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Quantum simulator for electrons and electromagnetic fields in materials

MIT researchers have found ways to generate synthetic electromagnetic fields on superconducting quantum processors. This opens the way to better methods to simulate how electrons move in materials.

The researchers generated a synthetic magnetic field inside a quantum processor comprising 16 qubits. The synthetic magnetic field lives inside a computation, and is not “real.” However, it acts like a magnetic field would in nature.

The synthetic magnetic field allows the researchers to study how electrons would behave if there was an actual magnetic field. This is important because electrons in materials can move in unique ways when influenced by magnetic fields. The response of electrons to magnetic fields can change how materials conduct electricity or turn into different states, like from metal to insulator.

By controlling how the qubits interact with each other, the researchers can simulate how electrons jump from one atom to another in a material. They can tweak the energy levels of the qubits, how the qubits talk to each other, and the frequencies of microwaves used to control the qubits.

The researchers described the methods and results of this study in a paper published in Nature Physics.

Better simulations of material physics

The quantum processor is not a large-scale quantum computer but a smaller system designed to mimic the behavior of electrons in materials.

The researchers found that the behavior of the qubits mimicked the basic rules of electromagnetism, confirming that the simulated synthetic magnetic field works like a real magnetic field.

A better understanding of the behavior of electrons in materials can lead to finding new materials for making electronics that work faster or with less energy. Electronics like computers or phones could become much more efficient if we learn how to control materials at this microscopic level.

This research work shows that small quantum simulators can be very effective for studying material properties in a controlled way. It helps explore new possibilities in material science, potentially leading to breakthroughs in electronics and energy technology.

“Our work enables us to simulate much more of the rich physics that has captivated materials scientists,” says researcher Ilan Rosen in a MIT press release. “We are in a very exciting place for the future.”

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Big data and AI will power autonomous robot scientists

Scientists at the Institute of Tibetan Plateau Research of the Chinese Academy of Sciences are studying how big data and artificial intelligence (AI) are changing the way science works.

Scientists used to focus on finding out why things happen (causation), but now, with so much data, they often look at how things relate to each other (correlation).

In a paper published in Science Bulletin, Xin Li and Yanlong Guo explain how science is moving from being just about looking at data to a new way of data-intensive scientific discovery, where AI does much of the work.

The scientists analyze the full process of science, like watching things happen (observation), figuring out what the data means (data analysis), coming up with ideas (hypothesis generation), guessing what will happen next (prediction), checking if those guesses are right (hypothesis testing), and making big ideas about how things work (theorization). They say that AI tools help and improve the usual science methods, but don’t take over completely.

Totally new science

Li and Guo believe that with the growth in AI, “robot scientists” will become real soon. Robot scientists would watch things, analyze data, think of new ideas, test these ideas, and even come up with new theories without humans doing much.

Future robot scientists could use lots of sensors to watch the world, analyze what they see, make guesses about how things work, test those guesses, and then come up with new theories, all on their own.

Li and Guo underline that AI will make science faster and more automated, but it’s important that AI’s work is clear, makes sense, and can be trusted. While old ways of doing science are still good, using big data and AI makes everything better and quicker.

Robot scientists, with their ability to process huge amounts of information and think in new ways, could do science in ways we can’t even imagine now. Li and Guo envision how AI robots can go from just helping scientists to being scientists themselves, exploring new areas of knowledge.

We are facing, Li and Guo conclude, “a totally new science realm in which everything is changing or has changed.” In the new science process, “correlation supersedes causation.”

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Low power neuromorphic electronics for AI applications

Researchers at Seoul National University have developed hardware for artificial intelligence (AI) that uses very little power. This hardware is called “neuromorphic hardware” because it is designed to work like the human brain.

The human brain has about 100 billion neurons (nerve cells) and 100 trillion synapses (connections between neurons). These synapses store information and help the brain perform tasks like thinking and learning.

Today’s standard computers for AI applications like large language models (LLMs) use a lot of power to process large amounts of data. These standard computers for AI are based on silicon and use a Von Neumann architecture that separates memory and processing tasks. This can slow down the computer and use more energy.

The new neuromorphic hardware developed by the researchers uses a different approach. It mimics the way the brain works by using memristors. A memristor is a type of electronic component that can store multiple resistance states, similar to how synapses store information. This allows the hardware to perform computations more efficiently and with less power.

The researchers have developed a new type of memristor, based on hybrid organic-inorganic materials, that operates more reliably and uses less energy. This advancement could lead to more efficient AI systems that are better for the environment because they use less power and produce fewer carbon emissions.

Low power neuromorphic hardware for AI (Credit: Seoul National University).

The researchers describe the methods and results of the study in a paper published in Nature Nanotechnology.

Next generation semiconductor devices for AI

“This study provides crucial foundational data for solving the fundamental problems of next-generation intelligent semiconductor devices,” says research leader Ho Won Jang in a Seoul National University press release.

He added that the significance of this work, compared to previous methods, “lies in demonstrating that uniform ion movement across the surface of the material is more important for developing high-performance neuromorphic hardware than creating localized filaments in semiconductor materials.”

This work could help overcome the limitations of current computer systems and lead to the development of more advanced and energy-efficient AI technologies. This is especially relevant as AI continues to play a larger role in various fields.

“This breakthrough in intelligent semiconductor materials boosts commercialization potential and marks a leap forward for AI tech,” Seoul National University posted to X.

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Eye implant developed by BCI startup helps AMD patients see better

A brain-computer interface (BCI) startup called Science has shared some exciting news about a BCI device called PRIMA.

This device is an eye implant meant to help people who have lost their ability to see well because of a condition called geographic atrophy (GA), which is an advanced form of age-related macular degeneration (AMD). AMD affects the part of the eye that helps us see clearly, called the macula.

PRIMA is a tiny chip, about the size of a small grain of rice. This chip has around 380 pixels that change light into electrical signals.

Once PRIMA is implanted in the back of the eye, the recipient wears special glasses with a camera. The camera sends what it sees to the PRIMA chip through infrared light. The chip then turns this light into electrical signals and sends the signals to the brain, helping the person see shapes and objects again.

The company has tested this technology in a study called PRIMAvera. In the trial, 38 people with GA received the PRIMA implant. After a year, those who stayed in the study could read almost five more lines on a vision chart than they could before.

A turning point

”The results demonstrate a milestone in the treatment of blindness caused by geographic atrophy due to age-related macular degeneration. For the first time it was possible to restore real form vision in a retina that has deteriorated due to age-related macular degeneration” says PRIMAvera scientific coordinator Frank Holz. “Prior to this, there have been no real treatment options for these patients,”

These promising results suggest that PRIMA could be a big step towards helping people with AMD see better.

The goal of the trial was not just to see if PRIMA works but also to make sure it’s safe for people to use. The hope is to get a safety and performance certification from European authorities.

“This represents an enormous turning point for the field,” continues Hodak, “and we’re incredibly excited to bring this important technology to market over the next few years.”

Hodak is a co-founder and former President of Elon Musk’s BCI company Neuralink.

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Space-based solar power for Iceland

A British company called Space Solar and an Icelandic company called Transition Labs are planning to give Iceland electricity from space. They plan to build a space-based solar power (SBSP) plant, which means they’ll put solar panels in space to catch sunlight.

Solar panels turn sunlight into electricity. When these panels are in space, they can work all the time because there’s no night or clouds to block the sun. This is different from solar panels on Earth, which only work when it’s sunny.

Space Solar and Transition Labs are working with Iceland’s electricity company Reykjavik Energy. They’ve agreed to start sending power down to Iceland by the year 2030. This would be the first operational SBSP plant to send energy from space to use on Earth.

The initial SBSP plant would generate 30 megawatts (MW) of power. A megawatt is a lot of electricity, enough to power many homes. But the companies wouldn’t stopping there; they want to make even bigger plants by 2036 that could send back gigawatts (GW) of power. A gigawatt is a thousand megawatts, so that’s a lot more electricity.

To get the electricity from space to Earth, the SBSP plant would send high-frequency radio waves down to special antennas on Earth. These antennas would catch the waves and turn their energy back into electricity that we can use.

The promise of SBSP

John Mankins covers SBSP concepts and technologies in detail in his book “The Case for Space Solar Power” (2014).

This idea of getting power from space might sound like science fiction, but it is an actual possibility. It could give us a way to get energy without needing fossil fuels like coal or oil, which are bad for the environment. Of course there are big challenges, first and foremost the fact that sending equipment into space is still expensive. But the costs are going down.

People are excited about this because it could change how we get our energy, making it cleaner and possibly cheaper over time and providing yet one more compelling argument in support of space operations.

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Philip Rosedale returns to Second Life as Linden Lab CTO

Philip Rosedale, the visionary behind Second Life, has returned to the platform he founded, New World Notes reports.

Second Life, a pioneering virtual world launched in the early 2000s, is a Virtual Reality (VR) world built and programmed by its users with realtime, in-world tools. Today Second Life doesn’t often make news headlines as it did in the late 2000s. But it is still there and it has stood the test of time.

After leaving Second Life, Rosedale explored the frontiers of VR with High Fidelity, a project aimed at creating immersive, high-quality VR experiences.

Rosedale is returning to Second Life with a conviction that this platform still holds untapped potential. He envisions a revitalized Second Life that not only keeps up with but also sets the pace for emerging digital trends.

Rosedale will be Chief Technology Officer (CTO) of Second Life’s parent company Linden Lab.

One of the key areas Rosedale is focusing on is the expansion of Second Life’s user base. Currently, the platform boasts a user engagement of around half a million monthly active users. His strategy includes the development of a mobile application, recognizing the shift in digital consumption towards mobile devices. This move could potentially democratize access to Second Life, making it more appealing to a broader audience who might not engage with virtual worlds on traditional computing platforms.

Moreover, Rosedale has expressed concerns about the direction of other virtual platforms, particularly regarding the limitations they impose on user creativity and economic freedom.

Rosedale is using X to engage directly with the Second Life community.

The future of Second Life

Rosedale’s return to Second Life is not just a nostalgic journey but a strategic move to leverage his experience and vision for the future of virtual spaces. His renewed involvement signals a new chapter for Second Life, potentially setting it on a path to recapture its pioneering spirit in the ever-evolving landscape of VR and digital interaction.

In particular, Rosedale wants to more Artificial Intelligence (AI)-related features to Second Life. He refers to “many experimental projects underway… that are related to AI in different ways.”

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A landscape of theories of consciousness

Robert Lawrence Kuhn, the producer and host of the PBS program Closer to Truth, has analyzed theories of consciousness – how physical matter in the brain could produce subjective experiences, or what it “feels like” to be someone.

This puzzle, often called “the hard problem” of consciousness research, is foundational in philosophy and neuroscience.

Kuhn has created a structured “landscape” or taxonomy of various theories that try to explain consciousness.

“I have discussed consciousness with over 200 scientists and philosophers,” says Kuhn in a press release issued by the Foundational Questions Institute (FQxI). “Landscape is the product of a lifetime.”

Kuhn is a member of FQxI’s scientific advisory council.

Kuhn has published his monumental 175,000 words taxonomy in Progress in Biophysics and Molecular Biology.

Kuhn’s taxonomy divides theories into categories: materialism, quantum theories, panpsychism, dualism, idealism, and other frameworks that mix different perspectives.

Materialist theories propose that physical processes in the brain generate consciousness. Non-reductive physicalism suggests that while consciousness is rooted in the brain, physical processes in the brain alone cannot fully explain it.

Quantum theories propose that consciousness might involve quantum mechanics, and panpsychism suggests that some form of consciousness might be a basic property of all matter.

Dualism suggests that the mind and body are separate but interacting substances, and idealism proposes that consciousness or the mind is the primary substance of reality.

Understanding consciousness

Understanding consciousness could change our views on free will, whether AI could ever be conscious, and if consciousness might continue after death.

Kuhn does not aim to solve these issues but seeks to collect and organize perspectives for deeper insight.

“In my Landscape review, I did not want to defend, or even to offer, my own view because it might skew perceptions of the entire enterprise,” says Kuhn in an essay published by FQxI last week. “I try to present each theory as accurately and persuasively as I can, usually with the words of its creator.”

Kuhn adds that he himself leans toward a mix of dualism and idealism, with some interest in quantum consciousness.

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Better 3D printable concrete mixed with graphene

Researchers at the University of Virginia have made a step forward in 3D printing technology for concrete.

The researchers have created a new kind of concrete that is stronger, lasts longer, and is better for the environment. This concrete is mixed with graphene, a super thin and strong material made from carbon, along with limestone and calcined clay cement.

3D printing in construction means using a machine to build things layer by layer (additive manufacturing), just like how a regular 3D printer works but on a much bigger scale. Instead of the plastic materials used in regular 3D printers, 3D printers for construction use concrete.

The new concrete mix helps to cut down on the carbon emissions that come from making regular concrete.

The researchers looked at how well the concrete could be printed and how strong it was. They found that this new concrete mix not only prints well but also holds up better over time. This means buildings made with this concrete could last longer without needing repairs.

The researchers describe the methods and results of this study in a paper published in the Journal of Building Engineering.

Innovation for the future of construction

A life cycle assessment of the overall environmental impact showed that the process is much kinder to the environment than previous methods.

Traditional concrete making contributes a lot to carbon emissions globally. “Our goal was to design a printable concrete that performs better and is more eco-friendly,” says professor Osman Ozbulut in a University of Virginia press release. “This kind of innovation is essential for the future of construction,” adds research co-leader Tuğba Baytak.

The press release and the paper focus on the low environmental impact of the new 3D printable concrete, but the economic advantages of construction materials that last longer also come to mind. The researchers have studied preliminary applications to transportation infrastructure to showcase the real-world potential of the work. Future applications could extend the advantages of 3D printing to the full range of construction works.

In related news, university team in Chile has built a large 3D printed concrete home, Reuters reports.

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Stephen Wolfram’s new physics could actually work

Physicist and science communicator Sabine Hossenfelder has described the new approach to fundamental physics proposed by maverick scientist Stephen Wolfram as a Theory of Everything that could actually work.

Hossenfelder explains that Wolfram’s theory “is basically an attempt to put the simulation hypothesis on a solid mathematical  basis.” Wolfram is looking for code, Hossenfelder says, “that will produce fundamental physics as we know and like it, with gravity and the particles in the standard model.”

Wolfram outlined his then preliminary ideas on fundamental physics in a chapter of his book “A New Kind of Science” (2002). Then he collected further thoughts in an essay titled “What Is Spacetime, Really?” (2015).

It’s worth noting that the late lamented, recently departed mathematician Ralph Abraham had anticipated some of Wolfram’s ideas in a 2010 book.

Hossenfelder also establishes parallels with Rafael Sorkin’s causal set theory.

Wolfram’s book “A Project to Find the Fundamental Theory of Physics” (2020) includes his 2015 essay and the chapter on fundamental physics in “A New Kind of Science.” The book also includes an introduction written like a press release, titled “Finally We May Have a Path to the Fundamental Theory of Physics… and It’s Beautiful.”

“This is probably part of the reason why physicists mostly ignore Wolfram,” says Hossenfelder. “He doesn’t follow standard procedure.” The standard procedure would be “just publishing a paper like normal people.”

The Wolfram Physics Project

Wolfram’s 2020 book is the bible of the Wolfram Physics Project to derive fundamental physics from the discrete mathematics of hypergraphs. Hypergraphs, Hossenfelder explains, are sets of graphs, where graphs are sets of points connected by links. In Wolfram’s Physics Project, Wolfram and his collaborators are investigating how space, time, matter, end everything else including quantum behavior, could emerge from these hypergraphs.

Hossenfelder notes that it is one of Wolfram’s collaborators, Jonathan Gorard, “who did most of this work.”

Gorard posted to X to thank Hossenfelder. “Spending the last 5 years watching Stephen take sole credit for ideas, insights, developments, and discoveries that were the products of our collaboration,” he said, “has been a uniquely exhausting experience.”

Despite whatever bad things other physicists (who may be just envious of Wolfram’s fame and money) may say about Wolfram, it will be very interesting to see how this project develops.

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OpenAI denies rumors but confirms plans for new AI technology

Last week The Verge reported rumors that OpenAI would launch Orion, its next Large Language Model (LLM), by December.

According to the rumors, Orion would be up to 100 times more powerful than GPT-4. Over time, OpenAI would combine it with other Artificial Intelligence (AI) tools, likely including the o1 reasoning model that OpenAI released in September. Eventually, OpenAI would “create an even more capable model that could eventually be called artificial general intelligence, or AGI.”

Alongside anonymous sources, The Verge cited a September X post reporting that “Tadao Nagasaki of OpenAI Japan unveiled plans for ‘GPT Next,’ promising an Orders of Magnitude (OOMs) leap.” According to the post, the new AI model “aims for 100x more computational volume than GPT-4, using similar resources but with improved architecture and efficiency. Trained on a compact Strawberry version, it’s set for release later this year.”

Strawberry is a code name for OpenAI’s o1 reasoning model.

OpenAI CEO San Altman posted to X to deny the rumors, calling them “fake news out of control.”

The editors of The Verge have changed the original story to add that “OpenAI spokesperson Niko Felix told The Verge that the company doesn’t ‘have plans to release a model code-named Orion this year’ but that ‘we do plan to release a lot of other great technology.'”

OpenAI previously told TechCrunch that The Verge’s report wasn’t accurate, but declined to elaborate further. However, TechCrunch notes that OpenAI’s statement leaves substantial wiggle room and conclude that “At this point, it’s anyone’s guess.”

The march of OpenAI

This is a developing story that AI researchers and enthusiasts will want to follow closely. Felix confirmed that OpenAI plans to release “great technology” soon.

OpenAI has been in the top technology and business news in the last few years. It has launched what is arguably the most impactful technology trend of this decade, and its valuation has skyrocketed as a result.

It seems plausible that OpenAI could continue to generate game-changers in the fast-developing world of AI research and applications.

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