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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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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CISA’s warning serves as a reminder that ransomware is not confined to Windows. A Linux kernel flaw, CVE-2024-1086, is being exploited in real-world incidents, and federal networks face a November 20 patch-or-disable deadline. Businesses should read it as their cue, too.
Attackers who reach a vulnerable host can escalate privileges to root, bypass defences, and deploy malware. Many older kernels remain in circulation even though upstream fixes were shipped in January 2024, creating a soft target when paired with phishing and lateral movement.
Practical steps matter more than labels. Patch affected kernels where possible, isolate any components that cannot be updated, and verify the running versions against vendor advisories and the NIST catalogue. Treat emergency changes as production work, with change logs and checks.
Resilience buys time when updates lag. Enforce least privilege, require MFA for admin entry points, and segment crown-jewel services. Tune EDR to spot privilege-escalation behaviour and suspicious modules, then rehearse restores from offline, immutable backups.
Security habits shape outcomes as much as CVEs. Teams that patch quickly, validate fixes, and document closure shrink the blast radius. Teams that defer kernel maintenance invite repeat visits, turning a known bug into an avoidable outage.
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Researchers at the University of Surrey have developed a new method to enhance AI by imitating how the human brain connects information. The approach, called Topographical Sparse Mapping, links each artificial neuron only to nearby or related ones, replicating the brain’s efficient organisation.
According to findings published in Neurocomputing, the structure reduces redundant connections and improves performance without compromising accuracy. Senior lecturer Dr Roman Bauer said intelligent systems can now be designed to consume less energy while maintaining power.
Training large models today often requires over a million kilowatt-hours of electricity, a trend he described as unsustainable.
An advanced version, Enhanced Topographical Sparse Mapping, introduces a biologically inspired pruning process that refines neural connections during training, similar to how the brain learns.
Researchers believe that the system could contribute to more realistic neuromorphic computers, which simulate brain functions to process data more efficiently.
The Surrey team said that such a discovery may advance generative AI systems and pave the way for sustainable large-scale model training. Their work highlights how lessons from biology can shape the next generation of energy-efficient computing.
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Europe raised €13.7bn across just over 1,300 rounds in Q3, the strongest quarter since Q2 2024. September alone brought €8.7bn. July and August reflected the familiar summer slowdown.
Growth equity provided €7bn, or 51.6% of the total, with two consecutive quarters surpassing 150 growth rounds. Data centres, AI agents, and GenAI led the activity, with more AI startups scaling with larger cheques.
Early-stage totals were the lowest in 12 months, yet they were ahead of Q3 last year. Lovable’s $200 million Series A at a $1.8 billion valuation stood out. Seven new unicorns included Nscale, Fuse Energy, Framer, IQM, Nothing, and Tide.
ASML led the quarter’s largest deal, investing €1.3bn in Mistral AI’s €1.7bn Series C. France tallied €2.7 billion, heavily concentrated in Mistral, while the UK reached €4.49 billion. Germany followed with just over €1.5bn, ahead of the Netherlands and Switzerland.
AI-native funding surpassed all verticals for the first time on record, reaching €3.9 billion, with deeptech at €2.6 billion. Agentic AI logged 129 rounds, sharply higher year-over-year, while data centres edged out agents for capital. Defence and dual-use technology attracted €2.1 billion across 44 rounds.
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Europe’s 8th Cybersecurity Forum in Brussels brought together more than 200 officials and operators from energy, cybersecurity and technology to discuss how to protect the bloc’s increasingly digital, decentralised grids. ENISA said strengthening energy infrastructure security is urgent as geopolitics and digitalisation raise risk.
Discussions focused on turning new EU frameworks into real-world protection: the Cyber Resilience Act placing board-level responsibility for security, the NIS2 Directive updating obligations across critical sectors, and the Network Code on Cybersecurity setting common rules for cross-border electricity flows. Speakers pressed for faster implementation, better public-private cooperation and stronger supply-chain security.
Case studies highlighted live threats. Ukraine’s National Cybersecurity Coordination Center warned of the growing threat of hybrid warfare, citing repeated Russian cyberattacks on its power grid dating back to 2015. ENCS demonstrated how insecure consumer-energy devices like EV chargers, PV inverters, and home batteries can be easily exploited when security-by-design measures are absent.
Organisers closed with a call to standardise best practice, improve information sharing and coordinate operators, regulators and suppliers. As DG Energy’s Michaela Kollau noted, the resilience of Europe’s grids depends on a shared commitment to implementing current legislation and sector cybersecurity measures.
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Anthropic and AWS switched on Project Rainier, a vast Trainium2 cluster spanning multiple US sites to accelerate Claude’s evolution.
Project Rainier is now fully operational, less than a year after its announcement. AWS engineered an EC2 UltraCluster of Trainium2 UltraServers to deliver massive training capacity. Anthropic says it offers more than five times the compute used for prior Claude models.
UltraServers bind four Trainium2 servers with high-speed NeuronLinks so 64 chips act as one. Tens of thousands of networks are connected through Elastic Fabric Adapter across buildings. The design reduces latency within racks while preserving flexible scale across data centres.
Anthropic is already training and serving Claude on Rainier across the US and plans to exceed one million Trainium2 chips by year’s end. More computing should raise model accuracy, speed evaluations, and shorten iteration cycles for new frontier releases.
AWS controls the stack from chip to data centre for reliability and efficiency. Teams tune power delivery, cooling, and software orchestration. New sites add water-wise cooling, contributing to the company’s renewable energy and net-zero goals.
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Foxconn will add humanoid robots to a new Houston plant building Nvidia AI servers from early 2026. Announced at Nvidia’s developer conference, the move deepens their partnership and positions the site as a US showcase for AI-driven manufacturing.
Humanoid systems based on Nvidia’s Isaac GR00T N are built to perceive parts, adapt on the line, and work with people. Unlike fixed industrial arms, they handle delicate assembly and switch tasks via software updates. Goals include flexible throughput, faster retooling, and fewer stoppages.
AI models are trained in simulation using digital twins and reinforcement learning to improve accuracy and safety. On the line, robots self-tune as analytics predict maintenance and balance workloads, unlocking gains across logistics, assembly, testing, and quality control.
Texas, US, offers proximity to a growing semiconductor and AI cluster, as well as policy support for domestic capacity. Foxconn also plans expansions in Wisconsin and California to meet global demand for AI servers. Scaling output should ease supply pressures around Nvidia-class compute in data centres.
Job roles will shift as routine tasks automate and oversight becomes data-driven. Human workers focus on design, line configuration, and AI supervision, with safety gates for collaboration. Analysts see a template for Industry 4.0 factories running near-continuously with rapid changeovers.
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Nokia and NVIDIA have announced a $1 billion partnership to develop an AI-powered platform that will drive the transition from 5G to 6G networks.
The collaboration will create next-generation AI-RAN systems, combining computing, sensing and connectivity to transform how the US mobile networks process data and deliver services.
However, this partnership marks a strategic step in both companies’ ambition to regain global leadership in telecommunications.
By integrating NVIDIA’s new Aerial RAN Computer and Nokia’s AI-RAN software, operators can upgrade existing networks through software updates instead of complete infrastructure replacements.
T-Mobile US will begin field tests in 2026, supported by Dell’s PowerEdge servers.
NVIDIA’s investment and collaboration with Nokia aim to strengthen the foundation for AI-native networks that can handle the rising demand from agentic, generative and physical AI applications.
These networks are expected to support future 6G use cases, including drones, autonomous vehicles and advanced augmented reality systems.
Both companies see AI-RAN as the next evolution of wireless connectivity, uniting data processing and communication at the edge for greater performance, energy efficiency and innovation.
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Plans are being rolled out for a €1 billion data centre in Germany to bolster Europe’s AI infrastructure, with Nvidia and Deutsche Telekom set to co-fund the project.
The facility is expected to serve enterprise customers, including SAP SE, Europe’s largest software company, and to deploy around 10,000 advanced chips known as graphics processing units (GPUs).
While significant for Europe, the build is modest compared with gigawatt-scale sites elsewhere, highlighting the region’s push to catch up with US and Chinese capacity.
An announcement is anticipated next month in Berlin alongside senior industry and government figures, with Munich identified as the planned location.
The move aligns with the EU efforts to expand AI compute, including the €200 billion initiative announced in February to grow capacity over the next five to seven years.
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