Singularity Hub Daily

The Intergovernmental Panel on Climate Change released its Sixth Assessment Report in early August, and the outlook isn’t good. The report has added renewed urgency to humanity’s effort to curb climate change.

The price of solar energy dropped 89 percent in 10 years, and new wind farms are being built both on land and offshore (with ever-bigger turbines capable of generating ever more energy). But simply adding more wind and solar generation capacity won’t get us very far if we don’t have a cost-effective, planet-friendly way to store the energy they produce.

As Zia Huque, general partner at Prime Movers Lab, put it, “To truly harness the power of renewable energy, the world needs to develop reliable, flexible storage solutions for when the sun does not shine or the wind does not blow.”

A startup called Energy Vault is working on a unique storage method, and they must be on the right track, because they just received over $100 million in Series C funding last week.

The method was inspired by pumped hydro, which has been around since the 1920s and uses surplus generating capacity to pump water up into a reservoir. When the water is released, it flows down through turbines and generates energy just like conventional hydropower.

Now imagine the same concept, but with heavy solid blocks and a tall tower rather than water and a reservoir. When there’s excess power—on a sunny or windy day with low electricity demand, for example—a mechanical crane uses it to lift the blocks 35 stories into the air. Then the blocks are held there until demand is outpacing supply. When they’re lowered to the ground (or lowered a few hundred feet through the air), their weight pulls cables that spin turbines, generating electricity.

“Heavy” blocks in this case means 35 tons (70,000 pounds or 31,751 kg). The blocks are made of a composite material that uses soil and locally-sourced waste, which can include anything from concrete debris and coal ash to decommissioned wind turbine blades (talk about coming full circle). Besides putting material that would otherwise go into a landfill to good use, this also means the blocks can be made locally, and thus don’t need to be transported (and imagine the cost and complexity of transporting something that heavy, oy).

The cranes that lift and lower the blocks have six arms, and they’re controlled by fully-automated custom software. Energy Vault says the towers will have a storage capacity up to 80 megawatt-hours, and be able to continuously discharge 4 to 8 megawatts for 8 to 16 hours. The technology is best suited for long-duration storage with very fast response times.

The Series C funding was led by Prime Movers Lab, with existing investors SoftBank and Saudi Aramco adding additional funds and several new investors joining. Energy Vault plans to use the funding to roll out its EVx platform, launched in April of this year. The platform includes performance enhancements like round-trip efficiency up to 85 percent, a lifespan of over 35 years, and a flexible, modular design that’s shorter than the original—which means it could more easily be built in or near densely-populated areas.

Huque called Energy Vault a “gamechanger” in the transition to green energy, saying the company “has cracked the code with a transformative solution.designed to fulfill clean energy demand 24/7 with a more efficient, durable, and environmentally sustainable approach.”

The company will roll out its EVx platform in the US late this year, moving on to fulfill contracts in Europe, the Middle East, and Australia in 2022.

Image Credit: Energy Vault

Deep learning is solving biology’s deepest secrets at breathtaking speed.

Just a month ago, DeepMind cracked a 50-year-old grand challenge: protein folding. A week later, they produced a totally transformative database of more than 350,000 protein structures, including over 98 percent of known human proteins. Structure is at the heart of biological functions. The data dump, set to explode to 130 million structures by the end of the year, allows scientists to foray into previous “dark matter”—proteins unseen and untested—of the human body’s makeup.

The end result is nothing short of revolutionary. From basic life science research to developing new medications to fight our toughest disease foes like cancer, deep learning gave us a golden key to unlock new biological mechanisms—either natural or synthetic—that were previously unattainable.

Now, the AI darling is set to do the same for RNA.

As the middle child of the “DNA to RNA to protein” central dogma, RNA didn’t get much press until its Covid-19 vaccine contribution. But the molecule is a double hero: it both carries genetic information, and—depending on its structure—can catalyze biological functions, regulate which genes are turned on, tweak your immune system, and even crazier, potentially pass down “memories” through generations.

It’s also frustratingly difficult to understand.

Similar to proteins, RNA also folds into complicated 3D structures. The difference, according to Drs. Rhiju Das and Ron Dror at Stanford University, is that we comparatively know little about these molecules. There are 30 times as many types of RNA as there are proteins, but the number of deciphered RNA structures is less than one percent compared to proteins.

The Stanford team decided to bridge that gap. In a paper published last week in Science, they described a deep learning algorithm called ARES (Atomic Rotationally Equivalent Scorer) that efficiently solves RNA structures, blasting previous attempts out of the water.

The authors “have achieved notable progress in a field that has proven recalcitrant to transformative advances,” said Dr. Kevin Weeks at the University of North Carolina, who was not involved in the study.

Even more impressive, ARES was trained on only 18 RNA structures, yet was able to extract substantial “building block” rules for RNA folding that’ll be further tested in experimental labs. ARES is also input agnostic, in that it isn’t specifically tailored to RNA.

“This approach is applicable to diverse problems in structural biology, chemistry, materials science, and beyond,” the authors said.

Meet RNA

The importance of this biomolecule for our everyday lives is probably summarized as “Covid vaccine, mic drop.”

But it’s so much more.

Like proteins, RNA is transcribed from DNA. It also has four letters, A, U, C, and G, with A grabbing U and C tethered to G. RNA is a whole family, with the most well-known type being messenger RNA, or mRNA, which carries the genetic instructions to build proteins. But there’s also transfer RNA, or tRNA—I like to think of this as a transport drone—that grabs onto amino acids and shuttles them to the protein factory, microRNA that controls gene expression, and even stranger cousins that we understand little about.

Bottom line: RNA is both a powerful target and inspiration for genetic medicine or vaccines. One way to shut off a gene without actually touching it, for example, is to kill its RNA messenger. Compared to gene therapy, targeting RNA could have fewer unintended effects, all the while keeping our genetic blueprint intact.

In my head, RNA often resembles tangled headphones. It starts as a string, but subsequently tangles into a loop-de-loop—like twisting a rubber band. That twisty structure then twists again with surrounding loops, forming a tertiary structure.

Unlike frustratingly annoying headphones, RNA twists in semi-predictable ways. It tends to settle into one of several structures. These are kind of like the shape your body contorts ...

3D printing is picking up speed as a construction technology, with 3D printed houses, schools, apartment buildings, and even Martian habitat concepts all being unveiled in the last year (not to mention Airbnbs and entire luxury communities). Now another type of structure is being added to this list: military barracks.

ICON, a construction technologies startup based in Austin, Texas, announced the project earlier this month in partnership with the Texas Military Department. At 3,800 square feet, the barracks will be the biggest 3D printed structure in North America. It’s edged out for the worldwide title by at least one other building, a 6,900-square-foot complex in Dubai used for municipal offices.

The barracks are located at the Camp Swift Training Center in Bastrop, TX, and are replacing temporary facilities that have already been used for longer than their intended lifespan. 72 soldiers will stay in the building, sleeping in bunk beds, while they train for missions and prepare for deployment.

“The printed barracks will not only provide our soldiers a safe and comfortable place to stay while they train, but because they are printed in concrete, we anticipate them to last for decades,” said Colonel Zebadiah Miller, the Texas Military Department’s director of facilities.

The energy-efficient barracks are being built with ICON’s Vulcan 3D printer, the initial iteration of which was 11.5 feet tall by 33 feet wide, made up of an axis set on a track. The printer’s “ink” is a proprietary concrete mix, which it puts down in stacked layers from the ground up. The building was designed by Austin-based Logan Architecture, a firm that had previously worked with ICON on the East 17th Residences, four partially 3D printed homes that went on the market in Austin earlier this year.

Soldiers will move into the barracks this fall.

With the announcement of $207 million raised in Series B funding this week, ICON is well-positioned to launch several more projects in the coming months and years. In May the company unveiled both its new Vulcan printer—1.5 times larger and 2 times faster than the previous version—and its House Zero line of homes, optimized and designed specifically for construction via 3D printing.

TechCrunch reported last week that ICON’s revenue has grown by 400 percent every year since its 2018 launch. The startup tripled its team in the past year, hitting the benchmark of over 100 employees, and plans to double in size again within the next year.

What this all comes down to is that a lot of people and organizations are seeing the benefits of 3D printing as a construction tool, and at the rate the technology is growing, houses and barracks are just the beginning.

“ICON continues our missional work to deliver dignified, resilient shelter for social housing, disaster-relief housing, market-rate homes, and now, homes for those serving our country,” said ICON co-founder Evan Loomis. “We are scaling this technology across Texas, the US, and eventually the world. This is the beginning of a true paradigm shift in homebuilding.”

Image Credit: ICON

In the search for life beyond our planet, scientists have long focused on conditions similar to those found here. This makes sense. Earth is the only place we know life exists.

But in recent years, exactly where such conditions might occur—in particular the presence of liquid water oceans—has expanded. Scientists now believe there are oceans with the potential for life in the interiors of moons, dwarf planets, and even large asteroids.

Space agencies plan to visit some of these interior ocean worlds in the not-too-distant future. But of course, we can’t yet visit or study such tiny planetary bodies around other stars. So scientists are focused on roughly Earth-sized exoplanets in the search for life.

Earth-like planets in the habitable zone, where liquid water on the surface is possible, do exist—and are even relatively abundant, scientists believe—but they may not be the only or even best place to search for life given the observational tools at hand.

A recent paper by a Cambridge team published in The Astrophysical Journal identified a new class of exoplanet with the potential for life—despite relatively extreme conditions.

These planets, classified as Hycean worlds (a mashup of hydrogen and ocean), are bigger than Earth and smaller than Neptune. Typically this class of exoplanets is divided into rocky planets like Earth, dubbed super-Earths, and ice giants like Neptune, called mini-Neptunes. Hycean worlds sit in between the two.

They have extensive atmospheres dominated by hydrogen and large, planet-wide oceans. They can be up to 2.6 times larger than Earth with temperatures as high as 395 degrees Fahrenheit (202 degrees Celsius). Despite crushing pressures and scorching temperatures, the team defines these conditions “habitable” because we know they’re amenable to microbial life we see on Earth in extreme oceanic environments.

Previously, another recent study by the same team of researchers looked at a specific mini-Neptune (K2-18b) and found that under certain circumstances, such planets could host life. This led them to model the full range of planetary and stellar attributes that, in theory, would allow for the possibility of life and to look into the likelihood we could detect it.

The team says Hycean planets could broadly expand the number of worthy exoplanets in our search. This is, in part, because the Hycean habitable zone is wider than the habitable zone for Earth-like planets. Further, conditions suitable for life could exist on the dark sides of tidally locked Hycean planets close to their stars (where one side never faces their sun) as well as more distant, relatively chilly planets receiving less sunlight.

They also may be very common. Of the thousands of exoplanets discovered, the “vast majority” belong to the class of planets sized between Earth and Neptune. Indeed, the team identified a group of 11 potential Hycean planets orbiting red dwarf stars near Earth—within 35 and 150 light years—worthy of observation.

In addition to widening the pool of potential candidates, the team argues it could be easier to look for the telltale chemical signs of life on Hycean planets given today’s tools.

One such tool, the James Webb Space Telescope (JWST), Hubble’s successor, was packed up for shipping to its launch site this week. The JWST is scheduled to launch later this year.

In addition to peering deep into the early universe, the telescope will scan the atmospheres of promising exoplanets. To detect the byproducts (or biosignatures) of living creatures, scientists will analyze the spectrum of starlight shining through their atmospheres.

For Earth-like planets, where the atmosphere hugs the surface fairly closely, this may be relatively difficult and require data gathering from multiple orbits of—and transits across—a candidate’s host star. Hycean planets, on the other hand, are bigger and have atmospheres extending higher above the surface—allowing for more sunlight to pass through them. This may make them more eff...

Much of the recent progress in AI has come from building ever-larger neural networks. A new chip powerful enough to handle “brain-scale” models could turbo-charge this approach.

Chip startup Cerebras leaped into the limelight in 2019 when it came out of stealth to reveal a 1.2-trillion-transistor chip. The size of a dinner plate, the chip is called the Wafer Scale Engine and was the world’s largest computer chip. Earlier this year Cerebras unveiled the Wafer Scale Engine 2 (WSE-2), which more than doubled the number of transistors to 2.6 trillion.

Now the company has outlined a series of innovations that mean its latest chip can train a neural network with up to 120 trillion parameters. For reference, OpenAI’s revolutionary GPT-3 language model contains 175 billion parameters. The largest neural network to date, which was trained by Google, had 1.6 trillion.

“Larger networks, such as GPT-3, have already transformed the natural language processing landscape, making possible what was previously unimaginable,” said Cerebras CEO and co-founder Andrew Feldman in a press release.

“The industry is moving past 1 trillion parameter models, and we are extending that boundary by two orders of magnitude, enabling brain-scale neural networks with 120 trillion parameters.”

The genius of Cerebras’ approach is that rather than taking a silicon wafer and splitting it up to make hundreds of smaller chips, it makes a single massive one. While your average GPU will have a few hundred cores, the WSE-2 has 850,000. Because they’re all on the same hunk of silicon, they can work together far more seamlessly.

This makes the chip ideal for tasks that require huge numbers of operations to happen in parallel, which includes both deep learning and various supercomputing applications. And earlier this week at the Hotchips conference, the company unveiled new technology that is pushing the WSE-2’s capabilities even further.

A major challenge for large neural networks is shuttling around all the data involved in their calculations. Most chips have a limited amount of memory on-chip, and every time data has to be shuffled in and out it creates a bottleneck, which limits the practical size of networks.

The WSE-2 already has an enormous 40 gigabytes of on-chip memory, which means it can hold even the largest of today’s networks. But the company has also built an external unit called MemoryX that provides up to 2.4 Petabytes of high-performance memory, which is so tightly integrated it behaves as if it were on-chip.

Cerebras has also revamped its approach to that data it shuffles around. Previously the guts of the neural network would be stored on the chip, and only the training data would be fed in. Now, though, the weights of the connections between the network’s neurons are kept in the MemoryX unit and streamed in during training.

By combining these two innovations, the company says, they can train networks two orders of magnitude larger than anything that exists today. Other advances announced at the same time include the ability to run extremely sparse (and therefore efficient) neural networks, and a new communication system dubbed SwarmX that makes it possible to link up to 192 chips to create a combined total of 163 million cores.

How much all this cutting-edge technology will cost and who is in a position to take advantage of it is unclear. “This is highly specialized stuff,” Mike Demler, a senior analyst with the Linley Group, told Wired. “It only makes sense for training the very largest models.”

While the size of AI models has been increasing rapidly, it’s likely to be years before anyone can push the WSE-2 to its limits. And despite the insinuations in Cerebras’ press material, just because the parameter count roughly matches the number of synapses in the brain, that doesn’t mean the new chip will be able to run models anywhere close to its complexity or performance.

There’s a major debate in AI circles today over whether we can achieve general ar...

Imagine if you could power your kettle using the energy generated from the vegetable cuttings quietly breaking down in your kitchen’s compost bin. That reality might not be so far off with the growth of biogas technology.

Biogas is a green alternative to fossil fuels that not only helps to reduce toxic emissions but also provides cheap, clean energy. It’s made up of a mixture of methane, carbon dioxide and a little hydrogen sulfide and water vapor, all of which is produced by microbes that live on organic raw material within a airtight digester container.

The efficiency of the system depends on the size and insulation capability of the digester, as well as the quantity of methane produced from the “feedstock,” which can be anything from carrot leaves and onion peels to residue from gardening.

Biogas is “green” because it reduces the release of greenhouse gases into the atmosphere from decomposing food waste. Instead, these gases are stored and used for generating heat and electricity, making the energy produced from waste more sustainable.

Yet although biogas has been promoted as a way of helping to reduce carbon emissions for a few years now—and has actually been used to power households since as early as the 10th century BC (for heating bath water in the Middle East)—it still only represented around 0.004 percent of total EU gas consumption in 2019. So why is uptake so low, and what can be done about it?

Digesters in Practice

Micro-digesters (between two to ten cubic meters) can power individual household systems for up to 12 hours per day, while large digesters of 50 cubic meters can be linked to the local gas grid to support communities for up to 250 hours.

The diagram below shows how these systems usually work: the pipe at the top of the image would normally lead to a community gas tank or household appliance.

An example of an innovative small-scale biogas system is the Methanogen micro-digester. There is one running at Calthorpe community garden, a multi-functional urban community center in Islington, London. The unit sits in a repurposed shed next to a vegetable garden. The energy, generated from food and garden waste from the surrounding houses, is supplied to the center’s kitchen hob through a pipe.

The digester is run by community volunteers, whose mission is to improve the physical and emotional well-being of residents living in the center’s surrounding areas by encouraging them to grow food and spend more time in nature.

An even more ambitious initiative is running on the Swedish island of Gotland, where an eco-village, Suderbyn, has been created using zero-carbon materials. A community-run digester was set up to create heat using food and agricultural waste from the community. Inspired by Suderbyn’s success, similar sites have been launched in the UK at Hockerton, near Nottingham, and in Grimsby.

The Uptake Problem

But why are more digesters not springing up? Our research set out to understand the challenges responsible for the slow uptake of this technology.

To better understand people’s attitudes towards biogas, we carried out a study of community biogas generation in Europe. Our research, conducted through interviews and consultation workshops, found that one of the barriers stopping biogas use was prejudice arising from poor public understanding of the technology and its benefits.

People we spoke to were concerned that local digesters would produce a nasty smell, or that their industrial appearance would blight the landscape. In fact, many digesters are fairly small, and would only produce smells if the system broke down.

Other stumbling blocks include a lack of technical expertise in building or maintaining digesters, a lack of incentives to attract local businesses, and the high cost of the digester, which, depending on its size, can cost between £12,000 and £158,000.

Because of this, local government assistance will be crucial in bringing biogas to the masses. They should help shoulder the financial cost...

In 2018, GE unveiled its Haliade-X turbine, and it has since been the largest and most powerful offshore wind turbine in the world. At 853 feet tall and with a rotor measuring 722 feet across, a single rotation of its blades can power a home for two days (that’s a home in the UK, not the US; homes here tend to be bigger energy hogs). Last year, the Haliade-X prototype located in the Netherlands set a new world record by generating 312 megawatt-hours of continuous power in one day.

But the record-setting turbine is about to get dethroned by a new, even bigger and more powerful arrival. China’s MingYang Smart Energy Group this week announced development of its MySE 16.0-242, a 16-megawatt turbine that can reportedly power 20,000 homes. Standing 866 feet tall, the turbine only has a few feet on the Haliade-X’s height, but its rotor is the differentiator at 794 feet across. Each blade is 387 feet long, and their rotation will sweep an area bigger than six soccer fields.

Let’s put some more visuals to those numbers. 866 feet is taller than the 70-story GE building in New York’s Rockefeller Center. An American football field is 360 feet long, so imagine a blade that’s even longer, and a rotor taller than the Golden Gate Bridge.

It’s hard to wrap your head around, especially when you consider that these gigantic pieces will be assembled into one unit in the middle of the ocean, then work together to produce clean energy. The company says the turbine can be anchored to the ocean floor or installed on a floating base (the proportions of which are equally hard to imagine).

Putting a man-made structure of these dimensions with moving parts in the ocean must have some sort of impact on the surrounding marine life. However, not a ton of research has been done in this area, and as offshore wind becomes a more popular source of power, it’s probably a good idea to make sure we’re not wrecking entire ecosystems by plopping turbines into their midst.

To that end, the UK’s Natural Environment Research Council launched a study this week called ECOWind. In partnership with The Crown Estate, which manages the seabed of England, Wales, and Northern Ireland, the project will collect and analyze data on offshore wind’s impact on marine ecosystems, and is scheduled to last four years.

China will want to heed the findings; it’s been the world leader in new offshore wind installations for three years running, and installed more than half the world’s offshore wind capacity last year. As demand for renewable energy sources grows, offshore wind will continue to be scaled up, both in terms of the number of turbines installed and the power generation capacity of the turbines. MingYang’s new turbine can reportedly withstand typhoon-force winds.

Founded in 2006, MingYang is a public company whose stock trades on the Shanghai exchange. Earlier this year, the company secured a contract to provide 10 turbines (of an earlier model than the 16.0-242) for the Taranto offshore wind park off the Italian coast. It will be the first offshore wind farm in the Mediterranean, and is MingYang’s first European deal.

A prototype of the MySE 16.0-242 will be built in 2022, with commercial production of the turbine scheduled to start in early 2024.

Image Credit: MingYang Smart Energy Group Co. Ltd.

Nature hides astonishing medical breakthroughs.

Take CRISPR, the transformative gene editing tool. It was inspired by a lowly bacterial immune defense system and co-opted to edit our genes to treat inherited diseases, bolster cancer treatments, or even extend lifespan. Now, Dr. Feng Zhang, one of the pioneers of CRISPR, is back with another creation that could unleash the next generation of gene therapy and RNA vaccines. Only this time, his team looked deep inside our own bodies.

Powerful as they are, DNA and RNA therapeutics need to hitch a ride into our cells to work. Scientists usually call on viral vectors—delivery vehicles made from safe viruses—or lipid nanoparticles, little blobs of protective fat, to encapsulate new genetic material and tunnel into cells.

The problem? Our bodies aren’t big fans of foreign substances—particularly ones that trigger an undesirable immune response. What’s more, these delivery systems aren’t great with biological zip codes, often swarming the entire body instead of focusing on the treatment area. These “delivery problems” are half the battle for effective genetic medicine with few side effects.

“The biomedical community has been developing powerful molecular therapeutics, but delivering them to cells in a precise and efficient way is challenging,” said Zhang at the Broad Institute, the McGovern Institute, and MIT.

Enter SEND. The new delivery platform, described in Science, dazzles with its sheer ingenuity. Rather than relying on foreign carriers, SEND (selective endogenous encapsidation for cellular delivery) commandeers human proteins to make delivery vehicles that shuttle in new genetic elements. In a series of tests, the team embedded RNA cargo and CRISPR components inside cultured cells in a dish. The cells, acting as packing factories, used human proteins to encapsulate the genetic material, forming tiny balloon-like vessels that can be collected as a treatment.

Even weirder, the source of these proteins relies on viral genes domesticated eons ago by our own genome through evolution. Because the proteins are essentially human, they’re unlikely to trigger our immune system.

Although the authors only tried one packaging system, far more are hidden in our genomes. “That’s what’s so exciting,” said study author Dr. Michael Segel, adding that the system they used isn’t unique; “There are probably other RNA transfer systems in the human body that can also be harnessed for therapeutic purposes.”

The Body’s Shipping Infrastructure

Our cells are massive chatterboxes. And they’ve got multiple phone lines.

Electricity is a popular one. It’s partly what keeps neurons hooked up into networks and heart cells in sync. Hormones are another, linking up cells from halfway around the body through chemicals in the bloodstream.

But the strangest comes from an age-old truce between human and virus. Scouring the human genome today, it’s clear we have viral DNA and other genetic elements embedded inside our own double helices. Most of these viral additions have lost their original functions. Some, however, have been recruited to build our bodies and minds.

Take Arc, a protein made from a gene otherwise known as gag—a core viral gene that’s common in our genomes. Arc is a memory grandmaster: as we learn, the protein forms tiny capsules that transfer biological material, which in turn helps to cement new memories into our neural network repertoire. Another protein similar to gag, dubbed PEG10, can grab onto RNA and also form bubbly spaceships to help develop the placenta and aid reproduction.

If PEG10 makes the cardboard packaging for genetic material, then the mail stamp comes from another viral gene family, fusogens. The gene creates a zip code of sorts, allowing each spaceship, carrying the cargo, to dock onto targeted cells.

Although originally viral in nature, these genes have immigrated into our genomes and adapted into an amazingly specific transportation system that allows cells to share information...

Today’s brain implants are bulky and can typically only record from one or two locations. Now researchers have shown that a network of tiny “neurograins” can be used to wirelessly record and stimulate neurons in multiple locations in rat brains.

Researchers have been experimenting with brain computer interfaces (BCIs) that can record and stimulate groups of neurons for decades. But in recent years there has been growing interest in using them to treat diseases like epilepsy, Parkinson’s, or various psychiatric disorders.

More speculatively, some think they could soon be implanted in healthy people to help us monitor our brain function and even boost it. Last year, Elon Musk said brain implants being built by his startup Neuralink will one day be like “a Fitbit in your skull.” First, though, they will have to get much more accurate and far less obtrusive.

New research led by a team at Brown University has made significant strides on that latter problem by developing tiny implants measuring less than 0.1 cubic millimeters. The implants can both record and stimulate brain activity; these “neurograins” can be combined to create a network of implants that can be controlled and powered wirelessly.

“One of the big challenges in the field of brain-computer interfaces is engineering ways of probing as many points in the brain as possible,” Arto Nurmikko, who led the research, said in a press release. “Up to now, most BCIs have been monolithic devices—a bit like little beds of needles. Our team’s idea was to break up that monolith into tiny sensors that could be distributed across the cerebral cortex.”

Each of the tiny chips features electrodes to pick up electrical signals from brain tissue, circuitry to amplify the signal, and a tiny coil of wire that sends and receives wireless signals. The chips are attached to the surface of the brain and a thin relay coil that helps improve wireless power transfer to the neurograins is laid over the area where they are placed.

A thin patch containing another coil is then stuck to the outside of the scalp above the relay coil. This acts like a mini cellphone tower, using a specially-designed network protocol to connect to each of the neurograins individually. It also transmits power to the neurograins.

The concept is similar to the “neural dust” developed at University of California, Berkley, which has since been spun out by startup Iota Biosciences, though their neurograins are an order of magnitude smaller.

In a paper in Nature Electronics, the team showed that they could implant 48 of the tiny chips into a rat’s brain and use it to record and stimulate neural activity. While ultimately both capabilities will be integrated into one device, for the purpose of the study some neurograins were designed to record while others were built to stimulate.

The researchers say the fidelity of the recordings has room for improvement, but they were able to pick up spontaneous brain signals and detect when the brain was stimulated using a conventional implant. They also showed they could direct a single neurograin to stimulate neural activity, which they were able to pick up with conventional recording devices.

The team says their current setup could support up to 770 of the neurograins, but they envision scaling to thousands. That would likely require further miniaturization, but the paper notes that the chip design should translate from the 65 nanometer fabrication process it currently uses to a 22 nanometer one. The same group has also developed a novel method for implanting large numbers of tiny wireless sensors into soft tissue.

Plenty of work still needs to be done to improve the quality of the recordings the implants are capable of, and to verify their safety in humans. But the ability to coordinate many small implants into a network is an interesting advance, with plenty of potential for both research and medicine.

Image Credit: Image by Raman Oza from Pixabay

Swiss researchers at the University of Applied Sciences Graubünden this week claimed a new world record for calculating the number of digits of pi—a staggering 62.8 trillion figures. By my estimate, if these digits were printed out they would fill every book in the British Library ten times over. The researchers’ feat of arithmetic took 108 days and 9 hours to complete, and dwarfs the previous record of 50 trillion figures set in January 2020.

But why do we care?

The mathematical constant pi (π) is the ratio of a circle’s circumference to its diameter, and is approximately 3.1415926536. With only these ten decimal places, we could calculate the circumference of Earth to a precision of less than a millimeter. With 32 decimal places, we could calculate the circumference of our Milky Way galaxy to the precision of the width of a hydrogen atom. And with only 65 decimal places, we would know the size of the observable universe to within a Planck length—the shortest possible measurable distance.

What use, then, are the other 62.79 trillion digits? While the short answer is that they are not scientifically useful at all, mathematicians and computer scientists will be eagerly awaiting the details of this gargantuan computation for a variety of reasons.

What Makes Pi So Fascinating?

The concept of pi is simple enough for a primary school student to grasp, yet its digits are notoriously difficult to calculate. A number like 1/7 needs infinitely many decimals to write down—0.1428571428571.—but the numbers repeat themselves every six places, making it easy to understand. Pi, on the other hand, is an example of an irrational number, in which there are no repeating patterns. Not only is pi irrational, but it is also transcendental, meaning it cannot be defined through any simple equation featuring whole numbers.

Mathematicians around the world have been computing pi since ancient times, but techniques to do so changed dramatically after the 17th century, with the development of calculus and the techniques of infinite series. For example, the Madhava series (named after the Indian-Hindu mathematician Madhava of Sangamagrama), says:

π = 4(1 – 1/3 + 1/5 – 1/7 + 1/9 – 1/11 + .)

By adding more and more terms, this computation gets closer and closer to the true value of pi. But it takes a long time—after 500,000 terms, it produces only five correct decimal places of pi!

The search for new formulae for pi adds to our mathematical understanding of the number, while also letting mathematicians vie for bragging rights in the quest for more digits. The infinite sum used in the 2020 record-breaking effort was discovered in 1988 and can calculate 14 new digits of pi for each new term that is added to the sum.

While breaking the record may be one of the key motivators for finding new digits of pi, there are two other important benefits.

The first is the development and testing of supercomputers and new high-precision multiplication algorithms. Optimizing the computation of pi leads to computer hardware and software that benefit many other areas of our lives, from accurate weather forecasting to DNA sequencing and even COVID modeling.

The latest computation of pi was 3.5 times as fast as the previous effort, despite the extra 12 trillion decimal places—an impressive increase in supercomputing performance in just 18 months.

The second is the exploration of the very nature of pi. Despite centuries of research, there are still fundamental unanswered questions about the way its digits behave. It is conjectured that pi is a “normal” number, meaning all possible sequences of digits should appear equally often.

For example, we expect the digit 3 to appear as often as the digit 8, and the digit string “12345” to appear as often as “99999.” But we don’t even know if each decimal digit appears infinitely often in pi, let alone whether there are more complex patterns waiting to be discovered.

The data for the new pi computation have not yet been released, as the ...