AI ambition is easy to describe - using data and models to improve decisions, automate work, accelerate discovery, or create new services. Delivering those outcomes is harder and takes a significant amount of experience to be successful. Training a frontier model, fine-tuning an industry model, running high-volume inference and supporting agentic AI place different demands on infrastructure, processes and people. Implementing AI may include a single-purpose turnkey configuration that will accommodate one line of business, or the business may demand a more strategic approach to capitalize on the economies of scale and create AI as a multi-tenant service, designed to accommodate the multitude of mainstream business requirements. That is the value of an AI factory, bringing the complete AI lifecycle together so a cost-effective infrastructure can be designed around the mission, scaled with demand, secured as needed and operated as a dependable source of intelligence. The AI factory is designed to deliver the capacity, performance, utilization and business value customers expect. From AI workload to business outcome An AI factory is an integrated solution for data ingestion, model development, training, fine-tuning, inference, monitoring and continuous improvement. Its purpose is to turn data into intelligence repeatedly and efficiently—whether that intelligence supports a clinician, an engineer, a researcher, a public service or an enterprise application. Achieving that goal requires more than choosing an accelerated processor. Compute must match the business model and expected workloads. Networking and data pipelines must keep accelerators supplied. Storage must support the volume and velocity of data. Software must provision resources and orchestrate jobs. Security, governance and multi-tenancy must reflect who will use the environment and what data they can access. Power and cooling must support the system’s density today and as it grows. “Without proper architecture, governance and operational expertise, organizations can't safely leverage their data, take AI into core processes, or turn innovation into durable competitive advantage,” says Thierry Pienaar, HPE Fellow, Vice President and CTO for HPC and AI Sales. “Customers are realizing the fact that to derive value to its utmost extent they need an end-to-end infrastructure that's purpose-designed and purpose-built for AI.” Choice starts with the workload The HPE AI Factory with NVIDIA portfolio brings together NVIDIA accelerated computing, networking and AI software with HPE infrastructure, software, services and expertise at deploying complex systems. Rather than forcing every customer into a single configuration, the portfolio provides three paths for different ambitions, operating models and requirements. ● HPE Private Cloud AI, the turnkey AI factory solution, is an enterprise-ready, on-premises AI platform for running fine tuning, RAG & inferencing workload environments that need up to 256 GPUs. ● HPE AI Factory at-scale supports model builders, service providers and large enterprises that operate across many users, workloads and GPU resources (using 100s to 10s of thousands of GPUs) with centralized control, operational visibility, and multi-tenancy over the entire AI lifecycle ● HPE Sovereign AI Factory is an HPE AI factory at-scale that adds a deep level of operational control, data security and residency, sovereign management (including optional air-gapped configurations), and built-in compliance frameworks. It is designed for large enterprises, and any other organizations with sensitive information that require strict control and compliance across data, infrastructure, models and operations within defined legal, regulatory or geographic boundaries. Each option starts with the same principle: define the workloads and desired outcomes first, then select the right technologies to support them and finally identify the required resources needed to implement such an infrastructure. A hospital deploying clinical assistants will make different choices from a service provider offering GPU capacity, a manufacturer training vision models or a government operating sensitive national workloads. The HPE AI Factory model gives each a way to build for its mission without losing sight of performance, control or future growth – and HPE partners with these organizations to dramatically increase the likelihood of success. Operate the environment as one system As the use of AI expands across an organization, the operational challenges mature. Multiple teams may need different resource profiles, application stacks, service levels and data boundaries. Platform teams need to see utilization, allocate capacity, apply policy and understand consumption without creating a separate infrastructure island for every workload. The management of these differences make time-to-production an increasingly useful way to think about AI infrastructure: How quickly can an organization cost effectively move from investment vision to an operational environment generating useful intelligence? Many enterprises initially try to answer that question by extending their existing IT expertise. But building a DIY production AI environment from individual components requires skill sets that many enterprise IT organizations have never needed or required at this scale. A poorly implemented AI system may technically operate while still failing economically or operationally. GPUs can sit underutilized. Data pipelines can create bottlenecks. Cooling or power constraints can limit operation and/or expansion. Security policies can prevent sensitive data and workloads from being included. Separate less understood management systems can make AI factory infrastructure difficult to operate. That is why the AI factory challenge is fundamentally a strategic, systems integration and operations problem, not simply a stream of hardware purchasing transactions. "The HPE AI Factory with NVIDIA portfolio gives enterprises a range of AI solutions co-developed with NVIDIA, backed by HPE’s engineering expertise and technical capabilities to design an AI factory around their specific needs and optimize it for performance at scale." Pienaar explains. That distinction matters; customers can choose an architecture suited to their current mission and expand it as models, users and operational requirements change. The HPE AI Factory is designed to help operators provision and govern resources, observe infrastructure, track usage and support secure multi-tenant operations. That control helps customers align capacity with workload priorities while keeping the environment easier to manage as it grows. Make sovereignty a design requirement Cloud services, private environments and hybrid approaches can all play important roles in an AI strategy. For organizations with sovereignty requirements, the decision is defined by costs and the level of sovereignty and control they need: where data and models reside, who can administer the environment, which jurisdiction applies, data residency, how policies are enforced and what level of isolation various workloads require. “Sovereign AI tools from HPE and NVIDIA give an enterprise, or even a nation state, complete control over how its AI systems are built, deployed, operated and governed,” says Kaushik Shirhatti, Vice President, AI Factory at NVIDIA. “For some, that means keeping sensitive data in-country. For others, it means controlling who can access systems, where workloads run, how models are governed, and which local laws apply.” HPE and NVIDIA engineer for the complete outcome HPE and NVIDIA co-engineer AI factory solutions to reduce the integration work required to deploy and operate a high efficiency enterprise AI environment. By combining NVIDIA accelerated computing, networking, and AI software with HPE infrastructure, cloud operations, services, and support, the joint solution helps data scientists and developers spend more time building and improving AI applications while platform teams maintain operational production and control. NVIDIA provides accelerated computing platforms, networking, and the NVIDIA AI Enterprise software suite to power modern training, fine-tuning, inference, and agentic workloads. HPE contributes its expertise in enterprise systems engineering, high-performance computing, management and observability software, services, global support, financing, and years of experience in the power and cooling requirements of dense computing environments. Together, the companies can optimize AI computing solutions beyond any single component. The objective is to select the right GPU architecture and system design for the workload, keep accelerators productive with high-speed data movement, provide the software and operational controls teams need, and create a path to scale without unnecessarily redesigning the environment. HPE AI Services support that path from business planning, AI strategy, workload characterization and facility planning through deployment, integration, support and ongoing operations. HPE Financial Services can help with purchasing, accelerated depreciation schedules and lifecycle flexibility. These capabilities help customers make economically sound technology choices in the context of the business outcome, the operating model and the pace at which the environment needs to evolve. Deployment speed matters, but it is not the final measure of success. Customers need to consider workload readiness, model performance, accelerator utilization, developer productivity, governance, availability, economics and the ability to expand. Those measures connect the infrastructure decision to the outcomes the organization set out to achieve. The case for HPE AI Factory with NVIDIA is not that every customer needs the same stack. It is that every customer needs an AI environment intentionally matched to its workloads, data, operating requirements and goals. By combining NVIDIA’s accelerated computing leadership with HPE’s infrastructure, software, services and operating expertise, organizations can choose the right path—and move from AI investment to meaningful business outcomes faster. Recent deployments of the HPE AI Factory with NVIDIA - TELUS Sovereign AI Factory in Canada and the sovereign AI factory at the University of Utah in the US - are helping with overcoming engineering challenges and driving scientific advances. In conclusion, start by identifying the workloads that would benefit from AI, define the relevant data boundaries and residency requirements, estimate the expected scale over a reasonable timeframe, and determine the operating model, resources, and skills needed to support the AI infrastructure. Then work with HPE and NVIDIA to evaluate which path—turnkey, at-scale, or sovereign—best meets those requirements. To learn more visit HPE AI Factory | AI Infrastructure for Enterprises | HPE Sponsored by HPE and NVIDIA

Attackers were poking at a critical Zimbra mail server bug weeks before it was publicly disclosed, and then moved on to steal credentials, raid mailboxes, and take deeper control of compromised systems. Microsoft Threat Intelligence said it tracked exploitation of CVE-2026-73570, an unauthenticated command injection vulnerability in Zimbra Collaboration Suite that gives attackers a potentially easy route into exposed mail servers. No stolen password or unfortunate employee clicking a dodgy link is required. An attacker can send a specially crafted email to a vulnerable internet-facing server and potentially run commands, though Redmond notes the flaw affects only servers running Zimbra's optional SNMP monitoring package with notifications enabled. Zimbra fixed the flaw in version 10.1.20 on July 20, but CVE-2026-73570 wasn't publicly disclosed until August 13. Between July 28 and August 7, Redmond spotted two different scanning tools probing the same part of Zimbra later used in attacks. At first, the activity appears to have focused on finding vulnerable servers and testing the flaw. The attackers used a collection of common network utilities to make vulnerable systems call back to infrastructure they controlled, confirming they could execute commands. Once they found servers that played ball, things got messier. Microsoft's investigation found attackers deploying web shells and reverse shells, escalating their privileges, installing tools for persistent remote access, and running malicious code directly in memory. Some even tidied up after themselves. Microsoft said attackers temporarily changed permissions on public directories to plant web shells, then restored the original settings afterward in an apparent attempt to make their meddling harder to spot. The intruders also explored the wider Zimbra environments they landed in, identifying other mail servers and looking for trusted connections they could use to move between them. In some cases, existing SSH relationships between Zimbra systems gave them a route to neighboring servers. On at least one compromised machine, attackers turned their initial foothold into root access. They then set things up to keep running commands with the highest privileges without needing a password. Mailboxes were, unsurprisingly, also on the shopping list. Microsoft said attackers hunted for Zimbra credentials and authentication secrets that could potentially be used to access user accounts. One malicious tool it uncovered was built specifically to extract service account credentials and pull mailbox information from Zimbra's databases. In another incident, attackers bundled recent mailbox backups into an archive and tried to ship the haul to Azure Blob Storage using Microsoft's own AzCopy utility. Microsoft said it couldn't confirm from the evidence available whether the transfer actually succeeded. The company saw affected organizations across multiple regions and industries, with the attacks ranging from automated exploitation to more deliberate hands-on-keyboard activity. It hasn't attributed the activity to a particular crew. Admins running versions earlier than Zimbra 10.1.20 should update to 10.1.20 or later, while those unable to patch can reduce their exposure by removing the optional SNMP package or disabling SNMP notifications. Attackers, meanwhile, appear to have gotten there early, with Microsoft spotting probes for the flaw more than two weeks before it was publicly disclosed. ®

Orange Jazz Days zet dit weekend in TivoliVredenburg de Nederlandse jazz in volle breedte centraal. Maar wat maakt die jazz eigenlijk zo Nederlands en vooral: waarin zit die vernieuwing?

De zes Egyptische journalisten worden er door autoriteiten van beschuldigd buitenlandse belangen te dienen. Mensenrechtenorganisaties en collega-journalisten roepen op tot onmiddellijke vrijlating van de redactie.

Franse middelbare scholieren demonstreren al een week tegen de slechte staat van het onderwijs in Frankrijk. Steeds meer studenten sluiten zich bij hen aan. Op meerdere plekken loopt het protest uit de hand.

Het Rotterdamse stadsbestuur wil betaald parkeren uitbreiden naar de hele stad om investeringen te bekostigen. De inwoners van de buitenwijken zijn boos, de oppositie ook. Een referendum werd op het laatste moment afgewend. „Rotterdammers worden als melkkoe gebruikt.”

Een 37-jarige man uit de Hoeksche Waard is aangehouden en blijft twee weken langer vastzitten omdat hij wordt verdacht van het verkrachten en drogeren van zijn vriendin. Dat zou meermaals zijn gebeurd, bovendien zou de man dat allemaal hebben gefilmd.

LONDEN (ANP) - Het Internationaal Strafhof (ICC) in Den Haag en verzekeraar Axa hebben hun banden verbroken, meldt de Financial Times (FT). Daarmee bereiden ze zich voor op eventuele Amerikaanse sancties tegen het strafhof. Beide partijen vreesden dat eventuele maatregelen van de VS Axa zouden dwingen de dienstverlening aan het ICC te staken, en dat willen ze voor zijn.

De overeenkomst tussen het ICC en AXA is per 1 oktober beëindigd, meldde het gerechtshof voor onder meer misdaden tegen de menselijkheid en oorlogsmisdaden aan de zakenkrant. Eerder werd bekend dat de instantie is gestopt met software van het Amerikaanse techconcern Microsoft.

Tegen een aantal werknemers van het ICC zijn al Amerikaanse sancties ingesteld, maar buitenlandminister Marco Rubio dreigde het hof helemaal te ontmantelen. De VS, die nooit lid zijn geweest van het ICC, zijn onder president Donald Trump extra fel tegen het hof. Zo is Trump ontstemd over het arrestatiebevel voor de Israëlische premier Benjamin Netanyahu, maar vreest hij ook dat Amerikanen ooit voor het ICC moeten verschijnen.

Agreement expected to end on Thursday after running for 423 days, during which it has been beset by problems

• UK politics live – latest updates

The UK government’s “one in, one out” deal with France, which was supposed to help deter small boat arrivals, is expected to expire on Thursday, government sources have said.

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