Cloud computing

Canada-EU digital partnership expands cooperation on AI and security

The European Union and Canada have strengthened their digital partnership during the first Digital Partnership Council in Montreal. Both sides outlined a joint plan to enhance competitiveness and innovation, while supporting smaller firms through targeted regulation.

Senior representatives reconfirmed that cooperation with like-minded partners will be essential for economic resilience.

A new Memorandum of Understanding on AI placed a strong emphasis on trustworthy systems, shared standards and wider adoption across strategic sectors.

The two partners will exchange best practices to support sectors such as healthcare, manufacturing, energy, culture and public services.

They also agreed to collaborate on large-scale AI infrastructures and access to computing capacity, while encouraging scientific collaboration on advanced AI models and climate-related research.

A meeting that also led to an agreement on a structured dialogue on data spaces.

A second Memorandum of Understanding covered digital credentials and trust services. The plan includes joint testing of digital identity wallets, pilot projects and new use cases aimed at interoperability.

The EU and Canada also intend to work more closely on the protection of independent media, the promotion of reliable information online and the management of risks created by generative AI.

Both sides underlined their commitment to secure connectivity, with cooperation on 5G, subsea cables and potential new Arctic routes to strengthen global network resilience. Further plans aim to deepen collaboration on quantum technologies, semiconductors and high-performance computing.

A renewed partnership that reflects a shared commitment to resilient supply chains and secure cloud infrastructure as both regions prepare for future technological demands.

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EU partners with EIB to support AI gigafactories

The European Commission and the European Investment Bank Group (EIB) have signed a memorandum of understanding to support the development of AI Gigafactories across the EU. The partnership aims to position Europe as a leading AI hub by accelerating financing and the construction of large-scale AI facilities.

The agreement establishes a framework to guide consortia responding to the Commission’s informal Call for Expression of Interest. EIB advisory support will help turn proposals into bankable projects for the 2026 AI Gigafactory call, with possible co-financing.

The initiative builds on InvestAI, announced in February 2025, mobilising €20 billion to support up to five AI Gigafactories. These facilities will boost Europe’s computing infrastructure, reinforce technological sovereignty, and drive innovation across the continent.

By translating Europe’s AI ambitions into concrete, large-scale projects, the Commission and the EIB aim to position the EU as a global leader in next-generation AI, while fostering investment and industrial growth.

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Google launches Workspace Studio for AI-powered automation

Google has made Workspace Studio generally available, allowing employees to design, manage, and share AI agents directly within Workspace. Powered by Gemini 3, these agents automate tasks ranging from simple routines to complex business workflows, all without coding.

The platform aims to save time on repetitive work, freeing employees to focus on higher-value activities.

Agents can understand context, reason through problems, and integrate with core Workspace apps such as Gmail, Drive, and Chat, as well as enterprise platforms like Asana, Jira, Mailchimp, and Salesforce.

Early adopters, including cleaning solutions leader Kärcher, have utilised Workspace Studio to streamline workflows, reducing planning time by up to 90% and consolidating multiple tasks into a single minute.

Workspace Studio allows users to build agents using templates or natural language prompts, making automation accessible to non-specialists. Agents can manage status reports, reminders, email triage, and critical tasks, such as legal notices or travel requests.

Teams can also easily share agents, ensuring collaboration and consistency across workflows.

The rollout to business customers will continue over the coming weeks. Users can start creating agents immediately, explore templates, use prompts for automations, and join the Gemini Alpha program to test early features and controls.

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SAP elevates customer support with proactive AI systems

AI has pushed customer support into a new era, where anticipation replaces reaction. SAP has built a proactive model that predicts issues, prevents failures and keeps critical systems running smoothly instead of relying on queues and manual intervention.

Major sales events, such as Cyber Week and Singles Day, demonstrated the impact of this shift, with uninterrupted service and significant growth in transaction volumes and order numbers.

Self-service now resolves most issues before they reach an engineer, as structured knowledge supports AI agents that respond instantly with a confidence level that matches human performance.

Tools such as the Auto Response Agent and Incident Solution Matching enable customers to retrieve solutions without having to search through lengthy documentation.

SAP has also prepared organisations scaling AI by offering support systems tailored for early deployment.

Engineers have benefited from AI as much as customers. Routine tasks are handled automatically, allowing experts to focus on problems that demand insight instead of administration.

Language optimisation, routing suggestions, and automatic error categorisation support faster and more accurate resolutions. SAP validates every AI tool internally before release, which it views as a safeguard for responsible adoption.

The company maintains that AI will augment staff rather than replace them. Creative and analytical work becomes increasingly important as automation handles repetitive tasks, and new roles emerge in areas such as AI training and data stewardship.

SAP argues that progress relies on a balanced relationship between human judgement and machine intelligence, strengthened by partnerships that turn enterprise data into measurable outcomes.

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ChatGPT users gain Jira and Confluence access through Atlassian’s MCP connector

Atlassian has launched a new connector that lets ChatGPT users access Jira and Confluence data via the Model Context Protocol. The company said the Rovo MCP Connector supports task summarisation, issue creation and workflow automation directly inside ChatGPT.

Atlassian noted rising demand for integrations beyond its initial beta ecosystem. Users in Europe and elsewhere can now draw on Jira and Confluence data without switching interfaces, while partners such as Figma and HubSpot continue to expand the MCP network.

Engineering, marketing and service teams can request summaries, monitor task progress and generate issues from within ChatGPT. Users can also automate multi-step actions, including bulk updates. Jira write-back support enables changes to be pushed directly into project workflows.

Security updates sit alongside the connector release. Atlassian said the Rovo MCP Server uses OAuth authentication and respects existing permissions across Jira and Confluence spaces. Administrators can also enforce an allowlist to control which clients may connect.

Atlassian frames the initiative as part of its long-term focus on open collaboration. The company said the connector reflects demand for tools that unify context, search and automation, positioning the MCP approach as a flexible extension of existing team practices.

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Serbia sees wider coverage as Yettel activates 5G

Yettel has launched its 5G network in Serbia, offering higher speeds, lower latency, and support for large numbers of connected devices. Customers need a 5G-ready handset and coverage access, which currently spans major cities and tourist areas. The operator plans wider expansion as deployment progresses.

The service uses recently acquired spectrum, with 5G delivered across the 700 MHz low band and the 3.5 GHz mid band. The frequencies support stronger indoor reach and higher-capacity performance. Yettel says the combination will improve everyday mobile connectivity and enable new digital services.

Use cases include faster downloads, smoother streaming, and more responsive cloud-based gaming. Lower latency will also support remote work and IoT applications. The company expects the network to underpin emerging services that rely on real-time communication and consistent mobile performance.

Yettel forms part of the e& PPF Telecom Group and operates more than 130 retail locations alongside its digital channels. The company says the 5G rollout complements ongoing efforts to modernise national infrastructure. It also aims to maintain strong service quality across urban and regional areas.

The network received the umlaut ‘Best in Test’ award in 2025, marking a ninth consecutive national win. Yettel frames 5G as the next stage of its technological development. The operator expects the upgrade to strengthen the broader digital ecosystem of Serbia and improve long-term connectivity options.

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Mistral AI unveils new open models with broader capabilities

Yesterday, Mistral AI introduced Mistral 3 as a new generation of open multimodal and multilingual models that aim to support developers and enterprises through broader access and improved efficiency.

The company presented both small dense models and a new mixture-of-experts system called Mistral Large 3, offering open-weight releases to encourage wider adoption across different sectors.

Developers are encouraged to build on models in compressed formats that reduce deployment costs, rather than relying on heavier, closed solutions.

The organisation highlighted that Large 3 was trained with extensive resources on NVIDIA hardware to improve performance in multilingual communication, image understanding and general instruction tasks.

Mistral AI underlined its cooperation with NVIDIA, Red Hat and vLLM to deliver faster inference and easier deployment, providing optimised support for data centres along with options suited for edge computing.

A partnership that introduced lower-precision execution and improved kernels to increase throughput for frontier-scale workloads.

Attention was also given to the Ministral 3 series, which includes models designed for local or edge settings in three sizes. Each version supports image understanding and multilingual tasks, with instruction and reasoning variants that aim to strike a balance between accuracy and cost efficiency.

Moreover, the company stated that these models produce fewer tokens in real-world use cases, rather than generating unnecessarily long outputs, a choice that aims to reduce operational burdens for enterprises.

Mistral AI continued by noting that all releases will be available through major platforms and cloud partners, offering both standard and custom training services. Organisations that require specialised performance are invited to adapt the models to domain-specific needs under the Apache 2.0 licence.

The company emphasised a long-term commitment to open development and encouraged developers to explore and customise the models to support new applications across different industries.

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NVIDIA platform lifts leading MoE models

Frontier developers are adopting a mixture-of-experts architecture as the foundation for their most advanced open-source models. Designers now rely on specialised experts that activate only when needed instead of forcing every parameter to work on each token.

Major models, such as DeepSeek-R1, Kimi K2 Thinking, and Mistral Large 3, rise to the top of the Artificial Analysis leaderboard by utilising this pattern to combine greater capability with lower computational strain.

Scaling the architecture has always been the main obstacle. Expert parallelism requires high-speed memory access and near-instant communication between multiple GPUs, yet traditional systems often create bottlenecks that slow down training and inference.

NVIDIA has shifted toward extreme hardware and software codesign to remove those constraints.

The GB200 NVL72 rack-scale system links seventy-two Blackwell GPUs via fast shared memory and a dense NVLink fabric, enabling experts to exchange information rapidly, rather than relying on slower network layers.

Model developers report significant improvements once they deploy MoE designs on NVL72. Performance leaps of up to ten times have been recorded for frontier systems, improving latency, energy efficiency and the overall cost of running large-scale inference.

Cloud providers integrate the platform to support customers in building agentic workflows and multimodal systems that route tasks between specialised components, rather than duplicating full models for each purpose.

Industry adoption signals a shift toward a future where efficiency and intelligence evolve together. MoE has become the preferred architecture for state-of-the-art reasoning, and NVL72 offers a practical route for enterprises seeking predictable performance gains.

NVIDIA positions its roadmap, including the forthcoming Vera Rubin architecture, as the next step in expanding the scale and capability of frontier AI.

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Regulators question transparency after Mixpanel data leak

Mixpanel is facing criticism after disclosing a security incident with minimal detail, providing only a brief note before the US Thanksgiving weekend. Analysts say the timing and lack of clarity set a poor example for transparency in breach reporting.

OpenAI later confirmed its own exposure, stating that analytics data linked to developer activity had been obtained from Mixpanel’s systems. It stressed that ChatGPT users were not affected and that it had halted its use of the service following the incident.

OpenAI said the stolen information included names, email addresses, coarse location data and browser details, raising concerns about phishing risks. It noted that no advertising identifiers were involved, limiting broader cross-platform tracking.

Security experts say the breach highlights long-standing concerns about analytics companies that collect detailed behavioural and device data across thousands of apps. Mixpanel’s session-replay tools can be sensitive, as they can inadvertently capture private information.

Regulators argue the case shows why analytics providers have become prime targets for attackers. They say that more transparent disclosure from Mixpanel is needed to assess the scale of exposure and the potential impact on companies and end-users.

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SAP expands sovereign cloud vision with EU AI Cloud

SAP introduced the EU AI Cloud as part of a unified plan that aims to support Europe’s digital sovereignty goals.

The offering consolidates SAP’s existing sovereign cloud work under one structure and provides organisations with a way to meet strict regulatory and operational needs, ensuring full EU data residency.

Customers can select deployment options that match their level of required control, ranging from SAP’s European data centres to on-site infrastructure.

SAP is also expanding its partnership with Cohere to integrate advanced multimodal and agentic AI features through Cohere North.

Incorporation into SAP Business Technology Platform enables enterprises with data residency constraints to apply AI within core processes without undermining compliance or performance.

A collaboration that is intended to improve insight generation and decision support across a wide range of industries.

EU AI Cloud is backed by a broad ecosystem that includes Cohere, Mistral AI, OpenAI and other partners whose models and applications can be accessed through SAP BTP.

European enterprises and public bodies gain access to routes for developing and deploying AI tools while maintaining flexibility and sovereignty.

The range of options includes SAP Sovereign Cloud, customer-operated on-site deployments and, where chosen, commercial services on selected hyperscalers with sovereignty controls. The approach also includes Delos Cloud for organisations in Germany that require dedicated public sector safeguards.

SAP positions the initiative as a means to advance AI adoption in Europe, aligning with regional standards on data protection and operational independence.

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