While vision-language models (VLMs) are good at recognising generic object categories (dogs, chairs, etc.), they struggle when asked to point out your specific dog or chair under different conditions.
To remedy this, the researchers framed a fine-tuning regime using video-tracking datasets, where the same object appears in multiple frames.
Crucially, they used pseudo-names (e.g. ‘Charlie’) instead of real object names to prevent the model from relying on memorised label associations. This encourages it to reason about context, scene layout, appearance cues, and relative position, rather than shortcut to category matches.
AI models trained with the method showed a 12% average improvement in personalised localization. In some settings, especially with pseudo-naming, gains reached 21%. Importantly, this enhanced ability did not degrade the model’s overall object recognition performance.
Potential applications include smart home cameras recognising your pet, assistive devices helping visually impaired users find items, robotics, surveillance, and ecological monitoring (e.g. tracking particular animals). The approach helps models better generalise from a few example images rather than needing full retraining for each new object.
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Under this plan, sensor and equipment data from factory floors is captured in real time via Azure IoT and forwarded through Fabric. That data will then feed directly into Oracle SCM workflows.
The goal: more visibility, faster decisions and automated responses, such as triggering maintenance, quality checks or inventory adjustments.
Among the features highlighted are secure, real-time intelligence and data flows from shop floor equipment into enterprise systems, automated business events that respond to changes (e.g. imbalance, faults, demand shifts), standardised best practices with reference architectures and prescriptive guidance for integration and embedded AI assistant capabilities in SCM to augment decision making and resilience.
Oracle frames this as part of its Smart Operations vision, where systems are more connected and responsive by design. Microsoft emphasises that Azure’s edge processing and Fabric’s real-time analytics are critical to turning raw IoT signals into actionable business events.
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The UK outsourcing firm Capita has been fined £14 million after a cyber-attack exposed the personal data of 6.6 million people. Sensitive information, including financial details, home addresses, passport images, and criminal records, was compromised.
Initially, the fine was £45 million, but it was reduced after Capita improved its cybersecurity, supported affected individuals, and engaged with regulators.
A breach that affected 325 of the 600 pension schemes Capita manages, highlighting risks for organisations handling large-scale sensitive data.
The Information Commissioner’s Office (ICO) criticised Capita for failing to secure personal information, emphasising that proper security measures could have prevented the incident.
Experts note that holding companies financially accountable reinforces the importance of data protection and sends a message to the market.
Capita’s CEO said the company has strengthened its cyber defences and remains vigilant to prevent future breaches.
The UK government has advised companies like Capita to prepare contingency plans following a rise in nationally significant cyberattacks, a trend also seen at Co-op, M&S, Harrods, and Jaguar Land Rover earlier in the year.
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The UAE Ministry of Investment and Microsoft signed a Memorandum of Understanding at GITEX Global 2025 to apply AI to investment analytics, financial forecasting, and retail optimisation. The deal aims to strengthen data governance across the investment ecosystem.
Under the MoU, Microsoft will support upskilling through its AI National Skilling Initiative, targeting 100,000 government employees. Training will focus on practical adoption, responsible use, and measurable outcomes, in line with the UAE’s National AI Strategy 2031.
Both parties will promote best practices in data management using Azure services such as Data Catalog and Purview. Workshops and knowledge-sharing sessions with local experts will standardise governance. Strong controls are positioned as the foundation for trustworthy AI at scale.
The agreement was signed by His Excellency Mohammad Alhawi and Amr Kamel. Officials say the collaboration will embed AI agents into workflows while maintaining compliance. Investment teams are expected to gain real-time insights and automation that shorten the time to action.
The partnership supports the ambition to make the UAE a leader in AI-enabled investment. It also signals deeper public–private collaboration on sovereign capabilities. With skills, standards, and use cases in place, the ministry aims to attract capital and accelerate diversification.
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Salesforce and AWS outlined a tighter partnership on agentic AI, citing rapid growth in enterprise agents and usage. They set four pillars for the ‘Agentic Enterprise’: unified data, interoperable agents, modernised contact centres and streamlined procurement via AWS Marketplace.
Data 360 ‘Zero Copy’ accesses Amazon Redshift without duplication, while Data 360 Clean Rooms integrate with AWS Clean Rooms for privacy-preserving collaboration. 1-800Accountant reports agents resolving most routine inquiries so human experts focus on higher-value work.
Agentforce supports open standards such as Model Context Protocol and Agent2Agent to coordinate multi-vendor agents. Pilots link Bedrock-based agents and Slack integrations that surface Quick Suite tools, with Anthropic and Amazon Nova models available inside Salesforce’s trust boundary.
Contact centres extend agentic workflows through Salesforce Contact Center with Amazon Connect, adding voice self-service plus real-time transcription and sentiment. Complex issues hand off to representatives with full context, and Toyota Motor North America plans automation for service tasks.
Procurement scales via AWS Marketplace, where Salesforce surpassed $2bn in lifetime sales across 30 countries. AgentExchange listings provide prebuilt, customisable agents and workflows, helping enterprises adopt agentic AI faster with governance and security intact.
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Most firms are still struggling to turn AI pilots into measurable value, Cisco’s 2025 AI Readiness Index finds. Only 13% are ‘AI-ready’, having scaled deployments with results. The rest face gaps in data, security and governance.
Southeast Asia outperforms the global average at 16% ready. Indonesia reaches 23% and Thailand 21%, ahead of Europe at 11% and the Americas at 14%. Cisco says lower tech debt helps some emerging markets leapfrog.
Infrastructure debt is mounting: limited GPU capacity, fragmented data and constrained networks slow progress. Just 34% say their tech stack can adapt and scale for evolving compute needs. Most remain stuck in pilots.
Adoption plans are ambitious: 83% intend to deploy AI agents, with almost 40% expecting them to support staff within a year. Yet only one in three have change-management programmes, risking stalled workplace integration.
The leaders pair strong digital foundations with clear governance and cybersecurity embedded by design. Cisco urges broader collaboration among industry, government and tech firms, arguing that trust, regulation and investment will determine who monetises AI first.
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AI data centres in Scotland use enough tap water to fill over 27 million half-litre bottles annually, BBC News reports. The number of centres has quadrupled since 2021, with AI growth increasing energy and water use, though it remains a small fraction of the national supply.
Scottish Water urges developers to adopt closed-loop cooling or treated wastewater instead of relying only on mains water. Open-loop systems, still used in many centres, consume vast amounts of water, but closed-loop alternatives can reduce demand, though they may increase energy usage.
Experts warn that AI data centres have a significant carbon footprint as well. Analysis from the University of Glasgow estimates the energy use of Scottish centres could equate to each person in the country driving an extra 145 kilometres per year.
Academic voices have called for greater transparency from tech companies and suggested carbon targets and potential penalties to ensure sustainable growth.
The Scottish government and industry stakeholders are promoting ‘green’ AI development, citing Scotland’s cool climate, renewable energy resources, and local expertise. Developers are urged to balance AI expansion with Scotland’s net zero and resource sustainability goals.
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A new era in data technology is emerging as Starcloud, a member of NVIDIA’s Inception startup program, prepares to send its first AI-driven satellite into orbit next month.
The mission marks the debut of NVIDIA’s H100 GPU in space and represents a decisive step toward the creation of large-scale orbital data centres designed to meet the planet’s soaring demand for AI.
By operating data centres in space, Starcloud aims to cut energy costs by tenfold and significantly reduce carbon emissions. The vacuum of space will serve as a natural cooling system, while constant exposure to solar energy will eliminate the need for batteries or backup power.
According to CEO Philip Johnston, the only environmental cost will come from the launch itself, resulting in substantial carbon savings over the data centre’s lifetime.
Starcloud’s technology could transform how Earth observation data is processed. Instead of transmitting raw information back to the ground, satellites will analyse it in real time, improving responses to wildfires, weather changes, and agricultural needs.
The company plans to run Google’s open AI model Gemma on its satellite and eventually integrate NVIDIA’s next-generation Blackwell GPUs, boosting computing power even further.
Johnston predicts that within a decade, most new data centres will be built in orbit. If achieved, Starcloud’s innovation could mark the beginning of a sustainable digital revolution powered by the stars instead of the grid.
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A new report from the Higher Education Policy Institute warns of an urgent need to improve AI literacy among staff and students in the UK. The study argues that without coordinated investment in training and policy, higher education risks deepening digital divides and losing relevance in an AI-driven world.
British report contributors say universities must move beyond acknowledging AI’s presence and instead adopt structured strategies for skill development. Kate Borthwick adds that both staff and students require ongoing education to manage how AI reshapes teaching, assessment, and research.
The publication highlights growing disparities in access and use of generative AI based on gender, wealth, and academic discipline. In a chapter written by ChatGPT, the report suggests universities create AI advisory teams within research offices and embed AI training into staff development programmes.
Elsewhere, Ant Bagshaw from the Australian Public Policy Institute warns that generative AI could lead to cuts in professional services staff as universities seek financial savings. He acknowledges the transition will be painful but argues that it could drive a more efficient and focused higher education sector.
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The International Organization for Standardization has released a major update to ISO 27701, the global standard for managing privacy compliance programmes. The revised version, published in 2025, separates the Privacy Information Management System (PIMS) from ISO 27001.
The updated standard introduces detailed clauses defining how organisations should establish, implement and continually improve their PIMS. It places strong emphasis on leadership accountability, risk assessment, performance evaluation and continual improvement.
Annex A of the standard sets out new control tables for both data controllers and processors. The update also refines terminology and aligns more closely with the principles of the EU GDPR and UK GDPR, making it suitable for multinational organisations seeking a unified privacy management approach.
Experts say the revised ISO 27701 offers a flexible structure but should not be seen as a substitute for legal compliance. Instead, it provides a foundation for building stronger, auditable privacy frameworks that align global business operations with evolving regulatory standards.
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