Cisco’s new Antares models help security teams narrow vulnerable code searches locally, but low benchmark scores expose important adoption limits.
The post Cisco Antares Models Bring Local AI to Vulnerability Triage appeared first on TechRepublic.
As technologies change and adapt, we’re often left with seemingly useless junk that has nowhere to go. Certainly anyone still sitting on a pile of floppy disks feels this way sometimes, but odds are anyone who owns a mining ASIC or an NFT can attest to that as well. The trillions of dollars flowing into GPU-based data centers will likely become the next victim of this trend, so if you want to capitalize on the losses of some venture capitalist you’ll want to figure out a way to get GPUs meant for a server into your desktop doing useful work.
Of course, calling these devices GPUs is a bit of a stretch compared to the Radeon and GeForce cards many of us are used to using for gaming. These don’t even have a PCIe slot or video output, after all. But, as [Oscar] notes, the VRAM and GPU cores are very real and can still do useful work. An adapter board is able to mate a Tesla V100 SXM2 16 GB GPU to a standard PCIe slot, which solves the first problem, but the major downside from there is that the cooling fan for this unit was literally deafeningly loud. At 82 dB it was about as loud as a lawnmower, which is fine in a server rack but not great in a bedroom. [Oscar] found a way to tamp down the fan speed, making it usable in a home.
Without video output, the utility of these cards mainly comes from adding VRAM and compute for tasks that benefit from parallel computing. Using tensor splitting, [Oscar] is running a local LLM with this card alongside his RTX 4080, providing 32 GB of VRAM on his NixOS system. With his benchmarking tests, the LLM sports impressive stats for a self-hosted model, ranking somewhere around Claude Sonnet 4.6. What’s even more impressive is that this is all done for around £200, and with the rate the various LLM companies are ratcheting up pricing could pay itself back very quickly. If trading off performance for cost is acceptable, though, it’s possible to run local models on much less powerful hardware as well.
In the early years of the United States, when the nascent US Navy was still getting its sea legs, several presidents used privateers to capture or destroy enemy warships when armed naval vessels were unable to do so.
President John Adams was one of the most vigorous proponents of commissioning private vessels for national ends. His administration issued letters of marque and reprisal during the so-called "Quasi-War" with France in the final years of the 18th century. These letters created the legal distinction between privateering and piracy.
One of the letters signed by Adams, dated November 1799, authorized the use of a merchant ship to "subdue, seize, and take any armed French vessel" found near US coastal waters of "elsewhere on the high seas." France also routinely used privateers against US shipping at the time.
© MPI/Getty Images
Jean Paoli has spent his career making documents readable by machines — first as a co-creator of XML, then helping build the file formats behind Microsoft Office. Now his Kirkland, Wash.-based startup, Docugami, is open-sourcing the technology at the heart of its business, betting it can become a standard way to turn documents into data that people and AI agents can trust.
The company is releasing its technology, called DGML (short for Document Graph Markup Language), under Apache 2.0, a widely used open-source license, so other developers and companies can adopt it.
The idea is to turn it into a shared standard that no single company owns, much as XML became a common foundation across the tech industry.
The move reflects a shift in where the value is created in AI. Docugami until now has made its money selling software that turns unstructured documents into usable data. It’s betting now that there’s more value in proving that data is trustworthy instead.
How it works: Docugami is teaming up with Inveniam, a Detroit company whose software helps big investors keep tabs on the mountains of paperwork behind real estate and other hard-to-value assets. Inveniam will record a kind of digital fingerprint of each piece of DGML data on NVNM Chain, its blockchain built with Mantra, a crypto firm that Inveniam is acquiring.
That means, for example, that a single fact buried in a 200-page lease — such as the rental rate, a renewal option, or a default clause — can be verified on its own, without exposing the whole document. An investor, auditor, or AI agent can trace it to the page it came from.
To work with documents, AI systems usually convert them into a simpler format first. DGML enters a growing field of contenders in that regard, competing with the popular Markdown format and DocLang, a new open standard for AI-ready documents backed by IBM, Nvidia and Red Hat.
The business model: This is a big move for a company of Docugami’s size, taking the 30-person startup in a new direction. Paoli is handing the industry the technology his team spent years building, and pinning the company’s future on a larger idea.
The plan is to make money not from the format itself but from the value of the trusted data. Once a company converts its leases or loans into DGML and anchors the key numbers on the blockchain, investors, lenders and auditors can pay to draw on that verified data.
Docugami will share in the revenue through its partnership with Inveniam. The company also stands to collect a small fee each time a piece of data is recorded on the chain.
The company is giving away the DGML format and a working version of the software, but not everything. Paoli said the company is keeping some of its own technology private, including AI models it has fine-tuned to read documents, and could sell those or other tools to enterprises.
“The business model of everybody is changing. And if you know any company where it’s not true, you need to tell me, because I haven’t met them yet,” Paoli said in an interview.
Docugami has raised about $13 million to date, including a $10 million seed round in 2020 that drew the first investment in Grammarly’s history.
The partnership: Paoli met Patrick O’Meara, Inveniam’s CEO, a few months ago, through a former Microsoft colleague who had become one of O’Meara’s advisers. They quickly realized they had been working toward the same idea from different directions.
Inveniam, founded in 2017, helps big investors keep track of assets that are hard to value, like office towers, private loans and infrastructure. It monitors the documents behind those assets and flags changes as they happen, and its clients include some of the world’s largest sovereign wealth funds, according to O’Meara.
What it lacked was a consistent way to break those documents into verifiable pieces. That is what Docugami provides.
“We’re not putting the data itself on-chain, just a fingerprint of the document. Change one bit, one byte, one pixel, and the hash won’t match,” O’Meara said.
The blockchain comes from Mantra, a crypto company run by John Patrick Mullin. Inveniam invested $20 million in Mantra last year and has since agreed to acquire it outright. Mantra’s OM token collapsed in April 2025, erasing several billion dollars in value.
Paoli said the project uses the underlying blockchain, not the token.
“Crypto as an industry has gone through a lot of changes in the last 18 to 24 months, and it’s growing up in a lot of ways. This is a real use case with fundamental value, not just pure speculation,” Mantra’s Mullin said in an interview.
The result is a division of labor: Docugami turns documents into data, Inveniam verifies it and brings the customers, and Mantra provides the chain where the proof is recorded.
The DGML specification, sample documents and reference code are at dgml.io and on GitHub.
Editor’s note: This story was updated after publication to correct the name of a competing document format, DocLang, and to note that Inveniam’s blockchain is called NVNM Chain.
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Did you know there are different Linux terminals, some with unique and special features that can genuinely improve your day-to-day experience? For the average user, the choice doesn't matter much, but if you're planning to get serious about the terminal—using terminal apps, Vim, or Emacs—the terminal you choose becomes almost as important as the Linux distribution you run. With that in mind, here's why I settled on my current terminal, along with how the other popular options compare to my daily driver.
At least in theory, video games are more resistant to becoming lost media thanks to their digital nature — they’re easy to copy and emulators have saved many titles that are otherwise locked in corporate vaults. But emulators give us something beyond simple preservation: they can also be used to enhance games well beyond the capabilities of the original systems while still preserving the souls of the games, as this NES emulator manages to do.
The emulator is called Anemoia-ESP32, and as its name suggests is a re-write of the Anemoia emulator specifically built for the ESP32. By modern standards these little chips don’t pack much of a punch, but compared to original NES hardware they’re more than up to the task of gaming. This project aims to recreate the Nintendo Entertainment System experience as faithfully as possible, hitting 60 FPS in most instances, as well as maintaining full audio emulation. Running on an ESP32 enables some truly small handheld options that would be difficult to achieve with more traditional platforms for emulation. There are some PCBs available here as well, but aren’t required to explore this project with.
As far as extra features compared to original NES hardware, the emulator does support save states and has a number of other settings improvements. Installation is as easy as flashing any other firmware image onto an ESP32, which these days can even be done from the browser. No word on whether or not it will eventually support emulating dual Picture Processing Units, but we can hope.
Google Photos caps your free storage at 15GB, and that isn't just your email—it is pooled between Drive, Gmail, Photos, and every other Google service. Given how many things it gets used for, that storage space disappears pretty quickly. If you need more storage, or if you use iCloud, you're basically forced to opt into a monthly subscription.
Muscle memory is hard to shake. If you've spent years in Photoshop, you're not going to have a good time switching to GIMP. It took me three tries to switch over, and even then, tools like PhotoGIMP were incredibly helpful. You're unlearning years of shortcuts and what feels ingrained, which is hard to commit to for a tool you've never used before. If you're on the fence about switching to an alternative, then this tool is exactly what you need.
The European Commission has fined Alibaba €550 million under the Digital Services Act, the largest penalty issued under the law so far.
The post EU Hits Alibaba With Record $629 Million Fine Over AliExpress Counterfeit Goods appeared first on TechRepublic.
Clarify, the Seattle-based AI startup that has raised more than $22 million to take on Salesforce and other CRM incumbents, has made its first acquisition: San Francisco-based Seam AI.
Seam’s technology monitors buying signals across the web — such as funding rounds, hiring, website activity, and executive job moves — and surfaces them to sales teams. Clarify plans to fold the technology into a new product called Clarify Signals, slated to launch later this year.
Clarify is led by co-founders Patrick Thompson (CEO) and Ondrej Hrebicek (CTO), who previously co-founded Iteratively, a Seattle data-analytics startup that was acquired in 2021 by Amplitude, the publicly traded digital-analytics company.
Rationale: Clarify says the deal is part of a shift beyond what it calls a “system of record” that tracks what already happened to a “system of awareness” that flags what’s about to happen.
Thompson said the Seam deal fills a gap in what Clarify’s own AI can pull from the open web, giving the CRM access to proprietary datasets that can’t be reached with a simple search.
“The value that Seam is providing is typically the information that’s not necessarily easy to get from the web,” Thompson explained in an interview. “It’s the harder stuff to find.”
Hrebicek said Clarify’s customers have been looking for a bigger and richer dataset — the ability to “look around the corners on who would be a good lead.”
Deal points: Financial terms weren’t disclosed. Clarify, which had raised a total of $22.5 million in its seed and Series A rounds from investors including U.S. Venture Partners, Gradient Ventures, and Madrona, said it brought in additional funding as part of the deal but did not disclose the amount.
As part of the acquisition, five Seam employees are joining Clarify, including Seam co-founder and CEO Nicholas Scavone. With the deal, Clarify is adding a San Francisco office alongside its Seattle headquarters. The company now has 30 people total.
Backstory: Scavone started Seam in 2020 after five years at Okta, where he saw teams accumulate many different sales and marketing systems, with customer data scattered across all of them.
Seam raised $7 million including angel funding and a seed round led by Bessemer Venture Partners in April 2024. It counts Zapier, GoFundMe, Drata, and Betterment among its customers. Existing customers are on hold while the technology is integrated into Clarify, but many have already indicated they plan to move over to the new platform.
Scavone said he had been weighing whether to raise a new round or find a home for the company when he and Thompson, who have known each other for years, began talking about a combination.
“We’re all going after the same big incumbents here,” he said, explaining that he ultimately decided Seam had a better chance of taking on the market’s dominant players by joining forces with Clarify than as a standalone company.
In a post announcing the deal, the Seam and Clarify founders said they “realized we weren’t building competing products—we were building different halves of the same future.”
Landscape: Clarify is entering a crowded field. Sales-intelligence platforms like Clay, ZoomInfo, and Apollo already sell third-party data to revenue teams, and 6sense and Demandbase lead the account-based marketing category Seam had been targeting.
Thompson said one edge for Clarify is that signals arrive inside the CRM sellers already use, not a separate dashboard.
The company was co-founded in early 2024 by Thompson, Hrebicek, and Austin Hay, a marketing-technology operator who served as co-CEO alongside Thompson. Hay departed in September 2025 and is now with Khosla Ventures, per his LinkedIn.
What’s next: Clarify plans to launch Signals later this year, Thompson said, noting that the company is considering raising additional funds in a Series B round early next year.
It seems as though $5.6 billion wasn't enough. That was the news from the US Space Force on Friday, when military officials announced they were tripling the maximum value of one of the service's National Security Space Launch contracts to $17 billion.
The expansion of the Space Force's National Security Space Launch (NSSL) Phase 3 contract comes as the Pentagon signals rising demand for military satellite launches. The NSSL program is set up to allow Space Systems Command, which oversees the Space Force's launch program, to select from a pool of launch providers for individual missions to deliver the military's satellites to orbit.
The NSSL program has two parts. Lane 1 covers the Space Force's more risk-tolerant missions, such as medium-lift launches with experimental payloads or rideshare missions carrying satellites for the Pentagon's surveillance or data relay constellations. Lane 2 includes higher-priority strategic missions, like the government's largest and most expensive spy satellites, or radiation-hardened communications satellites designed to survive a nuclear war.
© SpaceX
It seems as though $5.6 billion wasn't enough. That was the news from the US Space Force on Friday, when military officials announced they were tripling the maximum value of one of the service's National Security Space Launch contracts to $17 billion.
The expansion of the Space Force's National Security Space Launch (NSSL) Phase 3 contract comes as the Pentagon signals rising demand for military satellite launches. The NSSL program is set up to allow Space Systems Command, which oversees the Space Force's launch program, to select from a pool of launch providers for individual missions to deliver the military's satellites to orbit.
The NSSL program has two parts. Lane 1 covers the Space Force's more risk-tolerant missions, such as medium-lift launches with experimental payloads or rideshare missions carrying satellites for the Pentagon's surveillance or data relay constellations. Lane 2 includes higher-priority strategic missions, like the government's largest and most expensive spy satellites, or radiation-hardened communications satellites designed to survive a nuclear war.
© SpaceX
After using Jellyfin for a while, I've finally got it running how I want. But the process wasn't without a few issues, and the software comes with a steeper learning curve than Plex. Here are some of the things I wish I knew before I started using Jellyfin.
Since Linux is so widely used for servers, it has a lot of utlities for monitoring network information and accessing remote resources. There are some networking commands people still use because they know them, but some are outdated and deprecated. Here are some deprecated utilities along with what you should use instead.
Pop!_OS has a strong following, and one reason is its COSMIC desktop. Being unfamiliar with both, I decided to take a look at COSMIC and see what all the fuss was about. Could it make me give up my go-to Xfce?
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