Tech
AI could make it easier to create bioweapons that bypass current security protocols
Artificial intelligence is transforming biology and medicine by accelerating the discovery of new drugs and proteins and making it easier to design and manipulate DNA, the building blocks of life. But as with most new technologies, there is a potential downside. The same AI tools could be used to develop dangerous new pathogens and toxins that bypass current security checks. In a new study from Microsoft, scientists employed a hacker-style test to demonstrate that AI-generated sequences could evade security software used by DNA manufacturers.
“We believe that the ongoing advancement of AI-assisted protein design holds great promise for tackling critical challenges in health and the life sciences, with the potential to deliver overwhelmingly positive impacts on people and society,” commented the researchers in their paper published in the journal Science. “As with other emerging technologies, however, it is also crucial to proactively identify and mitigate risks arising from novel capabilities.”
Testing defenses
When biotech companies make DNA for researchers, they use Biosecurity Screening Software (BSS) to look for similarities between the new sequence and a database of known threats. And that is both a strength and a weakness because it can only screen against what is listed in the database.
To test this biosecurity gap, the Microsoft researchers used publicly available AI programs to create more than 76,000 synthetic variants of known dangerous proteins, including ricin. They didn’t actually produce the proteins; they designed the genetic instructions for their synthesis. Then they ran the sequences through four different screening software tools to see if any could slip through. And they did—in big numbers. A significant percentage of these AI-designed sequences breezed through the checks.
After discovering the flaws, the Microsoft team worked with BSS providers to develop patches. These included updating threat databases and fine-tuning the screening software. The result? The beefed-up screening tools caught 97% of the most dangerous sequences in a second test.
The research serves as a clear warning. Even though the patches increased the detection rate, they were not foolproof, as 3% of potentially dangerous sequences were missed. It’s also unclear how the resulting proteins would perform in the real world, as the sequences were computer predictions.
Clearly, more work will be needed to build robust defenses against increasingly sophisticated AI techniques, but this effort will be ongoing. A constant evolutionary arms race is inevitable. Just as vaccines must keep pace with new viral mutations, so too will biosecurity screening tools need continuous updates to counter AI-generated threats.
Written for you by our author Paul Arnold, edited by Gaby Clark, and fact-checked and reviewed by Robert Egan—this article is the result of careful human work. We rely on readers like you to keep independent science journalism alive.
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More information:
Bruce J. Wittmann et al, Strengthening nucleic acid biosecurity screening against generative protein design tools, Science (2025). DOI: 10.1126/science.adu8578
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AI could make it easier to create bioweapons that bypass current security protocols (2025, October 3)
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Tech
Framework Has a Better, More Take-Apart-Able Laptop
Framework, the company that makes laptops designed for optimal repairability, announced a new version of its main product, a 13-inch screen laptop. It’s called the Framework Laptop 13 Pro, and it has far better battery life, a touchscreen, a haptic touchpad, and is fitted with Intel processors.
At an event in San Francisco today, Framework CEO Nirav Patel showed off the company’s new tech, opening with a joke about making Framework AI—something the company is very much not doing. Framework’s whole thing, after all, is aiming to give users control over the physical tech they use.
“That industry is fighting for you to own nothing, and they own everything,” Patel said about the AI industry. “We’re fighting for a future where you can own everything and be free.”
Framework used the event to detail other updates coming to its 16-inch laptop. It also showed off previews of an official developer kit and a wireless keyboard for controlling your rig from the couch.
Framework 13 Pro
As the name implies, the 13 Pro is a step up from the company’s last version, the Framework 13. It’s also pricier, starting at $1,199 for a DIY Edition that requires assembling the computer yourself. Pre-built units start at $1,499 but can be upgraded with more features. Framework says it will start shipping the 13 Pro in June.
Framework’s signature move for its products is the ability to take the thing apart. The 13 Pro is made with that ethos in mind, so its parts can be easily swapped out, upgraded, or replaced. Four Thunderbolt 4 interfaces let you pick which ports (USB-C, HDMI, etc.) you want and then choose where to place them. Framework says it planned the laptop with cross-generation compatibility in mind, so current Framebook 13 laptop owners will be able to use new 13 Pro parts like the mainboard, display, and battery, and put them into their existing machine.
The big changes in the guts of the 13 Pro come from Framework’s shift away from using an AMD processor to Intel’s Core Ultra Series 3 processors, which Framework described in its press release as “just insanely efficient.” That efficiency, along with a bigger battery, translates to more than 20 hours of battery life while streaming 4K Netflix videos, at least that’s the claim. That’s almost 12 hours longer than the Framework 13.
Courtesy of Framework
Courtesy of Framework
Tech
OpenAI Beefs Up ChatGPT’s Image Generation Model
OpenAI launched a new image generation AI model on Tuesday, dubbed ChatGPT Images 2.0. This model can generate more than one image from a single prompt, like an entire study booklet, as well as output text, including in non-English languages, like Chinese and Hindi. This release is available globally for ChatGPT and Codex users, with a more powerful version available for paying subscribers.
When any major AI company releases a new image model, it can revive interest and boost usage, especially if social media users adopt a meme-able trend, transforming images of themselves. Last year, Google’s launch of the Nano Banana model was a major moment for the company, especially when users started posting hyperrealistic figurines of themselves online. Earlier this year, ChatGPT Images made waves on social media as users shared AI-generated caricatures.
What’s Different?
Since the new model can tap into ChatGPT’s “reasoning” capabilities, Images 2.0 can search the internet for recent information and generate more than one image at a time. In essence, the bot can use additional steps to output more thorough generations from a single prompt. Images 2.0 also has a more recent knowledge cutoff date: December 2025.
This also means that outputs from the new model are more granular. For example, I generated an infographic with San Francisco’s weather forecast for the next day, as well as activities worth doing. The image ChatGPT generated included accurate weather details for the rainy day, along with accurate-looking drawings of the Ferry Building, Castro Theater, Painted Ladies houses, and Transamerica Pyramid.
Additionally, Images 2.0 is more customizable for users who want unique aspect ratios for image outputs. The new model can generate images, ranging from 3:1 wide to 1:3 tall, and users can adjust the image’s size as part of their prompt to the AI tool.
First Impressions
After a few hours of generating images with the new model, I was generally impressed with the text rendering capabilities, in English at least. Not that long ago, image outputs featuring text, from any of the major models, often included numerous malformed characters or words with errant extra letters. ChatGPT struggled to label images accurately two years prior, so the cleaner, more complex outputs from Images 2.0 are a sign of continued improvement. Google has also focused on improving image outputs featuring text in its recent iterations of Nano Banana.
Tech
TAG Heuer Has Dropped New Polylight-Powered F1s
No doubt looking to find some breathing space after the hubbub of Watches and Wonders last week, TAG Heuer has dropped an update to its 2025 revamped collection of the brand’s iconic plastic-cased 1980s watch, the “Formula 1.”
The five new pieces are called the “pastel collection” by TAG, and all are built on the same solar-powered Formula 1 Solargraph 38 mm that launched in March last year. Two models feature a sandblasted stainless steel case, while the remaining three have cases made from TAG’s proprietary bio-polamide plastic, Polylight.
It’s these Polylight versions that, for WIRED, are the stars of the new mini collection. Coming in pastel blue, beige, and pink, and sporting case-matching rubber straps and bidirectional-rotating Polylight bezels, they reference classic F1 designs that made the line iconic in the first place.
The stainless steel models have a 3-link sandblasted steel bracelet and either a “pastel green” or “lavender blue” dial with matching Polylight bezels. The dials on both watches also see eight diamonds replace the circular hour markers. TAG says these models add “a touch of refinement for those seeking sophistication,” but considering these “luxury” F1s will retail at $2,800, as opposed to the already punchy $1,950 full Polylight versions, our pick is most definitely the plastic pieces.
Not only do these blue, beige, and pink versions pleasingly hark back to vintage F1 designs—though now 38 mm in size instead of the original 35 mm—but also, just like all F1 Solargraphs, they come equipped with screw-down crowns and casebacks, making for 100 meters of water resistance and ensuring these will serve well as dive and sports watches. My recommendation? Go for the pink, it looks superb on the wrist. The beige is a very close second.
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