On Thursday, a US District Court in Oregon ordered the US government to restart the process of approving wind projects. All new wind development in the US has been on hold since August 2025, when the Department of Defense (DoD) stopped participating in a process that allows it to compel developers to alter projects in order to limit their interference with radar equipment. The court ruled, however, that the DoD's national security claims did not allow it to opt out of a process that is legally mandated.

The Trump administration has made many attempts to block wind development, both offshore and land based. Its attempts to stop offshore wind included the same approach at issue in this case: Claim that drone developments mean that radar interference by wind turbines creates a national security risk. The courts were not sympathetic to this claim, including in cases where judges examined a classified report that the DoD was using to justify blocking offshore wind construction. As a result, the administration has turned to paying companies not to pursue wind development.

In parallel, the government was pursuing a similar approach for onshore wind. Here, a law lays out a process for the DoD to evaluate any problems posed by wind turbines and negotiate changes to planned wind farms with the developers. As laid out in the new decision, the government simply stopped participating in this process in August 2025, first by refusing to sign off on previously negotiated agreements, and later by refusing to draft agreements entirely. Eventually, it simply refused to participate in negotiations at all. This has brought a halt to all wind development in the US.

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On Thursday, a US District Court in Oregon ordered the US government to restart the process of approving wind projects. All new wind development in the US has been on hold since August 2025, when the Department of Defense (DoD) stopped participating in a process that allows it to compel developers to alter projects in order to limit their interference with radar equipment. The court ruled, however, that the DoD's national security claims did not allow it to opt out of a process that is legally mandated.

The Trump administration has made many attempts to block wind development, both offshore and land based. Its attempts to stop offshore wind included the same approach at issue in this case: Claim that drone developments mean that radar interference by wind turbines creates a national security risk. The courts were not sympathetic to this claim, including in cases where judges examined a classified report that the DoD was using to justify blocking offshore wind construction. As a result, the administration has turned to paying companies not to pursue wind development.

In parallel, the government was pursuing a similar approach for onshore wind. Here, a law lays out a process for the DoD to evaluate any problems posed by wind turbines and negotiate changes to planned wind farms with the developers. As laid out in the new decision, the government simply stopped participating in this process in August 2025, first by refusing to sign off on previously negotiated agreements, and later by refusing to draft agreements entirely. Eventually, it simply refused to participate in negotiations at all. This has brought a halt to all wind development in the US.

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A lot of the AI work in biology has been focused on designing proteins. That's partly because proteins do most of the business of life, catalyzing the interesting chemistry and structuring cells. So, figuring out how to make a new protein can mean directly tinkering with biochemistry, providing new and potentially useful functions.

Since the genetic code provides a layer of abstraction between DNA and proteins, it wasn't obvious what a model trained on DNA could do. Yet people went ahead and made a large genome model, and it turned out to be able to output DNA sequences that could encode functional proteins in bacteria and mimic the gene structures found in complex cells. Now, those same models have been used to output the genomes of viruses that infect bacteria.

This isn't science fiction—all the viruses the models created are closely related to an existing virus. But they do have some distinct features that would be challenging to evolve. And the researchers who did the work, based at Stanford University, suggest we may want to start thinking now about preparing for the potential that someone could develop a related AI that can design a virus that targets vertebrates.

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D-Wave is a bit of an oddity in the quantum computing space, having been founded back in the last century. And its initial offering wasn't a quantum computer like those being developed by IBM or Google. Instead, the company built what's now called a quantum annealer, a machine that isn't general-purpose but can solve a large class of optimization problems. While the hardware shares some similarities with the qubits used in gate-based quantum computers, it operates in a fundamentally different way.

But a few years back, D-Wave started working on gate-based hardware, apparently choosing a somewhat unusual qubit technology called fluxonium. And this year, the company acquired a startup called Quantum Circuits that spun out of Yale University and has been developing what's called a dual-rail qubit (the same technology used by Amazon), which promises to make most errors very easy to detect, simplifying error correction.

On Wednesday, the company is publishing a paper in Nature that describes a key step in validating this dual-rail technology, showing that two of the qubits can be entangled without altering their best feature: Most are a single type that is easy to detect.

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