biomimicking Learning by DragonFly

Like the idea of biomimicry for certain adaptive robotic abilities,  here an example at a fairly low level.  Technical.

Bio-Inspired Robotics: Learning From Dragonflies  By Kiel University (Germany),  January 28, 2021

Scientists at Germany's Kiel University (CAU) have decrypted the biomechanical function of the labial mask of dragonfly larvae, leading to a bio-inspired robot modeled after the same operating principle.

CAU's Sebastian Büsse said, "What is ideal about robotics is that it functions in two directions: we learn something about biology and develop something that can be applied in technology." The CAU team first deciphered the labial mask's operating principle, describing a synchronized dual-catapult system and visualizing its movements via three-dimensional (3D) animation to test this hypothesis.

Büsse said system improvements derived from these observations could be applied to enhance the performance of agile robots. CAU's Stanislav N. Gorb said the 3D-printed robot subsequently produced by the researchers "has provided us with more detailed insight into the operating principle of the  ... "

Drones Tracking Smells

 We did lots of work examining smells, and sought means to detect and track them. Here an update in the space. Could have used tested for forestry and agriculture  application.    See many posts on digital smell her over a number of years.

Smellicopter Drone Uses Live Moth Antenna to Track Scents

Robots are no match for the sensors insects are born with, but that doesn’t matter if we can just steal them   By Evan Ackerman  in IEEE Spectrum Robotics ...

AI to Understand Consciousness of a 'Theory of Mind'

 We read much on 'Theory of mind', as it related to things like intelligent undertanding and 'consciousness'. Could this leverage us into better definitions and uses of consciousness in context? 

New MIT brain research shows how AI could help us understand consciousness  By Tristan Greene  in TNW

A team of researchers from MIT and Massachusetts General Hospital recently published a study linking social awareness to individual neuronal activity. To the best of our knowledge, this is the first time evidence for the ‘theory of mind‘ has been identified at this scale.

Measuring large groups of neurons is the bread-and-butter of neurology. Even a simple MRI can highlight specific regions of the brain and give scientists an indication of what they’re used for and, in many cases, what kind of thoughts are happening. But figuring out what’s going on at the single-neuron level is an entirely different feat.

According to the paper: 

Here, using recordings from single cells in the human dorsomedial prefrontal cortex, we identify neurons that reliably encode information about others’ beliefs across richly varying scenarios and that distinguish self- from other-belief-related representations … these findings reveal a detailed cellular process in the human dorsomedial prefrontal cortex for representing another’s beliefs and identify candidate neurons that could support theory of mind.

In other words: the researchers believe they’ve observed individual brain neurons forming the patterns that cause us to consider what other people might be feeling and thinking. They’re identifying empathy in action.... " 

Electric Amoeba efficiently Solves TSP

Classic problem, usefully solved?

Electronic Amoeba' Finds Approximate Solution to Traveling Salesman Problem in Linear Time  By Hokkaido University (Japan)

Researchers in Japan developed electronic amoeba, an analog computer inspired by a single-celled amoeboid organism, to solve the traveling salesman problem.

Researchers at Hokkaido University and Amoeba Energy in Japan have, inspired by the efficient foraging behavior of a single-celled amoeba, developed an analog computer for finding a reliable and swift solution to the traveling salesman problem — a representative combinatorial optimization problem.

Many real-world application tasks such as planning and scheduling in logistics and automation are mathematically formulated as combinatorial optimization problems. Conventional digital computers, including supercomputers, are inadequate to solve these complex problems in practically permissible time as the number of candidate solutions they need to evaluate increases exponentially with the problem size — also known as combinatorial explosion. Thus new computers called "Ising machines," including "quantum annealers," have been actively developed in recent years. These machines, however, require complicated pre-processing to convert each task to the form they can handle and have a risk of presenting illegal solutions that do not meet some constraints and requests, resulting in major obstacles to the practical applications.

These obstacles can be avoided using the newly developed "electronic amoeba," an analog computer inspired by a single-celled amoeboid organism. The amoeba is known to maximize nutrient acquisition efficiently by deforming its body. It has shown to find an approximate solution to the traveling salesman problem (TSP), i.e., given a map of a certain number of cities, the problem is to find the shortest route for visiting each city exactly once and returning to the starting city. This finding inspired Professor Seiya Kasai at Hokkaido University to mimic the dynamics of the amoeba electronically using an analog circuit, as described in the journal Scientific Reports. "The amoeba core searches for a solution under the electronic environment where resistance values at intersections of crossbars represent constraints and requests of the TSP," says Kasai. Using the crossbars, the city layout can be easily altered by updating the resistance values without complicated pre-processing.

From Hokkaido University (Japan)