Featured UK & Global AI News from AIBusinessHelp - Page 67

Pope Leo XIV published his first encyclical, Magnifica Humanitas, May 25, warning that artificial intelligence (AI) and other technological advances pose moral challenges that could reshape humanity’s understanding of truth, work, relationships, and human dignity.“Humanity, created by God in all its grandeur, is today facing a pivotal choice: either to construct a new Tower of Babel or to build the city in which God and humanity dwell together,” the encyclical, subtitled “On Safeguarding the Human Person in the Time of Artificial Intelligence,” opens.Pope Leo signed the encyclical May 15, the 135th anniversary of Pope Leo XIII’s 1891 encyclical Rerum Novarum,...

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As generative AI reshapes industries worldwide, the startup investment landscape is also undergoing rapid transformation. Industry observers say that beyond securing funding, the ability to implement AI in real business operations and integrate technologies into scalable business models is becoming

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India's finance workforce must shift from reporting to strategy as AI takes over transactional work, AICPA leaders said at a Bengaluru summit. Younger professionals will manage AI agents directly, changing career paths from entry level up.

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If you have read anything about AI in Singapore over the past two years, you have probably seen the headlines. World-class AI infrastructure. Top three globally for government AI readiness. Number one in Asia for population-level AI usage. A national AI council chaired by the Prime Minister. Budget 2026 is putting AI at the centre [...] The post Singapore’s AI paradox: World-class infrastructure, single-digit SME adoption appeared first on e27 .

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Virgin Atlantic launched the first airline booking experience inside ChatGPT in April 2026, letting customers plan trips through conversation. Flights are suggested within the chat, but purchases still complete on Virgin Atlantic's website.

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AI SEO jargon is exploding, but most of these terms point to the same shift in search.

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TAIPEI, May 26, 2026 /PRNewswire/ -- AIC, a leading provider of AI storage and computing solutions, is proud to announce its participation in COMPUTEX 2026. From June 2 to June 5, AIC will showcase its latest innovations at TaiNEX 1, 4F, Booth N1106, focusing on building the infrastructure layer for the Agentic AI era. AIC to showcase Next-Generation AI Infrastructure at COMPUTEX 2026 Strategic Panel: Breaking the Memory Wall As AI evolves toward reasoning models and long-context inference, the industry faces a new bottleneck: moving and managing data efficiently. To address this, AIC will host a premier panel discussion exploring how storage is evolving from a passive repository into an active part of AI intelligence delivery. Topic: "Breaking the Memory Wall in the AI Era - Storage Challenges and Opportunities"Date/Time: June 2, 2026, at 14:00.Location: AIC Booth (N1106). The panel features industry leaders representing the critical "Infrastructure Layer" of the AI stack:Michael Liang, Chairman and CEO of AIC.Jason Hardy, VP of Storage Technology at NVIDIA.Andy Pernsteiner, Field CTO at VAST Data.AIC Exhibition Highlights AIC will demonstrate how its hardware platforms integrate with ecosystem partners to solve modern data challenges: AI Storage Solutions with NVIDIA CMX: AIC platforms feature NVIDIA Context Memory Platform (CMX) to overcome memory limitations in LLM inference. The NVMe SSD-based architecture, integrated with NVIDIA BlueField-4 to enable high-density GPU deployment for video analytics and LLM services.High-Performance Computing: New GPU server platforms delivering higher I/O bandwidth and lower latency for GenAI training, scientific simulations and enterprise data analytics.Intelligent Edge Computing: Short-depth GPU servers designed for space-constrained edge-to-cloud deployments, supporting multi-GPU scaling for real-time smart city and industrial automation.GPU-Accelerated Platforms: Integration of SCADA with GPU-centric platforms with ultra-high IOPS storage to support data-intensive AI workloads and accelerate end-to-end processing. Michael Liang, Chairman and CEO of AIC, stated: "In response to the fundamental transition in AI workloads, a comprehensive upgrade of AI infrastructure is essential. AIC is honored to collaborate with NVIDIA and VAST Data to co-create foundational platforms featuring high scalability and extreme performance. Our goal is to empower customers to maintain a leading edge in the next wave of AI.". Event Information Dates: June 2 - June 5, 2026Exhibition Hours: 09:30 - 17:30Venue: 4F, TaiNEX 1AIC Booth: N1106About AIC AIC is a global leader in server and storage solutions. With 30 years of expertise in high-density storage servers, storage server barebones, and high-performance computers/servers. The company's in-house design, manufacturing, and validation capabilities ensure products are highly flexible and configurable. Headquartered in Taiwan, AIC operates offices and facilities across the United States, Asia, and Europe. For more information, please visit www.aicipc.com.

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Taiwan Premier Cho assures power supply through 2030 after Nvidia CEO Jensen Huang warns the island needs more energy for AI growth and manufacturing.

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Pope Leo XIV called for strong AI regulation, warning that unchecked technology and profit-driven innovation could threaten jobs, human dignity and global peace.

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The 2026 Cannes Film Festival showcased a notable absence of major studios, allowing queer cinema to take the spotlight with several acclaimed entries. The integration of AI technology in filmmaking sparked discussions on its impact on the industry. These developments signal a potential shift in cinematic storytelling and production dynamics.

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ClickUp, a nine-year-old startup, has initiated mass layoffs, replacing hundreds of its employees with thousands of AI agents. This move highlights a significant shift in the future of work as companies increasingly turn to automation to enhance efficiency. The decision raises important questions about job security and the evolving role of human workers in the tech industry.

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The industry ministry on Tuesday discussed ways to accelerate the artificial intelligence (AI) transformation of the battery industry, currently facing sluggish growth amid the electric vehicle (EV) market slowdown. The Ministry of Trade, Industry and Resources met with representatives from leading battery maker LG Energy Solution Ltd. (LGES) to explore measures to help the domestic battery industry strengthen its manufacturing competitiveness under the government's initiative aimed at promoting the AI transformation of the manufacturing sector. In the meeting, which took place at LGES' smart manufacturing facility in the central city of Cheongju, the two sides discussed ways to support local battery makers in adopting AI technologies to improve production efficiency and maintain a competitive edge against global rivals, according to the ministry. The LGES has applied digital twin technology at its cylindrical battery production facility, increasing the production speed by more than 50 percent and reducing investment costs. "Manufacturing AI transformation has become an essential task fo

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Korea is turning to artificial intelligence (AI) to protect its most critical ecological asset from the accelerating threats of the climate crisis. The National Institute of Forest Science (NIFOS), an agency under the Korea Forest Service, announced a major technological initiative to systematically assess and safeguard the Baekdudaegan. This vast mountain system spans the length of the Korean Peninsula and serves as the region's core ecological spine and a critical sanctuary for biodiversity. The initiative leverages decades of comprehensive datasets accumulated by the state, including the National Forest Inventory and the Baekdudaegan Resource Status Change Survey. After aggregating this massive volume of data, researchers applied advanced statistical techniques alongside nine distinct machine-learning models. The result is a highly sophisticated, predictive mapping system detailing the distribution of 989 distinct biological species across the mountain range. This allows conservationists to analyze and categorize biodiversity health levels across the entire Baekdudaegan territory at

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Child actor Choi Woo-jin sparked online debate after viewers said his striking resemblance to Koo Kyo-hwan in "Colony" made his scenes appear to have been generated by artificial intelligence (AI). Choi plays the younger version of Seo Young-chul, Koo's character, in the sci-fi thriller. The child actor made a strong impression despite his limited screen time. The physical similarities prompted social media users to compare the boy's scenes to Koo's old graduation photos. Some viewers said on social media, "I thought it was made with AI." Choi's representative clarified the rumors on the actor's official social media. "Not AI. It is 14-year-old actor Choi Woo-jin," the post said. The viral moment coincides with a massive opening weekend for the zombie thriller. Released on Thursday, "Colony" topped the box office by drawing 1.28 million moviegoers between Friday and Sunday. The movie surpassed 1 million ticket sales on Sunday, making it the fastest film this year to reach the milestone. "Colony" marks director Yeon Sang-ho's return to the zombie genre after six years. The plot follows su

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Anthropic's Restricted Claude Mythos Moves Toward Public Release via Claude Code and Security CyberSecurityNews Project Glasswing: An initial update Anthropic Project Glasswing: what Mythos showed us The Cloudflare Blog Anthropic: Mythos Detected 23,000 Potential Vulnerabilities Across 1,000 OSS Projects SecurityWeek Claude Mythos AI Finds 10,000 High-Severity Flaws in Widely Used Software The Hacker News

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(MENAFN - GlobeNewsWire - Nasdaq) DUBAI, United Arab Emirates, May 26, 2026 (GLOBE NEWSWIRE) -- The agent economy is reshaping financial markets. Open-source agent frameworks are accelerating ...

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Nvidia CEO Jensen Huang said on Saturday that his forecast of a $200 billion market for CPUs includes China

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Senior decision-makers are the heaviest users of unapproved AI tools, and they continue using them despite being aware of the security and privacy risks linked to shadow AI, according to TrustedTech’s Shadow AI in the Workplace report. The study found that 65% of decision-makers use shadow AI, compared with 31% of employees below decision-maker level. Net Shadow AI use (Source: TrustedTech) The data suggests that shadow AI is not mainly driven by junior employees experimenting ... More → The post Turns out the C-suite loves shadow AI appeared first on Help Net Security .

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US tech giants are tapping markets as they race to build AI data centres

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The Scottish Government is facing calls to 'urgently address' what has been described as 'major shortcomings' in its policy on data centres

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Last year, analyst Forrester reported that while IT departments manage billion-dollar portfolios, their internal operations lag in automation, coordination and visibility. The complexity of managing a modern IT architecture means network management must evolve. This is not something that is entirely new. Automation is part of the functionality available in modern network management tools. Big data analysis of network log files is used in security information and event management (SIEM), and machine learning (ML) is helping network administrators identify potential issues before they affect the business. Phil Huang, business development and field application manager at D-Link, explains: “We have been offering a pure cloud management platform for networks for a number of years and the AI [artificial intelligence] assistance behind such network management gives us the ability to monitor in real time and also proactively try to alert of any potential problems that may arise.” Advances in tooling potentially reduce the complexity of network management. Matt Stava, CEO and chairman of third-party support firm Spinnaker Support, says this changes the role of IT administrators and programmers. Looking specifically at network skills, he says: “The need for a Cisco-certified expert is getting less and less right now.” Modern networking skills Modern IT infrastructure means that having an industry-certified network specialist is becoming less relevant. In a March 2026 blog post, Amit Katz, vice-president of ethernet switch at Nvidia, highlights the shifts occurring in network management. In the post, Katz points out that while the value of a new network administrator may have previously been measured by their level of expertise in a particular networking command line interface (CLI), the advent of hybrid cloud and DevOps means there is a growing shift towards application programming interfaces (APIs). “Skills in Ansible, Salt [the open source automation framework] and Python now have more value than a Cisco certification,” he says. Now, Katz believes the tasks network administrators need to do are very different from the way they used to monitor and manage networks. Skills in Ansible, Salt and Python now have more value than a Cisco certification Amit Katz, Nvidia “You’ve moved from tools that polled devices across the datacentre using SNMP [Simple Network Management Protocol] and NetFlow [which monitors IP traffic] to new switch-based telemetry models where the switches proactively stream flow-based diagnostic details,” he notes in the blog post. And according to Katz, while network administrators have a lot of experience introducing new workloads into datacentres – some of which have unique networking requirements – building an AI cluster is actually very different. He writes: “It is tempting to think that AI is just a bigger and faster big data application. But AI is different, and AI can be hard without the right tools.” AI also has a role to play in helping network administrators manage this complexity more easily. Information Services Group (ISG), a research and advisory firm, says organisations are taking advantage of the enhanced capabilities of AI and ML to automate configuration changes and optimisation across the network. In an ISG article about how AI is transforming network operations, Marc Herren, a director at ISG, notes that AI can analyse network data and identify patterns to automatically generate configurations that optimise performance. He says Cisco and Juniper Networks, the latter now being part of Hewlett Packard Enterprise, are developing intent-based networking products that use AI to understand an administrator’s intent and automatically configure the network accordingly. Such technology is essential to keep on top of ever-more-complex network management. Network complexity In a presentation at Microsoft Build 2025, Phil Gervasi, director of technical evangelism at Kentik, spoke about how networks are growing in complexity. They now span different clouds, datacentres, edge computing and hybrid IT infrastructure, all of which introduce new challenges for network management. “The volume of telemetry, events and logs has exploded beyond human capacity to analyse in real time,” he told attendees. At the same time, as Gervasi noted, network teams are under pressure to improve the mean time to resolution of an issue, and maintain uptime without expanding headcount. The volume of telemetry, events and logs has exploded beyond human capacity to analyse in real time Phil Gervasi, Kentik “What AI offers is not magic, but a better way to correlate data, forecast performance and understand network behaviour in context. So, in short, AI helps operators move from reacting to predicting,” he added. While ML is being used in networking for capacity planning, anomaly detection and baselining, Gervasi said that large language models (LLMs) offer a different approach to network management. “Unlike classical data models, which rely on structured data, LLMs operate on unstructured information like documentation, configuration files and tickets,” he told Build 2025 delegates. However, LLMs are probabilistic, which means they can produce inconsistent and different answers to the same prompts. They also hallucinate. To get around these limitations, Gervasi stressed the need to ensure quality of training data, proper evaluation and controlled model behaviour. These are key to keeping LLM responses honest. Privacy and regulation are also issues for LLMs, especially when handling network data that could contain sensitive information. Some IT operations challenges are inherent to AI use. For Gervasi, IT decision-makers need to be aware of the difficulties that may arise when integrating real-time telemetry, dealing with diverse data types, and managing compute costs for AI workloads. But, despite these caveats, Gervasi believes the real power of LLMs lies in their ability to synthesise vast volumes of data into information that can then be used by people to make better decisions. Among the examples he provided during his Build 2025 talk was incident triage and summarisation. “Instead of sifting through hundreds of alerts, an AI system can turn that noise into a single incident summary, highlighting probable root cause, and even suggesting next steps,” Gervasi said. Getting started with AI in network management The starting point in using AI for network management is collecting network telemetry logs, helpdesk ticket and configuration files. Those then need to be cleaned up and stored in a format that can be accessed by the AI system. Gervasi told delegates that one of the most effective ways to use this information is through retrieval augmented generation (RAG). As an example, he said when a user submits a query, the system converts the question into a mathematical representation, which searches a vector database for semantically related data, such as telemetry, past incidents or documentation. “The LLM then synthesises an answer, using both its general knowledge and the retrieved context,” he explained. Another use for LLMs is in text-to-structured query language (SQL), which, as Gervasi noted, enables network engineers to use natural language, where their queries are converted by the LLM into an SQL query and then, where relevant, provide a graphical representation of the data. Once the data is in a format the AI model can process, agentic AI is a natural progression. “An LLM doesn't just respond to prompts, but acts kind of like the brain, coordinating multiple tools,” he says. During the presentation, Gervasi spoke about how with agentic AI powering network management, an agent could run a trace route, collect network telemetry, consult a knowledge base, and then generate a remediation plan, all autonomously, but with human oversight. This is something that is likely to provide autonomous operations behind commercial network provider services. Analyst Gartner expects that AI will be embedded into managed network services (MNS) by 2028, to increase and enhance operational efficiency and enable more informed decision-making. According to Gartner, AI will be used to ensure that networks are robust and agile enough to adapt to changing demands and traffic patterns. “Looking ahead three to five years from now, we anticipate significant transformation in MNS due to extensive use of AI and automation,” the analyst firm stated in its AI will transform managed network services in the next three years report. For Stava and other industry watchers, the hot skill is agentic AI and the ability to integrate AI agents into workflows to achieve a business outcome. And these outcomes are increasingly IT-focused, especially as IT teams are being asked to do more with fewer resources and being put under increasing strain to support companies’ appetites for all things relating to AI. But AI also has a big role to play in making networks more manageable. As network management becomes more automated and networks become self-healing, network engineers will need to learn how to integrate the latest tooling with agentic technology to provide the data stream for AI-powered network management. Read more about AI in network management Agentic AI ushers in a new era of network management: Agentic AI will redefine network management. But IT execs have to understand the technology’s benefits – and its drawbacks. AI-driven self-healing networks bring new capabilities: Self-healing networks use AI to continuously monitor, diagnose and fix issues autonomously, shifting IT from reactive troubleshooting to proactive management.

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That could potentially undermine business transformation and erode productivity gains.

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Punggol Digital District will test whether Singapore can turn Physical AI pilots into scalable rules for cities, workers and industry.

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In AI-driven transformation, the real risk isn't the technology itself—it's leaders staying silent or vague at the exact moment employees need clarity, context and trust the most.

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