Anthropic says that it has released a new set of AI models tailored for U.S. national security customers. The new models, a custom set of “Claude Gov” models, were “built based on direct feedback from our government customers to add

While Mark Zuckerberg was hyping Meta’s latest Ray-Ban smartglasses and Apple was promoting its Vision Pro mixed reality headset in 2023, Finnish startup IXI was quietly crafting high-tech specs for more practical purposes.  Founded in 2021, the comp

Bridging the Tech Skills Gap with Real-World Innovation in AI and Cybersecurity  Deccan Chronicle

Every few weeks, it seems like there’s a new headline about a lawyer getting in trouble for submitting filings containing, in the words of one judge, “bogus AI-generated research.” The details vary, but the throughline is the same: an attorney turns to a large language model (LLM) like ChatGPT to help them with legal research (or worse, writing), the LLM hallucinates cases that don’t exist, and the lawyer is none the wiser until the judge or opposing counsel points out their mistake. In some cases, including an aviation lawsuit from 2023, attorneys have had to pay fines for submitting filings with AI-generated hallucinations. So why haven’t they stopped?The answer mostly comes down to time crunches, and the way AI has crept into nearly every profession. Legal research databases like LexisNexis and Westlaw have AI integrations now. For lawyers juggling big caseloads, AI can seem like an incredibly efficient assistant. Most lawyers aren’t necessarily using ChatGPT to write their filings, but they are increasingly using it and other LLMs for research. Yet many of these lawyers, like much of the public, don’t understand exactly what LLMs are or how they work. One attorney who was sanctioned in 2023 said he thought ChatGPT was a “super search engine.” It took submitting a filing with fake citations to reveal that it’s more like a random-phrase generator — one that could give you either correct information or convincingly phrased nonsense.Andrew Perlman, the dean of Suffolk University Law School, argues many lawyers are using AI tools without incident, and the ones who get caught with fake citations are outliers. “I think that what we’re seeing now — although these problems of hallucination are real, and lawyers have to take it very seriously and be careful about it — doesn’t mean that these tools don’t have enormous possible benefits and use cases for the delivery of legal services,” Perlman said. Legal databases and research systems like Westlaw are incorporating AI services.In fact, 63 percent of lawyers surveyed by Thomson Reuters in 2024 said they’ve used AI in the past, and 12 percent said they use it regularly. Respondents said they use AI to write summaries of case law and to research “case law, statutes, forms or sample language for orders.” The attorneys surveyed by Thomson Reuters see it as a time-saving tool, and half of those surveyed said “exploring the potential for implementing AI” at work is their highest priority. “The role of a good lawyer is as a ‘trusted advisor’ not as a producer of documents,” one respondent said. But as plenty of recent examples have shown, the documents produced by AI aren’t always accurate, and in some cases aren’t real at all.RelatedIn one recent high-profile case, lawyers for journalist Tim Burke, who was arrested for publishing unaired Fox News footage in 2024, submitted a motion to dismiss the case against him on First Amendment grounds. After discovering that the filing included “significant misrepresentations and misquotations of supposedly pertinent case law and history,” Judge Kathryn Kimball Mizelle, of Florida’s middle district, ordered the motion to be stricken from the case record. Mizelle found nine hallucinations in the document, according to the Tampa Bay Times.Mizelle ultimately let Burke’s lawyers, Mark Rasch and Michael Maddux, submit a new motion. In a separate filing explaining the mistakes, Rasch wrote that he “assumes sole and exclusive responsibility for these errors.” Rasch said he used the “deep research” feature on ChatGPT pro, which The Verge has previously tested with mixed results, as well as Westlaw’s AI feature.Rasch isn’t alone. Lawyers representing Anthropic recently admitted to using the company’s Claude AI to help write an expert witness declaration submitted as part of the copyright infringement lawsuit brought against Anthropic by music publishers. That filing included a citation with an “inaccurate title and inaccurate authors.” Last December, misinformation expert Jeff Hancock admitted he used ChatGPT to help organize citations in a declaration he submitted in support of a Minnesota law regulating deepfake use. Hancock’s filing included “two citation errors, popularly referred to as ‘hallucinations,’” and incorrectly listed authors for another citation. These documents do, in fact, matter — at least in the eyes of judges. In a recent case, a California judge presiding over a case against State Farm was initially swayed by arguments in a brief, only to find that the case law cited was completely made up. “I read their brief, was persuaded (or at least intrigued) by the authorities that they cited, and looked up the decisions to learn more about them – only to find that they didn’t exist,” Judge Michael Wilner wrote.Perlman said there are several less risky ways lawyers use generative AI in their work, including finding information in large tranches of discovery documents, reviewing briefs or filings, and brainstorming possible arguments or possible opposing views. “I think in almost every task, there are ways in which generative AI can be useful — not a substitute for lawyers’ judgment, not a substitute for the expertise that lawyers bring to the table, but in order to supplement what lawyers do and enable them to do their work better, faster, and cheaper,” Perlman said.But like anyone using AI tools, lawyers who rely on them to help with legal research and writing need to be careful to check the work they produce, Perlman said. Part of the problem is that attorneys often find themselves short on time — an issue he says existed before LLMs came into the picture. “Even before the emergence of generative AI, lawyers would file documents with citations that didn’t really address the issue that they claimed to be addressing,” Perlman said. “It was just a different kind of problem. Sometimes when lawyers are rushed, they insert citations, they don’t properly check them; they don’t really see if the case has been overturned or overruled.” (That said, the cases do at least typically exist.)Another, more insidious problem is the fact that attorneys — like others who use LLMs to help with research and writing — are too trusting of what AI produces. “I think many people are lulled into a sense of comfort with the output, because it appears at first glance to be so well crafted,” Perlman said.Alexander Kolodin, an election lawyer and Republican state representative in Arizona, said he treats ChatGPT as a junior-level associate. He’s also used ChatGPT to help write legislation. In 2024, he included AI text in part of a bill on deepfakes, having the LLM provide the “baseline definition” of what deepfakes are and then “I, the human, added in the protections for human rights, things like that it excludes comedy, satire, criticism, artistic expression, that kind of stuff,” Kolodin told The Guardian at the time. Kolodin said he “may have” discussed his use of ChatGPT with the bill’s main Democratic cosponsor but otherwise wanted it to be “an Easter egg” in the bill. The bill passed into law. Kolodin — who was sanctioned by the Arizona State Bar in 2020 for his involvement in lawsuits challenging the result of the 2020 election — has also used ChatGPT to write first drafts of amendments, and told The Verge he uses it for legal research as well. To avoid the hallucination problem, he said, he just checks the citations to make sure they’re real.“You don’t just typically send out a junior associate’s work product without checking the citations,” said Kolodin. “It’s not just machines that hallucinate; a junior associate could read the case wrong, it doesn’t really stand for the proposition cited anyway, whatever. You still have to cite-check it, but you have to do that with an associate anyway, unless they were pretty experienced.”Kolodin said he uses both ChatGPT’s pro “deep research” tool and the LexisNexis AI tool. Like Westlaw, LexisNexis is a legal research tool primarily used by attorneys. Kolodin said that in his experience, it has a higher hallucination rate than ChatGPT, which he says has “gone down substantially over the past year.” AI use among lawyers has become so prevalent that in 2024, the American Bar Association issued its first guidance on attorneys’ use of LLMs and other AI tools. Lawyers who use AI tools “have a duty of competence, including maintaining relevant technological competence, which requires an understanding of the evolving nature” of generative AI, the opinion reads. The guidance advises lawyers to “acquire a general understanding of the benefits and risks of the GAI tools” they use — or, in other words, to not assume that an LLM is a “super search engine.” Attorneys should also weigh the confidentiality risks of inputting information relating to their cases into LLMs and consider whether to tell their clients about their use of LLMs and other AI tools, it states.Perlman is bullish on lawyers’ use of AI. “I do think that generative AI is going to be the most impactful technology the legal profession has ever seen and that lawyers will be expected to use these tools in the future,” he said. “I think that at some point, we will stop worrying about the competence of lawyers who use these tools and start worrying about the competence of lawyers who don’t.”Others, including one of the judges who sanctioned lawyers for submitting a filing full of AI-generated hallucinations, are more skeptical. “Even with recent advances,” Wilner wrote, “no reasonably competent attorney should out-source research and writing to this technology — particularly without any attempt to verify the accuracy of that material.”See More:

Drones Set To Deliver Benefits for Labor-Intensive Industries: Forrester By John P. Mello Jr. June 3, 2025 5:00 AM PT ADVERTISEMENT Quality Leads That Turn Into Deals Full-service marketing programs from TechNewsWorld deliver sales-ready leads. Segment by geography, industry, company size, job title, and more. Get Started Now. Aerial drones are rapidly assuming a key role in the physical automation of business operations, according to a new report by Forrester Research. Aerial drones power airborne physical automation by addressing operational challenges in labor-intensive industries, delivering efficiency, intelligence, and experience, explained the report written by Principal Analyst Charlie Dai with Frederic Giron, Merritt Maxim, Arjun Kalra, and Bill Nagel. Some industries, like the public sector, are already reaping benefits, it continued. The report predicted that drones will deliver benefits within the next two years as technologies and regulations mature. It noted that drones can help organizations grapple with operational challenges that exacerbate risks and inefficiencies, such as overreliance on outdated, manual processes, fragmented data collection, geographic barriers, and insufficient infrastructure. Overreliance on outdated manual processes worsens inefficiencies in resource allocation and amplifies safety risks in dangerous work environments, increasing operational costs and liability, the report maintained. “Drones can do things more safely, at least from the standpoint of human risk, than humans,” said Rob Enderle, president and principal analyst at the Enderle Group, an advisory services firm, in Bend, Ore. “They can enter dangerous, exposed, very high-risk and even toxic environments without putting their operators at risk,” he told TechNewsWorld. “They can be made very small to go into areas where people can’t physically go. And a single operator can operate several AI-driven drones operating autonomously, keeping staffing levels down.” Sensor Magic “The magic of the drone is really in the sensor, while the drone itself is just the vehicle that holds the sensor wherever it needs to be,” explained DaCoda Bartels, senior vice president of operations with FlyGuys, a drone services provider, in Lafayette, La. “In doing so, it removes all human risk exposure because the pilot is somewhere safe on the ground, sending this sensor, which is, in most cases, more high-resolution than even a human eye,” he told TechNewsWorld. “In essence, it’s a better data collection tool than if you used 100 people. Instead, you deploy one drone around in all these different areas, which is safer, faster, and higher resolution.” Akash Kadam, a mechanical engineer with Caterpillar, maker of construction and mining equipment, based in Decatur, Ill., explained that drones have evolved into highly functional tools that directly respond to key inefficiencies and threats to labor-intensive industries. “Within the manufacturing and supply chains, drones are central to optimizing resource allocation and reducing the exposure of humans to high-risk duties,” he told TechNewsWorld. “Drones can be used in factory environments to automatically inspect overhead cranes, rooftops, and tight spaces — spaces previously requiring scaffolding or shutdowns, which carry both safety and cost risks,” he said. “A reduction in downtime, along with no requirement for manual intervention in hazardous areas, is provided through this aerial inspection by drones.” “In terms of resource usage, drones mounted with thermal cameras and tools for acquiring real-time data can spot bottlenecks, equipment failure, or energy leakage on the production floor,” he continued. “This can facilitate predictive maintenance processes and [optimal] usage of energy, which are an integral part of lean manufacturing principles.” Kadam added that drones provide accurate field mapping and multispectral imaging in agriculture, enabling the monitoring of crop health, soil quality, and irrigation distribution. “Besides the reduction in manual scouting, it ensures more effective input management, which leads to more yield while saving resources,” he observed. Better Data Collection The Forrester report also noted that drones can address problems with fragmented data collection and outdated monitoring systems. “Drones use cameras and sensors to get clear, up-to-date info,” said Daniel Kagan, quality manager at Rogers-O’Brien Construction, a general contractor in Dallas. “Some drones even make 3D maps or heat maps,” he told TechNewsWorld. “This helps farmers see where crops need more water, stores check roof damage after a storm, and builders track progress and find delays.” “The drone collects all this data in one flight, and it’s ready to view in minutes and not days,” he added. Dean Bezlov, global head of business development at MYX Robotics, a visualization technology company headquartered in Sofia, Bulgaria, added that drones are the most cost and time-efficient way to collect large amounts of visual data. “We are talking about two to three images per second with precision and speed unmatched by human-held cameras,” he told TechNewsWorld. “As such, drones are an excellent tool for ‘digital twins’ — timestamps of the real world with high accuracy which is useful in industries with physical assets such as roads, rail, oil and gas, telecom, renewables and agriculture, where the drone provides a far superior way of looking at the assets as a whole,” he said. Drone Adoption Faces Regulatory Hurdles While drones have great potential for many organizations, they will need to overcome some challenges and barriers. For example, Forrester pointed out that insurers deploy drones to evaluate asset risks but face evolving privacy regulations and gaps in data standardization. Media firms use drones to take cost-effective, cinematic aerial footage, but face strict regulations, it added, while in urban use cases like drone taxis and cargo transport remain experimental due to certification delays and airspace management complexities. “Regulatory frameworks, particularly in the U.S., remain complex, bureaucratic, and fragmented,” said Mark N. Vena, president and principal analyst with SmartTech Research in Las Vegas. “The FAA’s rules around drone operations — especially for flying beyond visual line of sight [BVLOS] — are evolving but still limit many high-value use cases.” “Privacy concerns also persist, especially in urban areas and sectors handling sensitive data,” he told TechNewsWorld. “For almost 20 years, we’ve been able to fly drones from a shipping container in one country, in a whole other country, halfway across the world,” said FlyGuys’ Bartels. “What’s limiting the technology from being adopted on a large scale is regulatory hurdles over everything.” Enderle added that innovation could also be a hangup for organizations. “This technology is advancing very quickly, making buying something that isn’t instantly obsolete very difficult,” he said. “In addition, there are a lot of drone choices, raising the risk you’ll pick one that isn’t ideal for your use case.” “We are still at the beginning of this trend,” he noted. “Robotic autonomous drones are starting to come to market, which will reduce dramatically the need for drone pilots. I expect that within 10 years, we’ll have drones doing many, if not most, of the dangerous jobs currently being done by humans, as robotics, in general, will displace much of the labor force.” John P. Mello Jr. has been an ECT News Network reporter since 2003. His areas of focus include cybersecurity, IT issues, privacy, e-commerce, social media, artificial intelligence, big data and consumer electronics. He has written and edited for numerous publications, including the Boston Business Journal, the Boston Phoenix, Megapixel.Net and Government Security News. Email John. Leave a Comment Click here to cancel reply. Please sign in to post or reply to a comment. New users create a free account. Related Stories More by John P. Mello Jr. view all More in Emerging Tech

Tech AI robots help nurses beat burnout and transform hospital care Hospitals using AI-powered robots to support nurses, redefine patient care Published June 4, 2025 6:00am EDT close AI robots help nurses beat burnout and transform hospital care Artificial intelligence and robotics may help with nursing shortage. NEWYou can now listen to Fox News articles! The global healthcare system is expected to face a shortage of 4.5 million nurses by 2030, with burnout identified as a leading cause for this deficit. In response, Taiwan's hospitals are taking decisive action by integrating artificial intelligence and robotics to support their staff and maintain high standards of patient care. AI-powered Nurabot (Nvidia)Nurabot: The AI nursing robot changing patient careNurabot, a collaborative nursing robot developed by Foxconn and Kawasaki Heavy Industries with Nvidia's AI technology, is designed to take on some of the most physically demanding and repetitive tasks in clinical care. These include delivering medications, transporting samples, patrolling wards and guiding visitors through hospital corridors. By handling these responsibilities, Nurabot allows nurses to focus on more meaningful aspects of patient care and helps reduce the physical fatigue that often leads to burnout. AI-powered Nurabot (Nvidia)Using AI to build the hospitals of the futureFoxconn's approach to smart hospitals goes beyond deploying robots. The company has developed a suite of digital tools using Nvidia platforms, including AI models that monitor patient vitals and digital twins that simulate hospital environments for planning and training purposes.The process starts in the data center, where large AI models are trained on Nvidia supercomputers. Hospitals then use digital twins to test and train robots in virtual settings before deploying them in real-world scenarios, ensuring that these systems are both safe and effective.ARTIFICIAL INTELLIGENCE TRANSFORMS PATIENT CARE AND REDUCES BURNOUT, PHYSICIAN SAYS AI-powered Nurabot (Nvidia)AI robots in real hospitals: Results from Taiwan's Healthcare SystemTaichung Veterans General Hospital (TCVGH), along with other top hospitals in Taiwan, is at the forefront of this digital transformation. TCVGH has built digital twins of its wards and nursing stations, providing a virtual training ground for Nurabot before it is introduced to real hospital floors. According to Shu-Fang Liu, deputy director of the nursing department at TCVGH, robots like Nurabot are augmenting the capabilities of healthcare staff, enabling them to deliver more focused and meaningful care to patients. AI-powered Nurabot (Nvidia)Ways Nurabot reduces nurse burnout and boosts efficiencyNurabot is already making a difference in daily hospital operations. The robot handles medicine deliveries, ward patrols and visitor guidance, which Foxconn estimates can reduce nurse workloads by up to 30%. In one ward, Nurabot delivers wound care kits and educational materials directly to patient bedsides, saving nurses multiple trips to supply rooms and allowing them to dedicate more time to their patients. The robot is also especially helpful during visiting hours and night shifts, when staffing levels are typically lower.Nurses hope future versions of Nurabot will be able to converse with patients in multiple languages, recognize faces for personalized interactions and even assist with lifting patients when needed. For example, a lung patient who needs two nurses to sit up for breathing exercises might only require one nurse with Nurabot's help, freeing the other to care for other patients. AI-powered Nurabot (Nvidia)Kurt's key takeawaysWhen it comes to addressing the nursing shortage, Taiwan is demonstrating that AI and robotics can make a significant difference in hospitals. Instead of spending their shifts running errands or handling repetitive tasks, nurses now have robots like Nurabot to lend a hand. This means nurses can focus their energy on what matters most – caring for patients – while robots handle tasks such as delivering medication or guiding visitors around the hospital.It's a team effort between people and technology, and it's already helping healthcare staff provide better care for everyone.CLICK HERE TO GET THE FOX NEWS APPHow would you feel if a robot, not a human, delivered your medication during a hospital stay? Let us know by writing us at Cyberguy.com/Contact.For more of my tech tips and security alerts, subscribe to my free CyberGuy Report Newsletter by heading to Cyberguy.com/Newsletter.Ask Kurt a question or let us know what stories you'd like us to cover.Follow Kurt on his social channels:Answers to the most-asked CyberGuy questions:New from Kurt:Copyright 2025 CyberGuy.com. All rights reserved. Kurt "CyberGuy" Knutsson is an award-winning tech journalist who has a deep love of technology, gear and gadgets that make life better with his contributions for Fox News & FOX Business beginning mornings on "FOX & Friends." Got a tech question? Get Kurt’s free CyberGuy Newsletter, share your voice, a story idea or comment at CyberGuy.com.

IT Pros ‘Extremely Worried’ About Shadow AI: Report By John P. Mello Jr. June 4, 2025 5:00 AM PT ADVERTISEMENT Enterprise IT Lead Generation Services Fuel Your Pipeline. Close More Deals. Our full-service marketing programs deliver sales-ready leads. 100% Satisfaction Guarantee! Learn more. Shadow AI — the use of AI tools under the radar of IT departments — has information technology directors and executives worried, according to a report released Tuesday. The report, based on a survey of 200 IT directors and executives at U.S. enterprise organizations of 1,000 employees or more, found nearly half the IT pros (46%) were “extremely worried” about shadow AI, and almost all of them (90%) were concerned about it from a privacy and security viewpoint. “As our survey found, shadow AI is resulting in palpable, concerning outcomes, with nearly 80% of IT leaders saying it has resulted in negative incidents such as sensitive data leakage to Gen AI tools, false or inaccurate results, and legal risks of using copyrighted information,” said Krishna Subramanian, co-founder of Campbell, Calif.-based Komprise, the unstructured data management company that produced the report. “Alarmingly, 13% say that shadow AI has caused financial or reputational harm to their organizations,” she told TechNewsWorld. Subramanian added that shadow AI poses a much greater problem than shadow IT, which primarily focuses on departmental power users purchasing cloud instances or SaaS tools without obtaining IT approval. “Now we’ve got an unlimited number of employees using tools like ChatGPT or Claude AI to get work done, but not understanding the potential risk they are putting their organizations at by inadvertently submitting company secrets or customer data into the chat prompt,” she explained. “The data risk is large and growing in still unforeseen ways because of the pace of AI development and adoption and the fact that there is a lot we don’t know about how AI works,” she continued. “It is becoming more humanistic all the time and capable of making decisions independently.” Shadow AI Introduces Security Blind Spots Shadow AI is the next step after shadow IT and is a growing risk, noted James McQuiggan, security awareness advocate at KnowBe4, a security awareness training provider in Clearwater, Fla. “Users use AI tools for content, images, or applications and to process sensitive data or company information without proper security checks,” he told TechNewsWorld. “Most organizations will have privacy, compliance, and data protection policies, and shadow AI introduces blind spots in the organization’s data loss prevention.” “The biggest risk with shadow AI is that the AI application has not passed through a security analysis as approved AI tools may have been,” explained Melissa Ruzzi, director of AI at AppOmni, a SaaS security management software company, in San Mateo, Calif. “Some AI applications may be training models using your data, may not adhere to relevant regulations that your company is required to follow, and may not even have the data storage security level you deem necessary to keep your data from being exposed,” she told TechNewsWorld. “Those risks are blind spots of potential security vulnerabilities in shadow AI.” Krishna Vishnubhotla, vice president of product strategy at Zimperium, a mobile security company based in Dallas, noted that shadow AI extends beyond unapproved applications and involves embedded AI components that can process and disseminate sensitive data in unpredictable ways. “Unlike traditional shadow IT, which may be limited to unauthorized software or hardware, shadow AI can run on employee mobile devices outside the organization’s perimeter and control,” he told TechNewsWorld. “This creates new security and compliance risks that are harder to track and mitigate.” Vishnubhotla added that the financial impact of shadow AI varies, but unauthorized AI tools can lead to significant regulatory fines, data breaches, and loss of intellectual property. “Depending on the scale of the agency and the sensitivity of the data exposed, the costs could range from millions to potentially billions in damages due to compliance violations, remediation efforts, and reputational harm,” he said. “Federal agencies handling vast amounts of sensitive or classified information, financial institutions, and health care organizations are particularly vulnerable,” he said. “These sectors collect and analyze vast amounts of high-value data, making AI tools attractive. But without proper vetting, these tools could be easily exploited.” Shadow AI Everywhere and Easy To Use Nicole Carignan, SVP for security and AI strategy at Darktrace, a global cybersecurity AI company, predicts an explosion of tools that utilize AI and generative AI within enterprises and on devices used by employees. “In addition to managing AI tools that are built in-house, security teams will see a surge in the volume of existing tools that have new AI features and capabilities embedded, as well as a rise in shadow AI,” she told TechNewsWorld. “If the surge remains unchecked, this raises serious questions and concerns about data loss prevention, as well as compliance concerns as new regulations start to take effect.” “That will drive an increasing need for AI asset discovery — the ability for companies to identify and track the use of AI systems throughout the enterprise,” she said. “It is imperative that CIOs and CISOs dig deep into new AI security solutions, asking comprehensive questions about data access and visibility.” Shadow AI has become so rampant because it is everywhere and easy to access through free tools, maintained Komprise’s Subramanian. “All you need is a web browser,” she said. “Enterprise users can inadvertently share company code snippets or corporate data when using these Gen AI tools, which could create data leakage.” “These tools are growing and changing exponentially,” she continued. “It’s really hard to keep up. As the IT leader, how do you track this and determine the risk? Managers might be looking the other way because their teams are getting more done. You may need fewer contractors and full-time employees. But I think the risk of the tools is not well understood.” “The low, or in some cases non-existent, learning curve associated with using Gen AI services has led to rapid adoption, regardless of prior experience with these services,” added Satyam Sinha, CEO and co-founder of Acuvity, a provider of runtime Gen AI security and governance solutions, in Sunnyvale, Calif. “Whereas shadow IT focused on addressing a specific challenge for particular employees or departments, shadow AI addresses multiple challenges for multiple employees and departments. Hence, the greater appeal,” he said. “The abundance and rapid development of Gen AI services also means employees can find the right solution [instantly]. Of course, all these traits have direct security implications.” Banning AI Tools Backfires To support innovation while minimizing the threat of shadow AI, enterprises must take a three-pronged approach, asserted Kris Bondi, CEO and co-founder of Mimoto, a threat detection and response company in San Francisco. They must educate employees on the dangers of unsupported, unmonitored AI tools, create company protocols for what is not acceptable use of unauthorized AI tools, and, most importantly, provide AI tools that are sanctioned. “Explaining why one tool is sanctioned and another isn’t greatly increases compliance,” she told TechNewsWorld. “It does not work for a company to have a zero-use mandate. In fact, this results in an increase in stealth use of shadow AI.” In the very near future, more and more applications will be leveraging AI in different forms, so the reality of shadow AI will be present more than ever, added AppOmni’s Ruzzi. “The best strategy here is employee training and AI usage monitoring,” she said. “It will become crucial to have in place a powerful SaaS security tool that can go beyond detecting direct AI usage of chatbots to detect AI usage connected to other applications,” she continued, “allowing for early discovery, proper risk assessment, and containment to minimize possible negative consequences.” “Shadow AI is just the beginning,” KnowBe4’s McQuiggan added. “As more teams use AI, the risks grow.” He recommended that companies start small, identify what’s being used, and build from there. They should also get legal, HR, and compliance involved. “Make AI governance part of your broader security program,” he said. “The sooner you start, the better you can manage what comes next.” John P. Mello Jr. has been an ECT News Network reporter since 2003. His areas of focus include cybersecurity, IT issues, privacy, e-commerce, social media, artificial intelligence, big data and consumer electronics. He has written and edited for numerous publications, including the Boston Business Journal, the Boston Phoenix, Megapixel.Net and Government Security News. Email John. Leave a Comment Click here to cancel reply. Please sign in to post or reply to a comment. New users create a free account. Related Stories More by John P. Mello Jr. view all More in IT Leadership

SSTL Relaunches as SST Think Tank to Become Asia’s First Global Space Think Tank  SpaceWatch.GLOBAL

Scaling distributed SQL queries needs more performance and efficiency in the agentic AI era. It’s a challenge Cockroach is looking to solve.

IBM and Roche are teaming up on an AI solution to a challenge faced by millions worldwide: the relentless daily grind of diabetes management. Their new brainchild, the Accu-Chek SmartGuide Predict app, provides AI-powered glucose forecasting capabilities to users. The app doesn’t just track where your glucose levels are—it tells you where they’re heading. Imagine having a weather forecast, but for your blood sugar. That’s essentially what IBM and Roche are creating.AI-powered diabetes managementThe app works alongside Roche’s continuous glucose monitoring sensor, crunching the numbers in real-time to offer predictive insights that can help users stay ahead of potentially dangerous blood sugar swings.What caught my eye were the three standout features that address very specific worries diabetics face. The “Glucose Predict” function visualises where your glucose might be heading over the next two hours—giving you that crucial window to make adjustments before things go south.For those who live with the anxiety of hypoglycaemia (when blood sugar plummets to dangerous levels), the “Low Glucose Predict” feature acts like an early warning system, flagging potential lows up to half an hour before they might occur. That’s enough time to take corrective action.Perhaps most reassuring is the “Night Low Predict” feature, which estimates your risk of overnight hypoglycaemia—often the most frightening prospect for diabetes patients. Before tucking in for the night, the AI-powered diabetes management app gives you a heads-up about whether you might need that bedtime snack. This feature should bring peace of mind to countless households.“By harnessing the power of AI-enabled predictive technology, Roche’s Accu-Chek SmartGuide Predict App can help empower people with diabetes to take proactive measures to manage their disease,” says Moritz Hartmann, Head of Roche Information Solutions.How AI is speeding up diabetes researchIt’s not just patients benefiting from this partnership. The companies have developed a rather clever research tool using IBM’s watsonx AI platform that’s transforming how clinical study data gets analysed.Anyone who’s been involved in clinical research knows the mind-numbing tedium of manual data analysis. IBM and Roche’s tool does the heavy lifting—digitising, translating, and categorising all that anonymised clinical data, then connecting the dots between glucose monitoring data and participants’ daily activities.The result? Researchers can spot meaningful patterns and correlations in a fraction of the time it would normally take. This behind-the-scenes innovation might do more to advance diabetes care and management in the long run than the app itself.What makes this collaboration particularly interesting is how it brings together two different worlds. You’ve got IBM’s computing prowess and AI know-how pairing up with Roche’s decades of healthcare and diabetes expertise.”Our long-standing partnership with IBM underscores the potential of cross-industry innovation in addressing unmet healthcare needs and bringing significant advancements to patients faster,” says Hartmann.“Using cutting-edge technology such as AI and machine learning helps us to accelerate time to market and to improve therapy outcomes at the same time.”Christian Keller, General Manager of IBM Switzerland, added: “The collaboration with Roche underlines the potential of AI when it’s implemented with a clear goal—assisting patients in managing their diabetes.“With our technology and consulting expertise we can offer a trusted, customised, and secure technical environment that is essential to enable innovation in healthcare.”What this means for the future of healthcare techHaving covered healthcare tech for years, I’ve seen plenty of promising innovations fizzle out. However, this IBM-Roche partnership feels promising—perhaps because it’s addressing such a specific, well-defined problem with a thoughtful, targeted application of AI.For the estimated 590 million people (or 1 in 9 of the adult population) worldwide living with diabetes, the shift from reactive to predictive management could be gamechanging. It’s not about replacing human judgment, but enhancing it with timely, actionable insights.The app’s currently only available in Switzerland, which seems a sensible approach—test, refine, and perfect before wider deployment. Healthcare professionals will be keeping tabs on this Swiss rollout to see if it delivers on its promise.If successful, this collaboration could serve as a blueprint for how tech giants and pharma companies might work together on other chronic conditions. Imagine similar predictive approaches for heart disease, asthma, or Parkinson’s.For now, though, the focus is squarely on using AI to improve diabetes management and helping people sleep a little easier at night—quite literally, in the case of that clever nocturnal prediction feature. And honestly, that’s a worthwhile enough goal on its own.(Photo by Alexander Grey)Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.Explore other upcoming enterprise technology events and webinars powered by TechForge here.