Bull

Pricing changes faster than it is possible to manage manually. Demand shifts, competitors move, seasons turn - and across thousands of products in multiple markets, spreadsheets stop keeping up. AI Dynamic Pricing addresses that problem directly: it sets the right price in real time, using machine learning to model how demand actually responds to price. AI Dynamic Pricing is purpose-built to move beyond traditional pricing methods. By modelling demand elasticity, seasonality and product relationships, it helps companies optimise every price, every day: improving margins, streamlining pricing workflows and reducing operational risk. Covering the full pricing lifecycle, from data ingestion and modelling to deployment of recommendations into production systems, AI Dynamic Pricing enables organisations to scale AI pricing reliably, with full governance. Swipe through to see the results a major European pharmacy chain achieved 👉

Growing AI adoption relies on massive data flows, driving demand for network infrastructure capable of moving ever-growing volumes of data efficiently, at scale. That's why Bull and Kalray are partnering to develop the networking technologies for AI and HPC infrastructures.   The collaboration will help evolve BXI, Bull's network technology, towards full Ultra Ethernet compatibility - the open standard now adopted across the AI cloud infrastructure - while preserving the ultra-low latency and advanced congestion management that advanced computing depends on.   Built on European IP, the partnership also aims to strengthen technological sovereignty by securing critical value chains and offering an alternative to non-European technologies.   The result: a more sovereign and unique approach in the market to deliver performance, scalability and openness required by tomorrow's AI Gigafactories, data centres and supercomputers, without compromise.   #HPC #SovereignAI #AIInfrastructure #BullAIDestiny

À mesure que l’IA se déploie à grande échelle, les besoins en infrastructures réseau explosent : plus de données à transporter, plus vite, plus efficacement et à moindre coût.   C’est précisément dans cet objectif que Bull et Kalray s’associent : développer les technologies réseau qui équiperont les infrastructures IA et HPC de demain.   Cette collaboration contribuera à faire évoluer BXI, la technologie réseau de Bull, vers une compatibilité totale avec Ultra Ethernet – le standard ouvert désormais largement adopté dans l’écosystème des infrastructures cloud pour l’IA – tout en préservant l’ultra-faible latence et les mécanismes avancés de gestion de la congestion, deux caractéristiques indispensables au calcul intensif.   S’appuyant sur des technologies conçues en Europe, ce partenariat vise également à renforcer la souveraineté technologique en sécurisant les chaînes de valeur critiques et en proposant une alternative à des technologies non européennes.   Résultat : une approche plus souveraine et unique sur le marché, combinant performance, évolutivité et ouverture pour répondre aux besoins des futures AI Gigafactories, des centres de données et des supercalculateurs, sans compromis. #HPC #SovereignAI #AIInfrastructure #BullAIDestiny

A few days on from AMD Advancing AI in San Francisco, and we're still thinking about the conversations. 🤝 Being an Innovator Sponsor of the event meant a week of standing shoulder to shoulder with the people building the next wave of advanced AI infrastructure – during executive keynotes led by CEO Dr. Lisa Su, technical breakout sessions, developer workshops and partner showcases. Dr. Lisa Su's keynote set out a vision of AI infrastructure built around balanced systems, where compute, networking, memory and energy efficiency are designed to work together rather than scaled independently. Helios, AMD's new rack-scale platform, sat at the heart of it. This week, we're proud to announce we're bringing AMD Helios™ rack-scale AI systems to Europe, expanding what's possible for cloud providers, NeoClouds and the next generation of European AI infrastructure. Helios will be deployed at CINES, with GENCI, in preparation for the Alice Recoque exascale project. Thank you to everyone who stopped by the booth, and to the AMD team for bringing this ecosystem together. #AdvancingAI Bruno Lecointe Prashant Sharma Cristina White David Giorgi

A major bank ran an AI pilot that worked flawlessly: speech-to-text and LLMs monitoring call-centre compliance across thousands of agents. ...and when they calculated the cost of scaling their AI solution in the cloud, their "eyes almost fell out."👁️ That's a wall a lot of enterprises are hitting now: the pilot proves the value and then the cloud cost estimate makes scaling almost impossible.  Petr Bednarik, Enterprise AI Global Lead at Bull, joins host Kevin Jackson on the episode of the Scaling Intelligence podcast to dig into how this played out, amongst other topics like national AI factories, hybrid sovereignty, and the full-stack thinking behind them. Link to the full episode in the comments. 👇 #BullAIDestiny #SovereignAI #EnterpriseAI Intersect360 Research

⚡Demand for high-performance computing keeps growing, and so does the question that comes with it: can machines this powerful genuinely be made eco-responsible? The energy footprint of a supercomputer isn't decided by its hardware alone - it's also determined by how the infrastructure is designed, how resources are actually used, and how efficiently the code runs on it. ♻️Each of these aspects has real impact: capturing heat directly at the components – in our case, with an equivalent of a glass of water per compute blade - turns it from waste into a resource that can even warm homes. Measuring in detail where and when energy is consumed exposes waste that would otherwise stay invisible. Finally, optimising a simulation to run four times faster cuts energy consumption with no new hardware involved. So, can supercomputers be eco-responsible? We believe they can, when sustainability is applied as a discipline across the entire lifecycle and across all layers, from components to code. More on this in the first part of a two-part article, linked in the comments. 👇 #BullAIDestiny #HPC #SustainableAI #Exascale

❔ How can Europe strengthen its technological sovereignty in the age of Quantum, AI, and critical technologies? At Bull, we believe that the future lies in the convergence of quantum computing, HPC, and AI and in building the partnerships and ecosystems needed to transform innovation into real-world industrial value. The same belief was reflected in the discussion “France and Bavaria/Germany Shaping Europe’s Sovereignty” at the Servus Scale Up Festival, organised by La French Tech Munich, where Matthias Schempp, Executive Board Member of science+computing AG, represented Bull.   Key topics of the discussion: 🔹 Building a strong European quantum ecosystem through cross-border collaboration 🔹 Enhancing Europe’s competitiveness in critical technologies including quantum computing 🔹 Turning scientific excellence into industrial impact and scalable innovation   One key takeaway from the discussion was that European sovereignty is about more than quantum hardware alone. It requires a strong and connected ecosystem that combines quantum technologies, HPC, AI, software platforms, infrastructure, industrial expertise, and talent. Thank you to La French Tech Munich, the organizers of Servus Scale Up, our fellow panelists, and all participants for an insightful exchange on Europe’s technological future. Julia Bauer from Fraunhofer-Gesellschaft Dr Laurent G. from ColibriTD Christopher Trummer from TUM Venture Labs Matthias Schempp from Bull #QuantumComputing #AI #HPC #EuropeanInnovation #DigitalSovereignty

[1/8💡] Raw performance is no longer the only metric of success. Read more on eight trends shaping HPC in 2026 from Bruno Lecointe, our HPC, AI and Quantum SVP.  🖇️ Link to the full article in the comments

AI at scale brings compute and infrastructure into the same conversation. The best accelerators deliver when the infrastructure around them keeps things running efficiently, securely, and at the scale that research, enterprise and public sector workloads actually demand. It’s the part of our expertise that we are bringing to AMD Advancing AI in San Francisco this July, where we’re proud to join the conversation as an Innovator Sponsor and AMD partner. Register for AMD Advancing AI at https://lnkd.in/g2uSyBdm

Error management is one of the most fundamental challenges in quantum computing.   Every quantum calculation is affected by noise and errors. The entire future of quantum computing depends on our ability to detect, understand and correct them.   In this article, our researchers introduce the Pauli Frame Sparse Representation (PFSR), a new method for estimating logical error thresholds more accurately and evaluating quantum systems under more realistic conditions.   👉 A step toward more reliable quantum computing. Link in the comments.