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Nvidia’s $3K “Digits” GB10 Supercomputer

The mention of gravity and quantum in the same sentence often elicits discomfort from theoretical physicists, yet the effects of gravity on quantum information systems cannot be ignored. In a recently announced collaboration between the University of Connecticut, Google Quantum AI, and the Nordic Institute for Theoretical Physics (NORDITA), researchers explored the interplay of these two domains, quantifying the nontrivial effects of gravity on transmon qubits.

Led by Alexander Balatsky of UConn’s Quantum Initiative, along with Google’s Pedram Roushan and NORDITA researchers Patrick Wong and Joris Schaltegger, the study focuses on the gravitational redshift. This phenomenon slightly detunes the energy levels of qubits based on their position in a gravitational field. While negligible for a single qubit, this effect becomes measurable when scaled.

While quantum computers can effectively be protected from electromagnetic radiation, barring any innovative antigravitic devices expansive enough to hold a quantum computer, quantum technology cannot at this point in time be shielded from the effects of gravity. The team demonstrated that gravitational interactions create a universal dephasing channel, disrupting the coherence required for quantum operations. However, these same interactions could also be used to develop highly sensitive gravitational sensors.

“Our research reveals that the same finely tuned qubits engineered to process information can serve as precise sensors—so sensitive, in fact, that future quantum chips may double as practical gravity sensors. This approach is opening a new frontier in quantum technology.”

To explore these effects, the researchers modeled the gravitational redshift’s impact on energy-level splitting in transmon qubits. Gravitational redshift, a phenomenon predicted by Einstein’s general theory of relativity, occurs when light or electromagnetic waves traveling away from a massive object lose energy and shift to longer wavelengths. This happens because gravity alters the flow of time, causing clocks closer to a massive object to tick more slowly than those farther away.

Historically, gravitational redshift has played a pivotal role in confirming general relativity and is critical to technologies like GPS, where precise timing accounts for gravitational differences between satellites and the Earth’s surface. In this study, the researchers applied the concept to transmon qubits, modeling how gravitational effects subtly shift their energy states depending on their height in a gravitational field.

Using computational simulations and theoretical models, the team was able to quantify these energy-level shifts. While the effects are negligible for individual qubits, they become significant when scaled to arrays of qubits positioned at varying heights on vertically aligned chips, such as Google’s Sycamore chip.

AI categorizes 700 million aurora images for better geomagnetic storm forecasting

The aurora borealis, or northern lights, is known for a stunning spectacle of light in the night sky, but this near-Earth manifestation, which is caused by explosive activity on the sun and carried by the solar wind, can also interrupt vital communications and security infrastructure on Earth. Using artificial intelligence, researchers at the University of New Hampshire have categorized and labeled the largest-ever database of aurora images that could help scientists better understand and forecast the disruptive geomagnetic storms.

The research, recently published in the Journal of Geophysical Research: Machine Learning and Computation, developed artificial intelligence and machine learning tools that were able to successfully identify and classify over 706 million images of auroral phenomena in NASA’s Time History of Events and Macroscale Interactions during Substorms (THEMIS) data set collected by twin spacecrafts studying the space environment around Earth. THEMIS provides images of the night sky every three seconds from sunset to sunrise from 23 different stations across North America.

“The massive dataset is a valuable resource that can help researchers understand how the interacts with the Earth’s magnetosphere, the protective bubble that shields us from charged particles streaming from the sun,” said Jeremiah Johnson, associate professor of applied engineering and sciences and the study’s lead author. “But until now, its huge size limited how effectively we can use that data.”

Record cold quantum refrigerator paves way for reliable quantum computers

Quantum computers require extreme cooling to perform reliable calculations. One of the challenges preventing quantum computers from entering society is the difficulty of freezing the qubits to temperatures close to absolute zero.

Now, researchers at Chalmers University of Technology, Sweden, and the University of Maryland, U.S., have engineered a new type of refrigerator that can autonomously cool superconducting qubits to record , paving the way for more reliable quantum computation.

Quantum computers have the potential to revolutionize fundamental technologies in various sectors of society, with applications in medicine, energy, encryption, AI, and logistics. While the building blocks of a classical computer—bits—can take a value of either 0 or 1, the most common building blocks in quantum computers—qubits—can have a value of 0 and 1 simultaneously.

Elon Musk JUST Dropped Massive Bombshell on Tesla Bots, Neuralink and Major Tesla Updates | CES 2025

At CES 2025, Elon Musk joined Mark Penn the Stagwell CEO, and 25 CMOs to discuss AI, robotics, Neuralink, space exploration, and Mars colonization. Musk shared bold predictions on AI’s role in cognitive tasks, humanoid robots, autonomous cars, and X’s future as a platform for collective human consciousness. They also explored government’s role in tech, internet connectivity, and combating global pessimism.

00:00 Introduction and Welcome.
01:52 Elon Musk on AI and Future Technology.
05:12 Advancements in Self-Driving Cars.
07:23 Humanoid Robots and Their Impact.
09:26 Mars Colonization Plans.
11:24 Neuralink and Brain-Computer Interfaces.
14:03 Government Efficiency and Budget Cuts.
17:49 Freedom of Speech and Social Media.
23:50 Optimism for the Future.

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Multiverse simulation: Robotic AI is about to accelerate sharply

The AI behavior models controlling how robots interact with the physical world haven’t been advancing at the crazy pace that GPT-style language models have – but new multiverse ‘world simulators’ from Nvidia and Google could change that rapidly.

There’s a chicken-and-egg issue slowing things down for AI robotics; large language model (LLM) AIs have enjoyed the benefit of massive troves of data to train from, since the Internet already holds an extraordinary wealth of text, image, video and audio data.

But there’s far less data for large behavior model (LBM) AIs to train on. Robots and autonomous vehicles are expensive and annoyingly physical, so data around 3D representations of real-world physical situations is taking a lot longer to collect and incorporate into AI models.

AI could crack unsolvable problems — and humans won’t be able to understand the results

AI promises to help scientists do more, faster, with less money. But it brings a host of new concerns, too — and if scientists rush ahead with AI adoption they risk transforming science into something that escapes public understanding and trust, and fails to meet the needs of society.

Experts have already identified at least three illusions that can ensnare researchers using AI.

Dr. Marcia McNutt — President, National Academy of Sciences — Shaping Culture & Conduct Of Science

Shaping The Culture & Conduct Of Science — Dr. Marcia McNutt Ph.D. — President, National Academy Of Sciences


Dr. Marcia McNutt, Ph.D. is President of the National Academy of Sciences (https://www.nasonline.org/directory-e…), where she also chairs the National Research Council, the operating arm of the National Academies of Sciences, Engineering, and Medicine, and serves a key role in advising our nation on various important issues pertaining to science, technology, and health.

From 2013 to 2016, Dr. McNutt served as editor-in-chief of the Science journals.

Dr. McNutt is a geophysicist who prior to joining Science, was director of the U.S. Geological Survey (USGS) and science adviser to the United States Secretary of the Interior from from 2009 to 2013. During her tenure, the USGS responded to a number of major disasters, including earthquakes in Haiti, Chile, and Japan, and the Deepwater Horizon oil spill.

Dr. McNutt led a team of government scientists and engineers at BP headquarters in Houston who helped contain the oil and cap the well. She directed the flow rate technical group that estimated the rate of oil discharge during the spill’s active phase. For her contributions, she was awarded the U.S. Coast Guard’s Meritorious Service Medal.

Entering The Artificial General Intelligence Spectrum In 2025

Technological development has hit warp speed – in a flash, stars have stretched into starlines and where we are today is far from where we were just days ago. It’s increasingly difficult to predict where we will be tomorrow.

One thing is clear: we are entering the Artificial General Intelligence (AGI) spectrum and Artificial Superintelligence (ASI) now seems clearly within reach. However it is defined, AGI will not appear suddenly; it will evolve and already we see signs of its incremental unfolding.

AGI has long been the ultimate goal—a technology capable of performing the mental work of humans, transforming how we work, live, think. Now, as we step into 2025, glimmers of AGI are already appearing and promise to grow stronger as the year moves along.