There's a general consensus that we won't be able to consistently perform sophisticated quantum calculations without the development of error-corrected quantum computing, which is unlikely to arrive until the end of the decade. It's still an open question, however, whether we could perform limited but useful calculations at an earlier point. IBM is one of the companies that's betting the answer is yes, and on Wednesday, it announced a series of developments aimed at making that possible.

On their own, none of the changes being announced are revolutionary. But collectively, changes across the hardware and software stacks have produced much more efficient and less error-prone operations. The net result is a system that supports the most complicated calculations yet on IBM's hardware, leaving the company optimistic that its users will find some calculations where quantum hardware provides an advantage.

Better hardware and software

IBM's early efforts in the quantum computing space saw it ramp up the qubit count rapidly, being one of the first companies to reach the 1,000 qubit count. However, each of those qubits had an error rate that ensured that any algorithms that tried to use all of these qubits in a single calculation would inevitably trigger one. Since then, the company's focus has been on improving the performance of smaller processors. Wednesday's announcement was based on the introduction of the second version of its Heron processor, which has 156 qubits (up from an earlier 133 in Revision 1). That's still beyond the capability of simulations on classical computers, should it be able to operate with sufficiently low errors.

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On Tuesday, Google announced that it had made a power purchase agreement for electricity generated by a small modular nuclear reactor design that hasn't even received regulatory approval yet. Today, it's Amazon's turn. The company's Amazon Web Services (AWS) group has announced three different investments, including one targeting a different startup that has its own design for small, modular nuclear reactors—one that has not yet received regulatory approval.

Unlike Google's deal, which is a commitment to purchase power should the reactors ever be completed, Amazon will lay out some money upfront as part of the agreements. We'll take a look at the deals and technology that Amazon is backing before analyzing why companies are taking a risk on unproven technologies.

Money for utilities and a startup

Two of Amazon's deals are with utilities that serve areas where it already has a significant data center footprint. One of these is Energy Northwest, which is an energy supplier that sends power to utilities in the Pacific Northwest. Amazon is putting up the money for Energy Northwest to study the feasibility of adding small modular reactors to its Columbia Generating Station, which currently houses a single, large reactor. In return, Amazon will get the right to purchase power from an initial installation of four small modular reactors. The site could potentially support additional reactors, which Energy Northwest would be able to use to meet demands from other users.

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On Tuesday, the Royal Swedish Academy of Sciences awarded the 2024 Nobel Prize in Physics to John J. Hopfield of Princeton University and Geoffrey E. Hinton of the University of Toronto for their foundational work in machine learning with artificial neural networks. Hinton notably captured headlines in 2023 for warning about the threat that AI superintelligence may pose to humanity. The win came as a surprise to many, including Hinton himself.

"I'm flabbergasted. I had no idea this would happen. I'm very surprised," said Hinton in a telephone call with members of the Royal Swedish Academy of Sciences during a live announcement press conference streamed to YouTube that took place this morning.

Hopfield and Hinton's research, which dates back to the early 1980s, applied principles from physics to develop methods that underpin modern machine-learning techniques. Their work has enabled computers to perform tasks such as image recognition and pattern completion, capabilities that are now ubiquitous in everyday technology.

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Enlarge / A movable robotic face covered with living human skin cells. (credit: Takeuchi et al.)

In a new study, researchers from the University of Tokyo, Harvard University, and the International Research Center for Neurointelligence have unveiled a technique for creating lifelike robotic skin using living human cells. As a proof of concept, the team engineered a small robotic face capable of smiling, covered entirely with a layer of pink living tissue.

The researchers note that using living skin tissue as a robot covering has benefits, as it's flexible enough to convey emotions and can potentially repair itself. "As the role of robots continues to evolve, the materials used to cover social robots need to exhibit lifelike functions, such as self-healing," wrote the researchers in the study.

Shoji Takeuchi, Michio Kawai, Minghao Nie, and Haruka Oda authored the study, titled "Perforation-type anchors inspired by skin ligament for robotic face covered with living skin," which is due for July publication in Cell Reports Physical Science. We learned of the study from a report published earlier this week by New Scientist.

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