Pramana and ARUP Laboratories Partner to Digitize Pathology Slides and Develop AI-Powered Hematopathology Algorithms for Deployment via Edge AI
Pramana, Inc., an AI-enabled health tech company modernizing the pathology sector, and ARUP Laboratories, the largest nonprofit clinical and academic reference laboratory in the United States, announced a collaboration to digitize pathology slides and develop AI-powered algorithms to improve the assessment of bone marrow biopsies and address other key diagnostic challenges in hematopathology. The partnership combines ARUP's hematopathology expertise with Pramana's cutting-edge SpectralHT autonomous whole-slide imaging scanners to advance diagnostic precision and efficiency.
This press release features multimedia. View the full release here:
'Hematopathology involves highly complex and difficult-to-scan specimens, where traditional methods often fall short in delivering consistent and reproducible results,' said David Ng, MD, medical director of Hematologic Flow Cytometry and Applied Artificial Intelligence at ARUP Laboratories. 'By combining our deep clinical expertise with Pramana's large-scale digitization and AI-driven analysis, we have the ability to develop and clinically validate new AI algorithms that will improve diagnostic accuracy and workflow efficiency. Additionally, this collaboration lays the foundation for the broad distribution of these AI tools, ensuring greater accessibility and impact across the pathology community.'
The AI model development process will be led by ARUP, drawing on its expert hematopathologists and annotation tools to train, refine, and validate the algorithms using real-world clinical cases and pathology slides obtained for this purpose. These algorithms will be designed and tested to run efficiently on Pramana's SpectralHT scanners, demonstrating the viability of in-line edge computing for real-time AI-powered diagnostics. ARUP and Pramana will explore commercialization strategies to enable the seamless deployment and distribution of advanced diagnostic algorithms per regulatory standards, which will run efficiently on scanners and drive broader industry adoption in clinical diagnostics.
'This collaboration with ARUP Laboratories showcases how AI-driven pathology can redefine industry standards, making diagnostics more scalable, efficient, and interoperable,' said Prasanth Perugupalli, chief product officer at Pramana. 'By leveraging edge computing, we're accelerating the adoption of advanced diagnostic algorithms, including those for complex hematopathology cases. This approach enhances precision, removes scalability barriers, and seamlessly integrates AI-driven insights into lab workflows.'
Pramana's SpectralHT scanners feature in-line Edge AI computing, allowing real-time quality control and automated image processing. This streamlined workflow reduces the burden on lab personnel while ensuring high-quality data output. The SpectralHT scanners' volumetric imaging capabilities improve image quality and detail while enhancing scanning efficiency, even for the most challenging diagnostic slides, such as microbiology, hematopathology, parasitology, and cytology.
The ongoing partnership between ARUP Laboratories and Pramana underscores a broader commitment to digitization and AI-driven pathology advancements, signaling the potential for deeper integration and expanded initiatives, including clinical applications.
About Pramana, Inc.
Pramana, Inc., an AI-powered health tech company modernizing the pathology sector, enables seamless digital adoption by pathology labs and medical centers. Built upon extensive industry experience and patented technological innovation, Pramana is a gateway for pathologists and physicians to utilize AI-enabled decision support. The company is headquartered in Cambridge, Mass., and backed by Matrix Capital, a global leader in customized investment solutions, and NTTVC, a leading firm backing diverse founders within the technology spectrum. For more information, visit www.pramana.ai.
About ARUP Laboratories
Founded in 1984, ARUP Laboratories is a leading national reference laboratory and a nonprofit enterprise of the University of Utah's Spencer Fox Eccles School of Medicine and its Department of Pathology. ARUP offers more than 3,000 tests and test combinations, ranging from routine screening tests to esoteric molecular and genetic assays. In addition, ARUP is a worldwide leader in innovative laboratory research and development, led by the efforts of the ARUP Institute for Research and Innovation in Diagnostic and Precision Medicine™. ARUP is ISO 15189 and CAP accredited. For more information, visit www.aruplab.com.
Pramana:
Andrea Sampson, Sampson PR Group
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Bonnie Stray
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PUB: 03/11/2025 08:10 AM/DISC: 03/11/2025 08:09 AM
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AI Deepfakes Are Stealing Millions Every Year — Who's Going to Stop Them?
This story appears in the July 2025 issue of Entrepreneur. Subscribe » Your CFO is on the video call asking you to transfer $25 million. He gives you all the bank info. Pretty routine. You got it. But, What the — ? It wasn't the CFO? How can that be? You saw him with your own eyes and heard that undeniable voice you always half-listen for. Even the other colleagues on the screen weren't really them. And yes, you already made the transaction. Ring a bell? That's because it actually happened to an employee at the global engineering firm Arup last year, which lost $25 million to criminals. In other incidents, folks were scammed when "Elon Musk" and "Goldman Sachs executives" took to social media enthusing about great investment opportunities. And an agency leader at WPP, the largest advertising company in the world at the time, was almost tricked into giving money during a Teams meeting with a deepfake they thought was the CEO Mark Read. Experts have been warning for years about deepfake AI technology evolving to a dangerous point, and now it's happening. Used maliciously, these clones are infesting the culture from Hollywood to the White House. And although most businesses keep mum about deepfake attacks to prevent client concern, insiders say they're occurring with increasing alarm. Deloitte predicts fraud losses from such incidents to hit $40 billion in the United States by 2027. Related: The Advancement Of Artificial Intelligence Is Inevitable. Here's How We Should Get Ready For It. Obviously, we have a problem — and entrepreneurs love nothing more than finding something to solve. But this is no ordinary problem. You can't sit and study it, because it moves as fast as you can, or even faster, always showing up in a new configuration in unexpected places. 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If anyone can lead the way, startups may have an advantage — because compared to big firms, they can focus exclusively on the problem and iterate faster, says Ankita Mittal, senior consultant of research at The Insight Partners, which has released a report on this new market and predicts explosive growth. Here's how a few of these founders are trying to stay ahead — and building an industry from the ground up to keep us all safe. Related: 'We Were Sucked In': How to Protect Yourself from Deepfake Phone Scams. Image Credit: Terovesalainen If deepfakes had an origin story, it might sound like this: Until the 1830s, information was physical. You could either tell someone something in person, or write it down on paper and send it, but that was it. Then the commercial telegraph arrived — and for the first time in human history, information could be zapped over long distances instantly. This revolutionized the world. 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Both Reality Defender and GetReal maintain pipelines coursing with tech that's deployed, in development, and ready to sunset. To do that, they're organized around different teams that go back and forth to continually test their models. Farid, for example, has a "red team" that attacks and a "blue team" that defends. Describing working with his head of research on a new product, he says, "We have this very rapid cycle where she breaks, I fix, she breaks — and then you see the fragility of the system. You do that not once, but you do it 20 times. And now you're onto something." Additionally, they layer in non-AI sleuthing techniques to make their tools more accurate and harder to dodge. GetReal, for example, uses AI to search images and videos for what are known as "artifacts" — telltale flaws that they're made by generative AI — as well as other digital forensic methods to analyze inconsistent lighting, image compression, whether speech is properly synched to someone's moving lips, and for the kind of details that are hard to fake (like, say, if video of a CEO contains the acoustic reverberations that are specific to his office). "The endgame of my world is not elimination of threats; it's mitigation of threats," Farid says. "I can defeat almost all of our systems. But it's not easy. The average knucklehead on the internet, they're going to have trouble removing an artifact even if I tell 'em it's there. A sophisticated actor, sure. They'll figure it out. But to remove all 20 of the artifacts? At least I'm gonna slow you down." Related: Deepfake Fraud Is Becoming a Business Risk You Can't Ignore. Here's the Surprising Solution That Puts You Ahead of Threats. 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For the fake data, he mostly generates it in house. He has also focused on developing partnerships with the companies whose tools are used to make deepfakes — because, of course, not all of them are meant to be harmful. So far, his partners include ElevenLabs (which, for example, translates popular podcaster and neuroscientist Andrew Huberman's voice into Hindi and Spanish, so that he can reach wider audiences) along with PlayAI and Respeecher. These companies have mountains of real-world data — and they like sharing it, because they look good by showing that they're building guardrails and allowing Reality Defender to detect their tools. In addition, this grants Reality Defender early access to the partners' new models, which gives it a jump start in updating its platform. Colman's team has also gotten creative. At one point, to gather fresh voice data, they partnered with a rideshare company — offering their drivers extra income by recording 60 seconds of audio when they weren't busy. "It didn't work," Colman admits. "A ridesharing car is not a good place to record crystal-clear audio. But it gave us an understanding of artificial sounds that don't indicate fraud. It also helped us develop some novel approaches to remove background noise, because one trick that a fraudster will do is use an AI-generated voice, but then try to create all kinds of noise, so that maybe it won't be as detectable." Startups like this must also grapple with another real-world problem: How do they keep their software from getting out into the public, where deepfakers can learn from it? To start, Reality Defender's clients have a high bar for whom within the organizations can access their software. But the company has also started to create some novel hardware. To show me, Colman holds up a laptop. "We're now able to run all of our magic locally, without any connection to the cloud on this," he says. The loaded laptop, only available to high-touch clients, "helps protect our IP, so people don't use it to try to prove they can bypass it." Related: Nearly Half of Americans Think They Could Be Duped By AI. Here's What They're Worried About. Some founders are taking a completely different path: Instead of trying to detect fake people, they're working to authenticate real ones. That's Joshua McKenty's plan. He's a serial entrepreneur who cofounded OpenStack and worked at NASA as Chief Cloud Architect, and this March launched a company called Polyguard. "We said, 'Look, we're not going to focus on detection, because it's only accelerating the arms race. We're going to focus on authenticity,'" he explains. "I can't say if something is fake, but I can tell you if it's real." To execute that, McKenty built a platform to conduct a literal reality check on the person you're talking to by phone or video. Here's how it works: A company can use Polyguard's mobile app, or integrate it into their own app and call center. When they want to create a secure call or meeting, they use that system. To join, participants must prove their identities via the app on their mobile phone (where they're verified using documents like Real ID, e-passports, and face scanning). Polyguard says this is ideal for remote interviews, board meetings, or any other sensitive communication where identity is critical. In some cases, McKenty's solution can be used with tools like Reality Defender. "Companies might say 'We're so big, we need both,'" he explains. His team is only five or six people at this point (whereas Reality Defender and GetReal both have about 50 employees), but he says his clients already include recruiters, who are interviewing candidates remotely only to discover that they're deepfakes, law firms wanting to protect attorney-client privilege, and wealth managers. He's also making the platform available to the public for people to establish secure lines with their attorney, accountant, or kid's teacher. This line of thinking is appealing — and gaining approval from people who watch the industry. "I like the authentication approach; it's much more straightforward," says The Alan Turing Institute's Swatton. "It's focused not on detecting something going wrong, but certifying that it's going right." After all, even when detection probabilities sound good, any margin of error can be scary: A detector that catches 95% of fakes will still allow for a scam 1 out of 20 times. That error rate is what alarmed Christian Perry, another entrepreneur who's entered the deepfake race. He saw it in the early detectors for text, where students and workers were being accused of using AI when they weren't. Authorship deceit doesn't pose the level of threat that deepfakes do, but text detectors are considered part of the scam-fighting family. Perry and his cofounder Devan Leos launched a startup called Undetectable in 2023, which now has over 19 million users and a team of 76. It began by building a sophisticated text detector, but then pivoted into image detection, and is now close to launching audio and video detectors as well. "You can use a lot of the same kind of methodology and skill sets that you pick up in text detection," says Perry. "But deepfake detection is a much more complicated problem." Related: Despite How the Media Portrays It, AI Is Not Really Intelligent. Here's Why. 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As the actors' and writers' strikes broke out, with AI being a central issue, Luke checked in with former colleagues at major talent agencies. He'd previously worked at Creative Artists Agency as a data scientist, and he was now wondering if his revenge-porn tool might be useful for their clients — though in a different way. It could also be used to identify celebrity deepfakes — to find, for example, when an actor or singer is being cloned to promote someone else's product. Along with feeling out other talent reps like William Morris Endeavor, he went to law and entertainment management firms. They were interested. So in 2023, Luke quit consulting to work with Rebekah and a third cofounder, Hirak Chhatbar, on building out their side hustle, Loti. "We saw the desire for a product that fit this little spot, and then we listened to key industry partners early on to build all of the features that people really wanted, like impersonation," Luke says. "Now it's one of our most preferred features. Even if they deliberately typo the celebrity's name or put a fake blue checkbox on the profile photo, we can detect all of those things." Using Loti is simple. A new client submits three real images and eight seconds of their voice; musicians also provide 15 seconds of singing a cappella. The Loti team puts that data into their system, and then scans the internet for that same face and voice. Some celebs, like Scarlett Johansson, Taylor Swift, and Brad Pitt, have been publicly targeted by deepfakes, and Loti is ready to handle that. But Luke says most of the need right now involves the low-tech stuff like impersonation and false endorsements. A recently-passed law called the Take It Down Act — which criminalizes the publication of nonconsensual intimate images (including deepfakes) and requires online platforms to remove them when reported — helps this process along: Now, it's much easier to get the unauthorized content off the web. Loti doesn't have to deal with probabilities. It doesn't have to constantly iterate or get huge datasets. It doesn't have to say "real" or "fake" (although it can). It just has to ask, "Is this you?" "The thesis was that the deepfake problem would be solved with deepfake detectors. And our thesis is that it will be solved with face recognition," says Luke, who now has a team of around 50 and a consumer product coming out. "It's this idea of, How do I show up on the internet? What things are said of me, or how am I being portrayed? I think that's its own business, and I'm really excited to be at it." Related: Why AI is Your New Best Friend... and Worst Enemy in the Battle Against Phishing Scams Will it all pay off? All tech aside, do these anti-deepfake solutions make for strong businesses? Many of the startups in this space are early-stage and venture-backed, so it's not yet clear how sustainable or profitable they can be. 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Many of the current anti-deepfake companies, she predicts, will get acquired by big tech and cybersecurity firms. Whether or not that's Reality Defender's future, Colman believes that platforms like his will become integral to a larger guardrail ecosystem. He compares it to antivirus software: Decades ago, you had to buy an antivirus program and manually scan your files. Now, these scans are just built into your email platforms, running automatically. "We're following the exact same growth story," he says. "The only problem is the problem is moving even quicker." No doubt, the need will become glaring at some point soon. Farid at GetReal imagines a nightmare like someone creating a fake earnings call for a Fortune 500 company that goes viral. If GetReal's CEO, Matthew Moynahan, is right, then 2026 will be the year that gets the flywheel spinning for all these deepfake-fighting businesses. "There's two things that drive sales in a really aggressive way: a clear and present danger, and compliance and regulation," he says. "The market doesn't have either right now. Everybody's interested, but not everybody's troubled." That will likely change with increased regulations that push adoption, and with deepfakes popping up in places they shouldn't be. "Executives will connect the dots," Moynahan predicts. "And they'll start saying, 'This isn't funny anymore.'" Related: AI Cloning Hoax Can Copy Your Voice in 3 Seconds—and It's Emptying Bank Accounts. Here's How to Protect Yourself.
Yahoo
16-07-2025
- Yahoo
How Generative AI's 'Deepfake Economy' Is Hobbling Small Businesses
Over the past few years, the potential uses of generative AI, both positive and negative, have been talked to death. However, there's one application of the technology that small business owners are saying is often overlooked: the deepfake economy. Several small business owners told Business Insider that since ChatCPT's debut three years ago, the deepfake economy has blown up. Now, scammers are using these deepfakes to pose as employees of a company, running cons that are wreaking havoc on the brands' reputations and bottom lines. Don't Miss: Named a TIME Best Invention and Backed by 5,000+ Users, Kara's Air-to-Water Pod Cuts Plastic and Costs — $100k+ in investable assets? – no cost, no obligation. An unnamed finance clerk at engineering firm Arup told the outlet about a time he joined a video call with his AI versions of colleagues. One of these "colleagues," supposedly the company's chief financial officer, asked him to approve a series of overseas transfers worth more than $25 million. Believing that the request came from his boss, the finance clerk approved the transactions. Only after the money had been sent did he learn that the colleagues were actually deepfake recreations of his real coworkers. The finance clerk isn't the only one being deceived by these impressionists. According to data from Chinabuse, TRM Labs' open-source fraud reporting platform, generative AI-enabled scams rose by 456% between May 2024 and April, when compared with the same period the year before. Another survey from Nationwide Insurance released in September found that 12% of small business owners had faced at least one deepfake scam within the previous year. Small businesses, the survey said, are more likely to fall victim to these types of scams because they lack the cybersecurity infrastructure of larger companies. Trending: This AI-Powered Trading Platform Has 5,000+ Users, 27 Pending Patents, and a $43.97M Valuation — Rob Duncan, vice president of strategy at Netcraft, told Business Insider that he isn't surprised at the increase in highly personalized attacks against small businesses. Generative AI has made it much easier for inexperienced scammers to pose as brands and launch these scams. As AI continues to improve, "attackers can more easily spoof employees, fool customers, or impersonate partners across multiple channels," he said. Many of the platforms used by small businesses, like Teams and Zoom, are getting better at detecting AI and weeding out accounts that don't have real people behind them. However, many experts worry that improved detection tools are making the AI problem worse. Beyond Identity CEO Jasson Casey told Business Insider that the data collected by platforms like Zoom and Teams is not only used to suss out deepfakes but to train sophisticated AI models. This creates a vicious cycle that becomes "an arms race defenders cannot win.'Casey and Robin Pugh, the executive director of non-profit Intelligence for Good, say that small businesses can best protect themselves from deepfake scams by focusing on confirming identities rather than disproving AI use. They also warn that these generative AI-based scams will not be going away anytime soon. Nina Etemadi, cofounder of a Philadelphia-based small business named Cake Life Bake Shop, agrees, telling Business Insider, 'Doing business online gets more necessary and high risk every year. AI is just part of that." Read Next: Many are using retirement income calculators to check if they're on pace — Image: Shutterstock UNLOCKED: 5 NEW TRADES EVERY WEEK. Click now to get top trade ideas daily, plus unlimited access to cutting-edge tools and strategies to gain an edge in the markets. Get the latest stock analysis from Benzinga? APPLE (AAPL): Free Stock Analysis Report TESLA (TSLA): Free Stock Analysis Report This article How Generative AI's 'Deepfake Economy' Is Hobbling Small Businesses originally appeared on © 2025 Benzinga does not provide investment advice. All rights reserved.
