Mercedes-Benz reported faster decisions and better on-time delivery at Celosphere 2025. Using Celonis within MO360, it unifies production and logistics data, extending visibility across every order, part, and process.
Order-to-delivery operations use AI copilots to forecast timelines, optimise sequencing, and cut delays. After-sales teams surface bottlenecks in service parts logistics and speed customer responses. Quality management utilises anomaly detection to identify deviations early, preventing them from impacting production output.
Executives say complete data transparency enables teams to act faster and with greater precision across production and supply chains. The approach helps anticipate change and react to market shifts. Hundreds of active users are expanding adoption as data-driven practices scale across the company.
Celonis positions process intelligence as the backbone that makes enterprise AI valuable. Integrated process data and business context create a live operational twin. The goal is moving from visibility to action, unlocking value through targeted fixes and intelligent automation.
Conference sessions highlighted broader momentum for process intelligence and AI in industry. Leaders discussed governance, standards, and measurable outcomes from digital platforms. Mercedes-Benz framed its results as proof that structured data and AI can lift performance at a global scale.
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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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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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Mustafa Suleyman, CEO of Microsoft AI, argues that AI should be built for people, not to replace them. Growing belief in chatbot consciousness risks campaigns for AI rights and a needless struggle over personhood that distracts from human welfare.
Debates over true consciousness miss the urgent issue of convincing imitation. Seemingly conscious AI may speak fluently, recall interactions, claim experiences, and set goals that appear to exhibit agency. Capabilities are close, and the social effects will be real regardless of metaphysics.
People already form attachments to chatbots and seek meaning in conversations. Reports of dependency and talk of ‘AI psychosis‘ show persuasive systems can nudge vulnerable users. Extending moral status to uncertainty, Suleyman argues, would amplify delusions and dilute existing rights.
Norms and design principles are needed across the industry. Products should include engineered interruptions that break the illusion, clear statements of nonhuman status, and guardrails for responsible ‘personalities’. Microsoft AI is exploring approaches that promote offline connection and healthy use.
A positive vision keeps AI empowering without faking inner life. Companions should organise tasks, aid learning, and support collaboration while remaining transparently artificial. The focus remains on safeguarding humans, animals, and the natural world, not on granting rights to persuasive simulations.
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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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A new joint study by the University of Maryland and Microsoft has found that Polish is the most effective language for prompting AI, outperforming 25 others, including English, French, and Chinese.
The researchers tested leading AI models, including OpenAI, Google Gemini, Qwen, Llama, and DeepSeek, by providing identical prompts in 26 languages. Polish achieved an average accuracy of 88 percent, securing first place. English, often seen as the natural choice for AI interaction, came only sixth.
According to the study, Polish proved to be the most precise in issuing commands to AI, despite the fact that far less Polish-language data exists for model training. The Polish Patent Office noted that while humans find the language difficult, AI systems appear to handle it with remarkable ease.
Other high-performing languages included French, Italian, and Spanish, with Chinese ranking among the lowest. The finding challenges the widespread assumption that English dominates AI communication and could reshape future research on multilingual model optimisation.
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NVIDIA and Hyundai Motor Group will build a Blackwell-powered AI factory for autonomous vehicles, smart plants and robotics. The partners will co-develop core physical AI, shifting from tool adoption to capability building across mobility, manufacturing and on-device chips.
The programme targets integrated training, validation and deployment on 50,000 Blackwell GPUs. In parallel, both sides will back the physical AI cluster in South Korea with about $3 billion, creating an NVIDIA AI Technology Center, Hyundai’s Physical AI Application Center and regional data centres.
Hyundai will use NVIDIA DGX for model training, Omniverse and Cosmos on RTX PRO Servers for digital twins and simulation, and DRIVE AGX Thor in vehicles and robots for real-time intelligence. The stack underpins design, testing and deployment at an industrial scale.
Factory digital twins will unify data, enable virtual commissioning and improve predictive maintenance, supporting safer human-robot work. Isaac Sim will validate tasks and ergonomics before line deployment, speeding robot integration and lifting throughput, quality and uptime.
Vehicles will gain evolving features via Nemotron and NeMo, from autonomy to personalised assistants and adaptive comfort. DRIVE AGX Thor with safety-certified DriveOS will power driver assistance and next-generation safety, linking car and factory into one intelligent ecosystem.
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Nvidia and Samsung outlined a semiconductor AI factory that embeds accelerated computing into production. Over 50,000 GPUs will drive digital twins, predictive maintenance, and real-time optimisation. Partners present the project as a template for autonomous fabs.
The alliance spans design and manufacturing. Samsung uses CUDA-X and EDA tools to speed simulation and verification. Integrating cuLitho into OPC reports roughly twentyfold gains in computational lithography at advanced nodes.
Factory planning and logistics run on Omniverse digital twins and RTX PRO servers. Unified analytics support anomaly detection, capacity planning, and flow balancing. Managers expect shorter ramps and smoother changeovers with higher equipment effectiveness.
Robotics and edge AI extend intelligence to the line. Isaac Sim, Cosmos models, and Jetson Thor target safe collaboration, faster task retargeting, and teleoperation. Samsung’s in-house models enable multilingual assistance and on-site decision support.
A decades-long Nvidia–Samsung relationship underpins the effort, from NV1 DRAM to HBM3E and HBM4. Work continues on memory, modules, and foundry services, plus AI-RAN research with networks in South Korea and academia linking factory intelligence with next-gen connectivity.
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