With dozens of companies, from small startups to tech giants, pursuing quantum computing, there's a steady flow of results as they try to find a path to utility. We typically focus on new technologies and major landmarks, which can obscure the fact that any big success will inevitably have been built on a lot of incremental progress.

The past few weeks have seen a number of companies release progress reports on how they're trying to get the technologies closer to general use. None of these represents a major breakthrough, but all are absolutely necessary for the technology to advance. The idea here is to convey the hard work required to move us closer to something useful.

Microsoft does material science

Microsoft is one of the few companies working on topological qubits, based on the distinct physics that occurs when particles are confined. Microsoft's system relies on a thin superconducting wire placed on top of a semiconductor. In superconductors, groups of two electrons form Cooper pairs. But if the wire contains an odd number of conducting electrons—meaning there's a single unpaired electron—it will end up delocalized to both ends of the wire. (Because quantum mechanics is weird.)

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A case of New World screwworm has been reported in South Texas. If confirmed, it would be the first detected breach of the US-Mexico border by the ravenous flesh-eating flies , which have been making their way up through Central America for the past several years.

In a social media post Wednesday afternoon , the US Department of Agriculture said a "sample is now at USDA's National Veterinary Services Laboratories (NVSL) in Ames, lowa for confirmatory testing. We will provide updates the moment results are available." It added that "We have already activated personnel on the ground and are working with local partners."

Chatter of a screwworm detection had already been building this week, rattling the US cattle industry.

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UK regulators today ordered Google to put clearer attributions and links to publishers' content in its AI-generated search features. The UK's Competition and Markets Authority (CMA) also said Google must give publishers a way to opt out of AI features in search.

"In a world first, publishers will now have effective tools to prevent their content being used to power AI features in search, such as AI Overviews," the CMA said today . "This will put publishers, like news organizations, in a stronger position to negotiate content deals with Google. To boost consumer trust, Google is also now required to make sure that publisher content is properly attributed, using clear links, in AI‑generated search results."

The CMA ruled that Google may not penalize publishers for opting out of AI, meaning that Google can't downrank opted-out publishers in general search results. The CMA said Google will have nine months to comply with all requirements but that the agency "expects important parts of the controls to become available to publishers well before that deadline. Google will also be required to submit and publish compliance reports, supported by key data and metrics, explaining changes it has made and how it has complied."

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There’s a lot that doesn’t add up in a security advisory password manager Dashlane published Monday, warning that attackers managed to obtain 20 encrypted user vaults.

“Starting on Sunday, May 31, 2026, an external party launched a brute force attack against certain Dashlane user accounts,” the company said . “The goal of the attack was to brute-force two-factor authentication (2FA) protections to allow the attacker to register new devices on existing user accounts.”

Hello, Dashlane, anybody home?

A Dashlane user who received such a 2FA request provided this screenshot of the notification, which arrived on Sunday.

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The generative AI boom has driven the cost of memory into the stratosphere, and Google is a key part of that trend. So it's only fitting that Google should offer some less RAM-hungry local AI models. The company has announced the release of a new Gemma 4 model that fills a gap in the lineup that launched earlier this year. The new model is efficient enough that you may be able to run it on a pretty average consumer laptop.

In April, Google released four models in the Gemma 4 family , which also marked the shift to a more open Apache 2.0 license. The initial models included two mobile-optimized options (E2B and E4B) along with a pair of models for more serious work (26B Mixture of Experts and 31B Dense). That left a rather large unserved space in the middle, which is right where the new model falls.

Gemma 4 12B is considerably more capable than the mobile versions, but it won't require a $20,000 AI accelerator to run locally. Google says Gemma 4 12B is unique in that it can run on many consumer laptops without sacrificing quality. As long as you've got a computer with 16GB of system RAM or VRAM, the 12-billion-parameter model will work. That's about half the total memory footprint of Gemma 4 26B MoE, and Google claims the new model is almost as capable, at least as far as benchmarks go.

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On Tuesday, Donald Trump finally signed his executive order expanding the government's efforts to conduct voluntary safety testing of frontier AI models. Now, critics are warning that the order may be short-sighted, offering only performative reassurances that the government is actively monitoring for AI risks, while changing very little about how and when models are deployed.

Last month, Trump abruptly canceled a signing event , where he had hoped to launch an earlier version of the EO with CEOs of leading AI firms in attendance. Invited at the last minute, several CEOs simply couldn't make the signing but still signaled support for the order. Officially, Trump claimed he postponed the event because he worried that the EO might have gone too far and had become a "blocker" impeding AI innovation. Reports indicated there was infighting in his administration as cybersecurity experts clashed with officials committed to deregulating AI.

The watered-down EO that Trump signed promises not "to stifle this innovation with overly burdensome regulation" and establishes no requirements for AI firms. Instead, it sets up a voluntary process for companies to collaborate with the government on safety reviews that Trump's EO claimed would "ensure that the best and most secure technology is deployed rapidly to confront any and all threats to our country."

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Plex is adding new social features to the platform.

As of today, users can make and share "personalized lists on Plex of any movie, show or episode," the company said in an announcement. Later this year, users will be able to import lists from other streaming services and react to other people's lists.

This month, Plex will also launch a community forum that will allow people to "post and comment directly on any movie, show, season, or episode." Later this year, Plex will introduce "Match Scores" based on a viewer's history and past ratings to predict how much they'll like a show or movie, Plex said.

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The age of robotaxis, long the preserve of science fiction, is now a reality, at least in a handful of American cities. It took just over a decade to get from the DARPA Grand Challenges to the start of Waymo's commercial service in California, albeit initially with a safety driver on board.

Proponents of the technology, which has attracted at least $100 billion in investment, say robotaxis will be safer than human-driven vehicles. And last year , Waymo's data showed its cars were involved in many fewer crashes than human drivers, with much lower insurance claims, although recent issues with school buses and flooded roads show the technology isn't perfect .

But safety isn't the only selling point: Autonomous vehicles are said to cut traffic . But data from Waymo's reports to the California Public Utilities Commission shows that, at least in that regard, robotaxis are no better than ride-hailing services like Lyft and Uber.

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A year after Mark Zuckerberg installed Alexandr Wang to jolt Meta’s artificial intelligence efforts into wartime mode, the $1.5 trillion company has produced Muse Spark, its most credible AI model yet.

By handing responsibility for Meta’s AI revival to a then-28-year-old start-up founder rather than a veteran researcher, Zuckerberg bet that an outsider’s urgency and ambition could succeed where the company’s established AI organization had struggled.

According to interviews with current and former Meta employees, and associates of Wang, the billionaire wunderkind has now begun to eke out results, while navigating criticism over his experience, early research challenges, and the esoteric internal politics of working at a Big Tech behemoth.

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