Researchers at MIT’s Computer Science and AI Lab (CSAIL) are collaborating with Adobe to create Refashion, a new AI-driven design tool promoting sustainable fashion. The software deconstructs clothing into modules, allowing designers and consumers to reimagine garments for reuse or transformation.
Users can utilise the AI to sketch shapes and combine elements to create adaptable pieces, such as a skirt that transforms into a dress or maternity wear that evolves throughout pregnancy. The system provides blueprints for flexible, reconfigurable designs that reduce waste.
Lead researcher Rebecca Lin said the project encourages reuse from the outset, contrasting with the disposable nature of fast fashion. By making clothing easy to resize, repair and restyle, Refashion aims to extend each item’s lifespan and reduce environmental impact.
MIT Professor Erik Demaine described Refashion as a bridge between computation, art and design, envisioning it as a tool that makes creative fashion accessible while embedding sustainability into every stage of garment creation.
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Lambda has announced a multibillion-euro agreement with Microsoft to expand AI infrastructure powered by tens of thousands of NVIDIA GPUs, marking one of the largest private cloud computing collaborations to date.
The multi-year deal aims to accelerate the deployment of AI supercomputers at scale, enhancing the capacity for enterprise and research applications across industries.
A collaboration that builds on an eight-year relationship between the two companies and reflects growing global demand for high-performance computing driven by the rise of AI assistants and enterprise AI solutions.
Stephen Balaban, CEO of Lambda, said the project represents a major step in developing gigawatt-scale AI factories capable of serving billions of users. The company positions itself as a trusted large-scale partner for organisations building advanced AI models and systems.
Founded in 2012, Lambda designs supercomputing infrastructure for AI training and inference, aiming to make computing power as accessible as electricity and to advance what it calls the era of ‘superintelligence’.
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The European Commission has unveiled RAISE, a new virtual institute designed to unite Europe’s AI research and accelerate scientific breakthroughs.
The launch, announced in Copenhagen, marks a flagship moment in the EU’s strategy to strengthen its leadership in science and technology through collective action.
Funded with €107 million under Horizon Europe, RAISE will bring together Europe’s best resources in data, computing power, and research talent.
An initiative that will help scientists apply AI to pressing challenges such as cancer treatment, climate change, and natural disaster prediction, while promoting innovation that serves humanity instead of commercial interests alone.
RAISE will work with the EuroHPC Joint Undertaking to secure access to AI Gigafactories and will dedicate €75 million to train and attract global researchers through Networks of Excellence.
The Commission also plans to double Horizon Europe’s annual AI investments to more than €3 billion, ensuring that the EU remains a global leader in scientific AI.
A project that reflects the EU’s ambition to achieve technological sovereignty and create an inclusive AI ecosystem. As RAISE grows in phases towards 2034, it will strengthen cooperation among Member States, academia, and industry, setting a benchmark for responsible and innovative AI in science.
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Organisations across public and private sectors are using Salesforce’s Agentforce to engage people whenever and wherever they need support.
From local governments to hospitals and education platforms, AI systems are transforming how services are delivered and accessed.
In the city of Kyle, Texas, an Agentforce-driven 311 app enables residents to report issues such as potholes or water leaks. The city plans to make the system voice-enabled, reducing traditional call volumes while maintaining a steady flow of service requests and faster responses.
At Pearson, AI enables students to access their online learning platforms instantly, regardless of their time zone. The company stated that the technology fosters loyalty by providing immediate assistance, rather than requiring users to wait for human support.
Meanwhile, UChicago Medicine utilises AI to streamline patient interactions, from prescription refills to scheduling, while ambient listening tools enable doctors to focus entirely on patients rather than typing notes.
Salesforce said Agentforce empowers organisations to save resources while enhancing trust, accessibility, and service quality. By meeting people on their own terms, AI enables more responsive and human-centred interactions across various industries.
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Amazon Web Services (AWS) and OpenAI have entered a $38 billion, multi-year partnership that will see OpenAI run and scale its AI workloads on AWS infrastructure. The seven-year deal grants OpenAI access to vast NVIDIA GPU clusters and the capacity to scale to millions of CPUs.
The collaboration aims to meet the growing global demand for computing power driven by rapid advances in generative AI.
OpenAI will immediately begin using AWS compute resources, with all capacity expected to be fully deployed by the end of 2026. The infrastructure will optimise AI performance by clustering NVIDIA GB200 and GB300 GPUs via Amazon EC2 UltraServers for low-latency, large-scale processing.
These clusters will support tasks such as training new models and serving inference for ChatGPT.
OpenAI CEO Sam Altman said the partnership would help scale frontier AI securely and reliably, describing it as a foundation for ‘bringing advanced AI to everyone.’ AWS CEO Matt Garman noted that AWS’s computing power and reliability make it uniquely positioned to support OpenAI’s growing workloads.
The move strengthens an already active collaboration between the two firms. Earlier this year, OpenAI’s models became available on Amazon Bedrock, enabling AWS clients such as Peloton, Thomson Reuters, and Comscore to adopt advanced AI tools.
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Nissan and Monolith have extended their strategic partnership for three years to apply AI across more vehicle programmes in Europe. The collaboration supports Nissan. RE: Nissan Plans to Compress Development Timelines and Improve Operational Efficiency. Early outcomes are guiding a wider rollout.
Engineers at Nissan Technical Centre Europe will utilise Monolith to predict test results based on decades of data and simulations. Reducing prototypes and conducting targeted, high-value experiments enables teams to focus more effectively on design decisions. Ensuring both accuracy and coverage remains essential.
A prior project on chassis bolt joints saw AI recommend optimal torque ranges and prioritise the following best tests for engineers. Compared with the non-AI process, physical testing fell by 17 percent in controlled comparisons. Similar approaches are being prepared for future models beyond LEAF.
Leaders say that a broader deployment could halve testing time across European programmes if comparable gains are achieved. Governance encompasses rigorous validation before changes are deployed to production. Operational benefits include faster iteration cycles and reduced test waste.
Monolith’s toolkit includes next-test recommendation and anomaly detection to flag outliers before rework. Nissan frames the push as an innovation with sustainability benefits, cutting material use while maintaining quality across a complex supply chain. Partners will share results as adoption scales.
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AI summaries can speed learning, but an extensive study finds they often blunt depth and recall. More than 10,000 participants used chatbots or traditional web search to learn assigned topics. Those relying on chatbot digests showed shallower knowledge and offered fewer concrete facts afterwards.
Researchers from Wharton and New Mexico State conducted seven experiments across various tasks, including gardening, health, and scam awareness. Some groups saw the same facts, either as an AI digest or as source links. Advice written after AI use was shorter, less factual, and more similar across users.
Follow-up raters judged AI-derived advice as less informative and less trustworthy. Participants who used AI also reported spending less time with sources. Lower effort during synthesis reduces the mental work that cements understanding.
Findings land amid broader concerns about summary reliability. A BBC-led investigation recently found that major chatbots frequently misrepresented news content in their responses. The evidence suggests that to serves as support for critical reading, rather than a substitute for it.
The practical takeaway for learners and teachers is straightforward. Use AI to scaffold questions, outline queries, and compare viewpoints. Build lasting understanding by reading multiple sources, checking citations, and writing your own synthesis before asking a model to refine it.
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Nearly eight in ten UK secondary teachers say AI has forced a rethink of how assignments are set, a British Council survey finds. Many now design tasks either to deter AI use or to harness it constructively in lessons. Findings reflect rapid cultural and technological shifts across schools.
Approaches are splitting along two paths. Over a third of designers create AI-resistant tasks, while nearly six in ten purposefully integrate AI tools. Younger staff are most likely to adapt; yet, strong majorities across all age groups report changes to their practices.
Perceived impacts remain mixed. Six in ten worry about their communication skills, with some citing narrower vocabulary and weaker writing and comprehension skills. Similar shares report improvements in listening, pronunciation, and confidence, suggesting benefits for speech-focused learning.
Language norms are evolving with digital culture. Most UK teachers now look up slang and online expressions, from ‘rizz’ to ‘delulu’ to ‘six, seven’. Staff are adapting lesson design while seeking guidance and training that keeps pace with students’ online lives.
Long-term views diverge. Some believe AI could lift outcomes, while others remain unconvinced and prefer guardrails to limit misuse. British Council leaders say support should focus on practical classroom integration, teacher development, and clear standards that strike a balance between innovation and academic integrity.
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Deutsche Telekom has joined the Theta Network as a strategic enterprise validator, alongside Google, Samsung and Sony. The company becomes the first major telecom provider to take part in securing the decentralised blockchain platform.
The partnership involves staking THETA tokens and operating validator nodes that support Theta’s layer-1 infrastructure for AI, cloud and media applications. Deutsche Telekom’s unit, T-Systems MMS, will manage the validator operations.
Theta Labs said the collaboration enhances network resilience and underlines growing enterprise interest in decentralised computing. The project’s EdgeCloud system is designed to distribute AI workloads across global nodes more efficiently.
Deutsche Telekom noted that Theta’s decentralised model aligns with its vision of providing reliable, scalable cloud and edge services for future digital ecosystems.
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Judges and employers are confronting a surge in AI-generated mistakes, from fabricated legal citations to inaccurate workplace data. Courts in the United States have already recorded hundreds of flawed filings, raising concerns about unchecked reliance on generative systems.
Experts urge professionals to treat AI as an assistant rather than an authority. Tools can support research and report writing, yet unchecked outputs often contain subtle inaccuracies that could mislead users or damage reputations.
Data scientist Damien Charlotin has identified nearly 500 court documents containing false AI-generated information within months. Even established firms have faced judicial penalties after submitting briefs with non-existent case references, underlining growing professional risks.
Workplace advisers recommend verifying AI results, protecting confidential information, and obtaining consent when using digital notetakers. Training and prompt literacy are becoming essential skills as AI tools continue shaping daily operations across industries.
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