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One of the biggest problems with today’s AI models is that they tend to simply make up answers when they don’t know what’s going on, something called hallucinations.

You would think that the number of hallucinations would decrease over time, but according to internal tests from Open AI, the opposite is true. The o3 and o4-mini reasoning AI models produce more hallucinations than their predecessors o1, o1-mini, and o3-mini, Techcrunch reports.

In one of the tests, the o3 model hallucinated in 33% of responses, compared to 16% for the o1 and 14.8% for the 03-mini.

Open AI has no idea why this is the case, but the company’s developers are looking into it and hopefully it will get better in the long run.

Cybersecurity researchers have detailed a malware campaign that's targeting Docker environments with a previously undocumented technique to mine cryptocurrency. The activity cluster, per Darktrace and Cado Security, represents a shift from other cryptojacking campaigns that directly deploy miners like XMRig to illicitly profit off the compute resources. This involves deploying a malware strain

Cybersecurity researchers have detailed a malware campaign that's targeting Docker environments with a previously undocumented technique to mine cryptocurrency. The activity cluster, per Darktrace and Cado Security, represents a shift from other cryptojacking campaigns that directly deploy miners like XMRig to illicitly profit off the compute resources. This involves deploying a malware strain Ravie Lakshmananhttp://www.blogger.com/profile/[email protected]

The recommended Ripple cryptocurrency NPM JavaScript library named "xrpl.js" was compromised to steal XRP wallet seeds and private keys and transfer them to an attacker-controlled server, allowing threat actors to steal all the funds stored in the wallets. [...]

The United Arab Emirates is planning to use AI to review and adjust existing legislation as well as write entirely new laws, reports the Financial Times. The Middle Eastern country is the first in the world to do so. Other countries are currently using AI to streamline various types of work, but not to create entirely new laws.

The UAE plans, for example, to use AI to see how laws affect the country’s population and economy by creating a database of laws with public sector data. The expectation is that AI will make local laws 70% faster and ensure they can be updated regularly. It is currently unknown what kind of AI system the country’s authorities will use.

“This new legislative system, powered by artificial intelligence, will change the way we create laws and make the process faster and more accurate,” said Sheikh Mohammad bin Rashid Al Maktoum, Emir of Dubai and Prime Minister and Vice President of the United Arab Emirates, according to the country’s state media.

**Microsoft blokuje prvky ActiveX ve Wordu a spol. **Přísné výchozí nastavení prostupuje do Microsoft 365. **Loni blokování zavedly Office 2024.

A proof-of-concept attack called "Cookie-Bite" uses a browser extension to steal browser session cookies from Azure Entra ID to bypass multi-factor authentication (MFA) protections and maintain access to cloud services like Microsoft 365, Outlook, and Teams. [...]

Cybersecurity researchers have detailed a now-patched vulnerability in Google Cloud Platform (GCP) that could have enabled an attacker to elevate their privileges in the Cloud Composer workflow orchestration service that's based on Apache Airflow. "This vulnerability lets attackers with edit permissions in Cloud Composer to escalate their access to the default Cloud Build service account, which

Cybersecurity researchers have detailed a now-patched vulnerability in Google Cloud Platform (GCP) that could have enabled an attacker to elevate their privileges in the Cloud Composer workflow orchestration service that's based on Apache Airflow. "This vulnerability lets attackers with edit permissions in Cloud Composer to escalate their access to the default Cloud Build service account, which Ravie Lakshmananhttp://www.blogger.com/profile/[email protected]

Google’s dominance in the search arena has given rise to two major antitrust lawsuits from the US government alleging the company has manipulated the market to maintain that dominance, to the exclusion of competitors and the detriment of the public at large.

The first lawsuit, targeting Google’s search business, kicked off in mid-September 2023 and drew to a close in May 2024; US District Judge Amit Mehta ruled against the tech giant in August 2024 and is now considering remedies. The second trial against the tech giant, focused on advertising, took place over 15 days in September 2024, with US District Judge Leonie Brinkema ruling against Google in April 2025. Google plans to appeal both decisions.

The cases heavily echo the turn-of-the-century Microsoft antitrust case in several respects, not least of which is the fact that Google faces the possibility of being broken up by regulators if it is unsuccessful in its legal battles.

Here’s our condensed timeline of the two lawsuits and their progress through the court system.

April 21, 2025: The remedy phase of Google’s search antitrust trial begins with Judge Mehta presiding. Federal prosecutors warn that Google might leverage artificial intelligence to entrench its search monopoly, demanding “strong measures” to prevent the tech giant from extending its market control into the AI era. These include requiring Google to divest Chrome, end exclusive default search agreements, license its search data to competitors, and potentially sell its Android operating system if other remedies fail.

April 17, 2025: In a second landmark defeat for Google, Judge Brinkema rules that Google illegally monopolized the ad tech market. The company’s “exclusionary conduct substantially harmed Google’s publisher customers, the competitive process, and, ultimately, consumers of information on the open web,” she wrote in the ruling. Remedies, which could include the breakup of Google’s advertising products and/or changes to its business practices, will be imposed at a future date.

Oct. 8, 2024: The US Department of Justice submits a court filing proposing that the Chrome browser and Android operating system be split off from Google as part of sweeping remedies aimed at curbing the tech giant’s monopoly in online search and advertising.

Sept. 20, 2024: The US Department of Justice is set to wrap its case in the Google antitrust trial after an eventful two weeks. The tech giant is accused of engaging in monopolistic behavior by strategically acquiring certain companies and controlling the adtech industry’s most widely-used tools and exchanges,  beginning with its acquisition of advertising company DoubleClick in 2008.

Sept. 9, 2024: The second major case against Google begins with the company defending itself against claims it engaged in illegal behavior to maintain control of the ad tech market. The US government is accusing Google of purposefully manipulating that market, snuffing out competitors and gobbling up key technologies through acquisitions. If the DoJ successfully makes its case, Google risks being broken up by regulators.

Aug. 5, 2024: In a major defeat for Google, Judge Amit Mehta rules that the company had engaged in anticompetitive behavior in an effort to protect its search business. In the 277-page decision, Mehta was blunt: “After having carefully considered and weighed the witness testimony and evidence, the court reaches the following conclusion: Google is a monopolist, and it has acted as one to maintain its monopoly. It has violated Section 2 of the Sherman Act.” Mehta’s ruling did not include remedies for the anticompetitive behavior; those will be decided later.

May 3, 2024: Over two days of closing arguments, the DoJ revisits its case for Google having a monopoly on search advertising, and Judge Mehta quizzes both parties about whether other platforms could be viewed as substitutes for Google’s search advertising business. He hasn’t said how long he expects to take to reach a decision, but if he rules against Google, a second hearing will take place to decide on any remedies.

Nov. 16, 2023: The evidentiary phase of the trial finishes, as Judge Mehta issues instructions for post-trial submissions. Despite considerable amounts of redaction and closed-door testimony, the case revealed some unprecedented details about the relationships between the largest tech companies in the world, including the fact that Apple apparently keeps 36% of the search revenue from Google searches in Safari, and Apple once considered buying Microsoft’s Bing search engine as leverage against Google. Judge Mehta has scheduled closing arguments in the case for May 1, 2024.

Oct. 31, 2023: Google CEO Sundai Pichai takes the stand, for long-awaited testimony about the relationship between his company and Apple. He gave some details about Google’s negotiations with Apple over a contract that made Google the default search engine on Apple’s iPhones, iPads, and Macs. Google has paid billions for the privilege of being the default search on Apple products, and the relationship is a key part of the case – which was underlined by the Justice Department’s cross-examination of Pichai, during which he admitted that default search status is a major driver of market share.

Oct. 18, 2023: Google begins its defense, calling Paul Nayak, a vice president of search, to the stand as its first witness. Nayak downplays the importance of scale in his testimony, stressing that machine intelligence, compute infrastructure, and a team of 16,000 staff that checks on search results are crucial to maintaining quality of service. DOJ witnesses including DuckDuckGo CEO Gabriel Weinberg and Microsoft CEO Satya Nadella had testified that Google keeps an edge over competitors via an ever-increasing trove of data — the result of its default search engine status, maintained through exclusive contracts and billions of dollars in payments to Apple, Samsung and other companies. This data gives Google an advantage in refining search engine results, they said. 

Oct. 3, 2023: As a witness for the prosecution in the Google antitrust trial, Microsoft CEO Satya Nadella warns that Google’s monopoly profits could lock in publishers as AI-enabled search arrives. Nadella argued that it’s almost impossible to compete with Google, given the search leader’s massive competitive edge in collecting and analyzing user data. He also warned that Google, with its vast profits and lock on the search market, stands poised to extend its monopoly power in a new era where artificial intelligence technologies will turbocharge the search business.

Sept. 26, 2023: Apple’s Eddy Cue testifies behind closed doors in the Google search case, as critics slam presiding Judge Amit Mehta’s decision to hold much of the trial’s testimony from witnesses secret, allow documents to be heavily redacted, and block some documents from public view — mainly at the insistence of Google, but also at the request of other companies, including Apple. By the end of Cue’s testimony — and after a wek of wrangling by all parties — Judge Mehta rules that documents used during the trial can be published online at the end of each day, but still allows time Google and third parties to object to exhibits being shown publicly before the DOJ presents them in court. 

Sept. 21, 2023: Judge Mehta rules that public access to court exhibits, which have been mostly internal Google documents thus far, should be removed, after Google challenged the Justice Department’s regular publication of them. The company said that it was concerned for its employees’ privacy.

Sept. 12, 2023: The default search trial begins with opening statements, and the government begins its case.

Aug. 2023: Judge Mehta grants partial summary judgment for Google in the search case, saying that the government had failed to raise a genuine dispute of material fact on antitrust charges relating to contracts around the use of the Android operating system, as well as Google Assistant and IoT devices. The claims relating to Google’s exclusive “default search” contracts, however, are allowed to proceed to trial.

July/Aug. 2023: Google and the plaintiffs in the search case argue various motions in limine, designed to control what evidence should be included or excluded in the actual trial. Discovery and motion practice over evidence continues in the advertising case.

June 2023: Judge Mehta schedules a trial date of September 12, 2023 for the search case.

April 2023: Judge Leonie M. Brinkema denies Google’s motion to dismiss in the advertising case.

March 2023: Google’s motion to transfer the advertising case to New York is denied by Judge Brinkema, who orders the parties to propose discovery schedules within two weeks of the order. Two weeks later, Google moves to dismiss the case for failure to state a claim, arguing that the plaintiffs have simply produced legal conclusions, and not specific facts, that could support their claims. Judge Brinkema schedules pre-trial conferences for January 2024.

Feb. 2023: The plaintiffs in the default search case case move for sanctions against Google, accusing it of spoliation, which refers to the destruction, alteration or failure to preserve relevant evidence in a case. Elsewhere, in the advertising case, Google moves to transfer the case from the Eastern District of Virginia to the Southern District of New York, which is seen as an attempt to consolidate the case with related digital advertising antitrust litigation.

Jan. 2023: A second antitrust action, pushed by eight states and the DoJ, is filed in federal district court in eastern Virginia. The plaintiffs, who call for Google’s advertising business to be split up, accuse Google of manipulating its dominant position in the online advertising world to squeeze out rivals and control both the supply and demand side of the advertising market. Google, according to the complaint, thwarted fair competition by manipulating fees, punished advertisers for using alternative platforms and ad exchanges, and engaged in a host of further anti-competitive behavior in the interest of monopolizing the marketplace. (This is case that began in September 2024.)

Dec. 2022: Google moves for summary judgment against the separate Colorado case and the larger, DoJ-led case. A summary judgement motion is essentially a request by one of the parties in a lawsuit that the judge rule in their favor and end the case, arguing that, based on the undisputed facts, they are entitled to win the case as a matter of law.

May 2022: A deadline of June 17 is set for the production of all discovery materials. Further documents – for example, those whose is existence is first disclosed in late in the discovery window – can be produced until June 30.

May 2022: Judge Mehta denies a government motion to sanction Google for inaccurately classifying documents as attorney-client privileged. The plaintiffs had argued that emails on which Google’s lawyers were listed as recipients or CCed, but that the lawyers never responded to, constituted a misuse of the attorney-client privilege rules.

Dec. 2021: Judge Mehta conditionally splits Colorado’s claims from the case at large, ordering that separate trials on that state’s issues of liability and remedies will be “more convenient for the Court and the Parties, and will expedite and economize this litigation.”

Aug.-Oct. 2021: Discovery-related motions and orders continue, as Yelp and Samsung join the fray. (Those companies, like Microsoft and Apple, are relevant to the case even if they aren’t parties themselves, as their internal records are potentially relevant to Google’s liability.)

June/July 2021: The discovery process continues, and the U.S. and Google both file several documents with the court under seal. (Microsoft files two sealed documents, as well, in response to Google’s subpoenas for company records, and Apple becomes involved after the government requests access to some of its internal information.)

March 2021: Meetings between Google and the various governmental plaintiffs continue, with periodic status reports on the discovery process.

Jan. 2021: Google files a response to the complaint, admitting to many of the facts alleged by the Justice Department and associated attorneys general, but categorically denying the substance of the government’s claims of illegality. Further responses to separate but related claims, generally to specific state attorneys general, follow in the subsequent weeks and months.

Dec. 2020: Judge Amit Mehta approves the joinder of Michigan, Wisconsin and California to the suit.

Oct. 2020: The Department of Justice, along with the attorneys general of 11 states, sues Google in DC federal district court for unlawfully maintaining a monopoly, in violation of Section 2 of the Sherman Act. The case centers on Google’s use of exclusive contracts that mandate its use as the default search engine in a host of different hardware and software applications, with the government alleging that this represents an artificial constraint on any possible competition for the search giant.

Federal prosecutors warned that Google might leverage artificial intelligence to entrench its search monopoly, demanding “strong measures” to prevent the tech giant from extending its market control into the AI era.

In the latest phase of the major antitrust trial that began on Monday, government lawyer David Dahlquist argued that Google has built a system where its control of search helps improve its AI products, which then send more users back to Google search, creating a cycle that keeps competitors locked out of both markets.

“Now is the time to tell Google and all other monopolists who are out there listening, and they are listening, that there are consequences when you break the antitrust laws,” Department of Justice attorney David Dahlquist told the court Monday, as the remedies phase of the landmark antitrust case against Google began, reported Reuters.

[ Google US antitrust trials: A timeline ]

The trial, which follows Judge Amit Mehta’s August 2024 ruling that Google illegally maintained a search monopoly, has evolved into a showdown over how deeply the government can intervene in tech markets—particularly as the industry rapidly shifts toward AI-powered services.

The AI expansion strategy

Evidence presented in court revealed that Google is employing familiar tactics to dominate the emerging AI landscape. The company has negotiated deals paying Samsung to preinstall its Gemini AI app on smartphones, with options to extend the arrangement through 2028.

The Justice Department contended that this mirrors the exclusive agreements with device makers that Judge Mehta previously ruled helped Google maintain its search monopoly. The government’s case portrays a self-reinforcing cycle: Google’s search dominance improves its AI products, which in turn drive users back to its search engine.

“This court’s remedy should be forward-looking and not ignore what is on the horizon,” Dahlquist emphasized, as per the report.

To underscore its focus on AI competition, the DOJ called OpenAI’s product head for ChatGPT, Nick Turley, to testify—signaling the government’s concern about how search and generative AI are converging.

“If Google’s conduct is not remedied, it will control much of the internet for the next decade and not just in internet search, but in new technologies like artificial intelligence,” DoJ Assistant Attorney General Gail Slater said in a statement.

Remedies that reshape markets

The Justice Department is pushing for interventions that would fundamentally alter Google’s business model. Their proposals include requiring Google to divest Chrome, end exclusive default search agreements, and license its search data to competitors. As a last resort, they’ve suggested Google might need to sell its Android operating system if other remedies fail.

However, industry analysts question whether some of these remedies align with market realities. Neil Shah, VP for research and partner at Counterpoint Research, believes the Chrome divestiture may miss the bigger picture.

“Chrome separation doesn’t impact Google much in the long run as we are moving from browser and app-centric to an Agentic world where search and content access will happen inside the agent app and browser becomes redundant property,” Shah said. “The AI agent itself becomes the search engine.”

Sanchit Vir Gogia, chief analyst and CEO of Greyhound Research, expressed similar concerns about focusing too narrowly on Chrome: “Separating Chrome from Google risks destabilizing a global platform that underpins not just web access, but AI discovery itself.”

Both analysts said that more attention should be directed toward Google’s control of the Android ecosystem, where default settings and bundled services most effectively limit competition.

The DOJ’s proposal for Google to license its search data to competitors faces significant practical challenges, according to experts.

“Mandating Google to license its search data may sound like fair market correction, but risks cascading privacy and compliance fallout,” Gogia noted. “Google’s behavioral query logs are rich and sensitive, anonymizing them without destroying contextual utility is technically tenuous.”

Shah was more direct: “DOJ’s remedy of Google sharing search results data turns its advertising-led business model as well as tech stack upside down and won’t be practically feasible.”

Google’s defense: national security and innovation

Google has framed the government’s proposals as threats to the US technological leadership in the global AI race with China — an argument that has gained traction among some industry observers.

“We’re in a fiercely competitive global race with China for the next generation of technology leadership, and Google is at the forefront of American companies making scientific and technological breakthroughs,” Lee-Anne Mulholland, Google’s vice president of regulatory affairs, wrote in a blog post.

“With new services like ChatGPT (and foreign competitors like DeepSeek) thriving, DOJ’s sweeping remedy proposals are both unnecessary and harmful,” Mulholland added in the post.

Gogia acknowledged the complexity of this argument, “Google’s concerns about national security aren’t misplaced. Fragmenting Google’s ecosystem may slow down America’s cohesive AI response to China. But a strong counter opinion to this is that it is a long-overdue correction to embedded defaults that restrict platform access.”

Competitors seek a middle ground

As the case unfolds, emerging AI search competitors are advocating for more nuanced solutions. Perplexity, an AI-powered search engine, published a blog post arguing that “the remedy isn’t breakup,” but rather increased consumer choice.

“When we think about a search product that’s 10X better than 10 blue links, we also think about being a company that works better with OEMs, carriers, and partners of all kinds,” Perplexity wrote in the blog.  “That’s because the only way we (or anyone else) can compete after all the hard work of building a superior product, is to be chosen.”

The company has been asked by both the DOJ and Google to share its opinion.

This approach aligns with Shah’s analysis: “Maximum DOJ would end up focusing on the exclusive agreements with OEMs and other ecosystem players to make it a somewhat level playing field where users have the choice of the agent.” The remedies trial is expected to conclude May 9, with Judge Mehta’s ruling anticipated in August. Google has already indicated it plans to appeal.

As SaaS and cloud-native work reshape the enterprise, the web browser has emerged as the new endpoint. However, unlike endpoints, browsers remain mostly unmonitored, despite being responsible for more than 70% of modern malware attacks. Keep Aware’s recent State of Browser Security report highlights major concerns security leaders face with employees using the web browser for most of their work.

As SaaS and cloud-native work reshape the enterprise, the web browser has emerged as the new endpoint. However, unlike endpoints, browsers remain mostly unmonitored, despite being responsible for more than 70% of modern malware attacks. Keep Aware’s recent State of Browser Security report highlights major concerns security leaders face with employees using the web browser for most of their [email protected]

Generative artificial intelligence (genAI) capabilities and features are coming to unified endpoint management (UEM) platforms — in fact, some are already here — and technology and business leaders need to be prepared for the challenges they might face.

Some of the leading UEM vendors are weaving AI and genAI features into their platforms. Here are a few examples:

ManageEngine has made its in-house AI-based assistant, Zia, an integral part of its UEM solution, Endpoint Central. Through natural-language interactions with the “Ask Zia” chatbot, IT teams can tap into AI-powered insights, intelligent report generation, and AI-enabled remote support.

Upcoming features for the platform include genAI-powered management and security automation. GenAI capabilities will be integrated through Ask Zia, and additional features will be aimed at enhancing device performance optimization and security incident management.

Microsoft offers Copilot for Windows Autopatch in its Intune UEM product, which enables AI-driven guidance through every update management stage, from planning and deployment tracking to issue identification and remediation. The genAI tool provides actionable insights so teams can keep endpoints secure and up to date with minimal disruption, according to the company. Other available or upcoming Intune features include Copilot assistance for multiple device queries, endpoint privilege management, and policy management.

BlackBerry’s mobile threat defense capability for UEM uses AI and machine learning models for scoring apps and URLs to check for malware and malicious sites and phishing incidents. The company says it is evaluating genAI use cases across both servers and apps for inclusion in future releases, with an emphasis on maintaining customer data privacy. A spokesperson declined further comments on these roadmap features or the approximate timeframe of release.

Industry watchers also point to improved script generation, natural-language data extraction and analysis, and end-user support as likely applications for genAI in UEM tools.

In a large enterprise, a UEM platform might be managing thousands of user devices and other endpoints and tightly tied to security systems, digital employee experience tools, and other enterprise software. Clearly there’s a potential for challenges around security, user experience, and operational efficiency when genAI is embedded in UEM. Preparation is important for success.

Computerworld asked three enterprise mobility analysts for their advice on how businesses can take advantage of genAI in UEM tools while still protecting their users, systems, and data.

Ask vendors for key information

“The most important first step that organizations can take is to fully understand the vendor’s roadmap for genAI features, along with the architecture that will be used to deliver the capabilities,” said Tom Cipolla, senior director and analyst at research firm Gartner.

“Surprise releases of genAI are indicative of a failure to prepare and a potentially weak vendor relationship,” Cipolla said.

Technology costs are a common concern of organizations, so executives need to keep tabs on how much genAI features cost and whether the added expense is worth it.

“Today, most of these capabilities are beta and offered at no cost,” said Andrew Hewitt, principal analyst at Forrester Research. “However, that may not last, as the cost of genAI is high.” Customers should ask vendors for specifics on what they intend to charge for various genAI features in their UEM platforms — and when, he said.

Other big issues include cybersecurity and the privacy of corporate data.

“GenAI may be utilizing data that is proprietary to the organization, and sending that to a third-party cloud” could be risky, Hewitt said. It’s a good practice to verify with the UEM vendor that data is being processed locally and protected, he said.

To that end, UEM customers need to get guarantees from their vendor about security and privacy protections, Hewitt said. It should be stated in the contract that customers’ proprietary data, including their employees’ private data, is encrypted and will not be used in training genAI models.

Gartner’s Cipolla also urged IT leaders to ensure that their UEM vendors are making security a priority with genAI. Ideally, genAI features should be provided in a secure way that isolates personal employee and customer data.

“Organizations should carefully review the data privacy protection documentation provided by the vendor, specifically looking for cases where the genAI capabilities of the platform use public large language models to fulfill requests,” Cipolla said.

Create guardrails

Before deploying any forthcoming genAI capabilities in their UEM platforms, companies should take steps to protect their systems and data. For example, they need to put guardrails in place to make sure proprietary data, such as personally identifiable information for employees, is protected.

“Organizations need to build AI governance not just for UEM platforms, but also across the digital workplace stack,” Hewitt said. “They should be doing an inventory of where their data currently resides, what protections they have in place for secure authorization, and doing their due diligence around personal or other sensitive information.”

IT organizations should start to think about their automation process, Hewitt added. “What types of approvals and authorizations will be necessary to execute automation in the endpoint management stack?” he said. “How will they plan to gain trust and confidence in AI and automation? How should they measure this? Taking an inventory of existing automation processes could help here, as well as doing some testing of genAI on basic use cases.”

Testing genAI features should be done in a safe environment prior to rolling them out. “As with any AI solution, organizations should proceed carefully and employ a ‘block, walk, run’ strategy while they gain comfort with the solution and its security,” Cipolla said.

Verify, test, and monitor — with humans in charge

As genAI features begin to appear in UEM tools, “organizations should ensure that endpoint device management tasks or functions enabled or assisted by AI have similar or better outcomes” than approaches used previously, said Phil Hochmuth, program vice president, enterprise mobility, at research firm IDC.

That means keeping a close eye on AI recommendations and actions. “Teams using AI in IT operations for endpoints must be watchful for AI system misinterpretation, partial or incorrect completion of tasks, and other bad outcomes that affect end-user productivity,” Hochmuth said.

Enterprises need to be especially mindful of false or inaccurate recommendations from AI, Hewitt said. Administrators need to conduct a “sanity check” on these recommendations before implementing them in their environment. For example, it’s important to confirm that the recommendations are based on recent or real-time data, he said.

Cipolla concurred. “Information delivered via genAI can contain inaccuracies and hallucinations — statements that sound factual but are not accurate — resulting from the large language model used to train the AI,” he said.

If genAI results are not verified prior to usage, that could result in significant operational impacts, including loss of data, a brand credibility hit, and a degraded digital employee experience, Cipolla said.

“For this reason, genAI must be combined with human expertise to validate generated results,” he said. “Prior to implementation of genAI recommendations, ensure that at least one expert human validates the accuracy of the information. Do not use genAI to validate genAI, as different models could share hallucinations.” 

To reduce the risk of inaccurate results, Cipolla recommended using a framework similar to common approaches based on the IT Infrastructure Library (ITIL), where proper vetting of IT changes is performed.

“Also, prior to implementing any script in a production environment, ensure that testing is performed to validate that there are no unintended side effects. After implementation, carefully monitor the operation of the system for delayed impacts,” Cipolla said.

Share what works and build on success

Organizations should not fall into the trap of thinking genAI can replace tech employees.

“The accuracy of genAI-produced information within tailored use cases, such as digital workplace management tools, will improve quickly. However, genAI will never be able to replace human intuition, empathy, curiosity, experience, and expertise within the digital workplace,” Cipolla said.

To prevent potentially catastrophic results, “genAI must be positioned to augment humans and not be seen as an opportunity to replace humans,” Cipolla said. “Human creativity and expertise combined with genAI is a force multiplier that has the potential to yield significant breakthroughs.”

To share and collectively improve on positive results, Cipolla recommended that organizations create wiki-style, easily searchable libraries of prompts (and sample result sets) that can be used to identify common successful prompts.

“This can be as simple as a shared spreadsheet, a channel in a collaboration tool, or a basic wiki-style website. Enable all employees to contribute, and recognize those employees who exhibit extraordinary creativity in their prompts,” Cipolla said.

“Prompt libraries also can be purchased from vendors as a service,” he noted.

Here, too, communication with the UEM vendor is important. Most genAI capabilities will have built-in feedback collection mechanisms, where feedback is routed to the vendor for integration into the program, Cipolla said. In this way, genAI successes (and failures) can be used to improve the features in the future.

In what has been described as an "extremely sophisticated phishing attack," threat actors have leveraged an uncommon approach that allowed bogus emails to be sent via Google's infrastructure and redirect message recipients to fraudulent sites that harvest their credentials. "The first thing to note is that this is a valid, signed email – it really was sent from [email protected]," Nick Johnson

In what has been described as an "extremely sophisticated phishing attack," threat actors have leveraged an uncommon approach that allowed bogus emails to be sent via Google's infrastructure and redirect message recipients to fraudulent sites that harvest their credentials. "The first thing to note is that this is a valid, signed email – it really was sent from [email protected]," Nick JohnsonRavie Lakshmananhttp://www.blogger.com/profile/[email protected]

Huawei is reportedly preparing to ramp up shipments of its new 910C AI chip to Chinese customers as early as next month, a move that could accelerate the fragmentation of global AI infrastructure and challenge US chip dominance in enterprise workloads.

Some of the chips have already been shipped, according to a Reuters report, as Chinese AI companies scramble for domestic alternatives to Nvidia’s H20 – a chip that had, until recently, been freely available in the region.

Security is an essential consideration when using computers and other technological devices. Linux admins and organizations must be informed about applicable legal measures related to the safety of their systems to ensure compliance and protect against possible risks.

CUPS, or the Common Unix Printing System , is an open-source printing system widely utilized on Unix-like operating systems such as Linux, BSDs, and macOS. CUPS acts as an open-source print server, allowing a computer to become an effective print server while managing print jobs and queues and providing a standardized interface for printing services.

In the current threat landscape, Linux servers have emerged as a dominant force, underpinning approximately 81% of all websites globally. Despite the prevalence of Windows in personal computing, Linux's resilience to various threats is a significant factor behind its extensive adoption, particularly in web hosting and enterprise environments.