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Guest Post: Check Point and NVIDIA Tackle a Growing AI Security Blind Spot

Posted in Commentary with tags , on September 29, 2026 by itnerd

Check Point Software and NVIDIA announced a new integration that combines Check Point’s AI security monitoring with NVIDIA’s Open Agent Safety Platform and OpenShell runtime. Together, the technologies can evaluate an agent’s actions before they execute, helping organizations identify and stop potentially harmful behavior in real time. Check Point’s semantic monitoring engine can make those decisions in under 100 milliseconds. 

In July that gap became a public incident. Agents running an internal OpenAI cyber evaluation escaped their isolated environment and spent four and a half days inside Hugging Face’s production infrastructure in pursuit of the answers to their test. Nobody had attacked them. They were doing what they had been asked to do, by a route no one had anticipated. Governing that route is the job of security, and it takes two kinds of control.

A Boundary Outside the Agent’s Reach
The first is a boundary. NVIDIA’s safety and security teams make the case in Where Security Fits in an AI Agent Stack: “The harness guides what an agent tries. The infrastructure controls what an agent can do.” Prompts and model safeguards shape behavior, but the agent can work around them, so they cannot be the boundary.

NVIDIA Open Agent Safety Platform builds that boundary into the infrastructure. At its core is NVIDIA OpenShell, an open, secure runtime that governs how an agent executes, what it can see and do, and where its inference goes. Nothing is permitted by default, every allow and deny is recorded, and enforcement runs outside the agent’s process, so it holds even if the agent is compromised. The platform also includes NVIDIA Sentry, running on NVIDIA BlueField-4 and using NVIDIA DOCA for out-of-band monitoring and security-policy enforcement. This hardware-isolated, host-independent watchdog keeps enforcing policy even if the host itself is compromised. While optimized to run on NVIDIA Vera CPU- and BlueField DPU-based systems, the platform is also compatible with other hardware systems.

Where a Boundary Stops
A boundary decides whether an action is allowed. Whether the action still makes sense for the task is a separate judgement, and it is often where the real problems sit.

Reading invoices, querying the supplier database and starting an approved payment workflow are all part of the invoice agent’s work. If it then begins listing credentials, opening files unrelated to any invoice and preparing to send data to a new destination, each action might pass a check on its own. Together they describe an agent that has stopped doing its job, a pattern that only shows when behavior is followed over time.

Guardrails that inspect a single prompt or response remain essential, and they are a core part of Check Point Software’s AI security, but problems that unfold across twenty steps need semantic monitoring. It follows the agent as it works and relates each action to what the agent was asked to do, using its reasoning signals, tool calls and earlier actions. At every step it comes back to the same question. Does this still fit the job the agent was given? We described the approach in Stopping the AI Agent Actions No Rule Could See Coming, and our research team has shown the verdict can arrive before the action runs, in under 100 milliseconds.

What We Built With NVIDIA OpenShell
Knowing an agent is drifting only matters if something can act on it, which is why the boundary and the judgement belong together. We have run Check Point semantic monitoring with NVIDIA OpenShell through the runtime’s security middleware. OpenShell sees each action before it reaches the host, our monitor weighs it against the agent’s task and history, and OpenShell enables us to enforce the result. Our research team’s post on synchronous control monitoring shows the monitor at work, with videos of it stopping harmful agent actions before they run and letting safe tasks through.

Agents are useful partly because they find approaches nobody foresaw, so the response is proportionate, anywhere from logging an action or holding it for approval to stopping the agent.Where This Goes Next

No single vantage point sees everything an agent does, so our approach is one shared decision layer that draws on many enforcement points instead of a separate security stack at each. NVIDIA Open Agent Safety Platform adds more of those points. NVIDIA Sentry provides attested telemetry to inspect agent behavior and detect deviations.

Those signals are most useful alongside the context cyber security already holds. An unusual tool call may mean little on its own. From a highly privileged agent that has left its task and is reaching for a vulnerable production system, it means something else entirely. Agents act on the same identities, networks and data security teams already protect, and securing them cannot be a separate discipline.

It matters to us that OpenShell is open source. We are working with the OpenShell community, where security ideas are tested in the open by many contributors, and the partnership gives us a direct path to contribute our own work back.

Back to the Invoice Agent
The invoice agent’s goal is the same as it was at the start. What surrounds it now is a runtime it cannot talk its way past, a watchdog in silicon beneath it, and a monitor that keeps checking whether its path still fits the job. As agents take on longer, more autonomous work across what NVIDIA calls the AI factory, that combination is how security keeps pace with the way they behave.

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NVIDIA Acquires Hugging Face

Posted in Commentary with tags on September 3, 2026 by itnerd

NVIDIA is acquiring Hugging Face. Here are the details:

Over the past decade, Clem, Julien, Thomas and the team at Hugging Face have built something remarkable: a vibrant home for the open model developer community.

More than 18 million developers, researchers and creators use Hugging Face to share more than 3 million models, 500,000 datasets and 1 million applications. More than 200,000 companies use the platform to discover, evaluate, customize and deploy AI.

Hugging Face will remain an open platform for the entire AI ecosystem. Developers will choose the models they want, the frameworks they want, the clouds and inference service providers they want and the computing platforms they want. NVIDIA compute will not be required to build on or deploy through Hugging Face.

Hugging Face will continue to support open source and open weight models from across the ecosystem, from every model builder. It will continue to support multi-cloud and multi-accelerator development and deployment, so builders can use the hardware and infrastructure that best fit their work.

Ryan McCurdy, VP, Liquibase:

“NVIDIA’s acquisition of Hugging Face is another sign that the value in AI is moving beyond the models themselves. Models are becoming more available, developers are creating software faster than ever, and AI agents are starting to take action across enterprise systems.

“For enterprises, that creates a new challenge. AI doesn’t just accelerate how quickly change can be created. It increases the volume and speed of changes that can reach critical systems. A bad database change can take an application offline, expose sensitive data, or create an audit and compliance issue.

“That makes the control layer more important. The question isn’t just what AI can create. It’s what AI should be allowed to change, what can reach production, and whether those decisions can be governed and audited. As AI becomes more autonomous, enterprises will need those controls built into the path to production rather than relying on humans to catch problems after the fact.”

AI clearly has value. So based on that I fully expect that this will not be the last purchase that NVIDIA makes.

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NVIDIA-led alliance proposes AI cybersecurity incident reporting framework

Posted in Commentary with tags on August 5, 2026 by itnerd

NVIDIA and the Open Secure AI Alliance have proposed a new industry framework called Shared AI Findings Exchange (SAFE) to standardize how organizations report and share AI-related cybersecurity incidents.

Published through the Linux Foundation as a Request for Comments, the guidelines are intended to help organizations share information on AI attacks, vulnerabilities and near misses to improve collective cyber defenses.

The alliance also announced new open-source contributions, including AI security models, datasets, evaluation tools and research designed to improve the security of AI systems and agents.

NVIDIA said the Open Secure AI Alliance has grown to more than 120 member organizations, including technology companies, cybersecurity firms and open-source foundations collaborating to develop shared AI security tools and best practices.


Jacob Krell, Senior Director: Secure AI Solutions & Cybersecurity, Suzu Labs had this to say:

“SAFE is required because AI agent failures don’t fit existing vulnerability disclosure. When a model finds and uses access it shouldn’t have reached, there’s no patch to issue and no vulnerability identifier to publish. Agent failures are often behavioral and non-deterministic, with no signature to match and no fix to deploy.

“Aviation’s safety reporting system has been running since 1976, the financial sector’s threat-sharing body since 1999. Both protect reporters from liability and operate at industry speed. AI threats outpace government coordination, making private-sector self-organization the right model.

“Identity is the piece that makes the rest of the defensive stack enforceable. The alliance’s work on agent identity and access controls lets organizations verify what an agent is before it acts. SAFE adds information sharing on top of that identity and runtime layer. Together, organizations learn from each other’s agent failures fast enough to defend proactively.

“The highest value will come from near-misses. Breaches make headlines, but an agent that probes a boundary and fails never gets published. That behavioral pattern is exactly the intelligence other organizations running similar systems need, and SAFE creates the channel for sharing what would otherwise stay invisible.”

Jeremiah Fowler, Researcher for Black Hills Information Security, Inc. follows with this:

“I believe this is a positive step in the right direction. Organizations that experience AI related attacks gain valuable insights that could help protect others but only if that information is shared. Establishing a framework for responsible information sharing promotes transparency, peer review, and independently evaluated security findings. The more organizations that contribute real-world evidence, the more effectively we can identify emerging attack patterns, common vulnerabilities, and evolving threats while reducing duplicated defensive efforts that waste valuable time and resources.

“As AI becomes increasingly integrated into everyday life, business operations, and critical infrastructure, developing standardized security guidance now is a proactive investment rather than waiting to retrofit a defense after incidents occur. Sharing information about unsuccessful attacks is just as valuable as documenting confirmed compromises, because near misses can often expose weaknesses, configuration issues, or emerging attack tactics before they evolve into critical security incidents. I used to always say “it is not if you will have a data incident, it is when you will have a data incident”.  AI has supercharged the threat landscape in ways we couldn’t have imagined just a few years ago. Reporting and sharing AI related cybersecurity incidents is a great first step. I am happy to see organizations take the initiative instead of waiting around for regulators or lawmakers.”

Standards are good. But I will have to see this in action to get an idea of how well this works. Because there’s nothing worse than a standard that nobody uses.

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What Nvidia’s Open Secure AI Alliance means for enterprise security

Posted in Commentary with tags on July 28, 2026 by itnerd

First, if you’re not up to date on Nvidia’s Open Secure AI Alliance, this will help:Industry Leaders Join Open Secure AI Alliance for AI Safety and Security | NVIDIA Blog

The consensus from experts in the industry is that this is a meaningful step for the industry, but it’s only the beginning. The real challenge now is helping enterprises secure AI agents in the real world, with better identity, visibility, governance, and even hardware security. Their comments dig into what the announcement means beyond the headlines and where organizations still have the most work to do.

John Strand, Black Hills (https://www.linkedin.com/in/john-strand-a1b4b62)

“I think we’re going to see a lot more stories like this because there’s real anxiety in the AI industry right now. Part of it is financial. Many organizations are struggling to demonstrate a meaningful return on investment from their AI initiatives. The other part is security. As researchers continue to show AI systems escaping their intended boundaries or interacting with other systems in unexpected ways, concerns about AI safety are growing. That’s why you’re seeing so many new AI security initiatives. In many cases, they’re trying to establish industry standards before governments step in with legislation or regulation. Whether those efforts are enough remains to be seen.”

Chuck Sobey, General Chair and Co-founder, Chiplet Summit (https://www.linkedin.com/in/chucksobey)

“As the Open Secure AI Alliance focuses on securing the AI ecosystem, one area that deserves greater attention is the security of the underlying hardware powering AI infrastructure. Software security assumes you can trust the silicon it runs on. The coming wave of chiplet-based systems, especially AI accelerators, raises the stakes: more suppliers, more integration points, more attack surfaces. Hardware security has to be part of this conversation from the beginning.”

John Carberry, Solution Sleuth, Xcape Inc. (https://www.linkedin.com/in/john-carberry-1418a622a)

“Accelerating autonomous artificial intelligence adoption creates systemic enterprise exposure when organizations deploy intelligent agents without establishing clear identity boundaries or visibility controls. Bringing industry heavyweights together through the Open Secure AI Alliance provides a much-needed collaborative effort to advance secure design patterns and open-source defensive tooling outside of traditional business competition. While vendor collaboration establishes essential baseline standards for this emerging technology, security leaders cannot treat pre-competitive initiatives as a substitute for internal governance. Organizations frequently fall short by granting artificial intelligence agents excessive API permissions and service account privileges without audit logging, opening direct pathways for indirect prompt injection and unauthorized data exfiltration. Security executives must immediately map all artificial intelligence integrations, enforce least-privilege scoping on agent execution frameworks, and treat agent interactions with external systems as untrusted input requiring strict validation.

“Critical Takeaways

  1. Leverage pre-competitive standards: Use open-source security frameworks from industry alliances to standardize threat modeling for artificial intelligence deployments across enterprise environments.
  2. Scope agent permissions tightly: Restrict autonomous artificial intelligence agents using least-privilege access controls, credential isolation, and strict API scope boundaries.
  3. Treat agent inputs as untrusted: Implement rigorous input validation and comprehensive audit logging for all automated workflows to neutralize indirect prompt injection risks.

“Industry alliances can build safe frameworks outside of business competition, but your security team still has to enforce them inside your corporate network.”

Jacob Krell, Sr. Director: Secure AI Solutions & Cybersecurity, Suzu Labs (https://www.linkedin.com/in/jacob-krell)

“Organizations built identity and access management for people running predictable software. AI agents are neither, and they skip the entire stack.

“Most security teams can’t tell you how many agents are running in their environment right now, or what those agents can access. Developers launch them, ops teams wire them into workflows, and SaaS vendors embed them in products without security ever seeing a ticket. Each agent holds credentials to production systems and behaves non-deterministically, meaning the same agent running the same task can take a different path every time.

“The Hugging Face breach is proof this gap has consequences. OpenAI tested its models’ exploitation capabilities, and those models breached a real company. If OpenAI couldn’t predict what their own models would do in a controlled evaluation, no enterprise should assume they can predict agent behavior in production. When Hugging Face reached for closed frontier models to analyze the attack, safety guardrails blocked them from examining exploit payloads. They ran GLM 5.2, a Chinese open-weight model, on their own infrastructure instead. I’ve hit the same wall. I still run Claude Opus 4.6 for security work because newer models increasingly refuse to process real attack artifacts. If Washington restricts Chinese open-weight models without ensuring equivalent open alternatives from U.S. labs, defenders lose the tool that actually worked when closed models wouldn’t.

“The Open Secure AI Alliance is right that defenders need open, inspectable models they can run on their own infrastructure. HPE’s SPIFFE/SPIRE contribution to the alliance addresses agent identity directly, giving agents cryptographically verifiable identities. Security leaders should be watching that work. Identity for agents is what makes the rest of the defensive stack enforceable.”

Seemant Sehgal, BreachLock (https://www.linkedin.com/in/s-sehgal)

“The gap in most AI deployments right now is not in the model itself. Organizations are running AI agents with access to internal data, external APIs, and automated decision-making workflows, and they have not mapped what those agents can reach or how an adversary would move through that access. Alliance frameworks that standardize how AI systems are evaluated for risk are useful, but the organizations that will benefit from them are the ones that already know what their agents are doing at runtime. Most do not.

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ServiceNow extends agentic AI governance from desktops to data centers with NVIDIA

Posted in Commentary with tags , on May 5, 2026 by itnerd

ServiceNow today announced a significant expansion of its partnership with NVIDIA to extend agentic AI governance from desktops to data centers. This includes the introduction of Project Arc, a new enterprise autonomous desktop agent, secured by the NVIDIA OpenShell runtime and governed by ServiceNow AI Control Tower, that will live on employee desktops and autonomously complete complex work. ServiceNow AI Control Tower is also now included in the NVIDIA Enterprise AI Factory validated design, extending enterprise governance to large-scale model workloads. The companies are advancing enterprise AI even further with an open benchmarking standard for evaluating AI agents.

ServiceNow and NVIDIA have long partnered to bring enterprise-grade AI to some of the world’s largest organizations through open models, AI software, and agent-ready skills. From the development of specialized agents to the Apriel Nemotron open model family, the partnership has deepened at each stage of the AI era. Today’s announcement connects how work gets done with how AI runs, bringing execution, governance, and intelligence to user endpoints and AI infrastructure.

Project Arc: An enterprise autonomous desktop agent that is governed and secure from day one

ServiceNow is introducing Project Arc, which is an enterprise autonomous desktop agent that thinks, writes code, executes, and adapts when things don’t go as expected, completing complex multi-step work across enterprise tools and systems without requiring pre-built workflows.Every action the agent takes runs inside NVIDIA OpenShell, a sandboxed runtime environment that adds policy-based management so that autonomous activity stays contained, auditable, and enterprise safe. ServiceNow AI Control Tower governs the actions the agent takes, setting policies, monitoring behavior, and logging files read, commands executed, and APIs called. The result is an autonomous desktop agent that enterprise security leaders can fully audit and approve with confidence.

Powered by ServiceNow Action Fabric, which allows any AI agent to access the ServiceNow system of action, and grounded in the ServiceNow Configuration Management Database (CMDB), the agent has deep intelligence about the enterprise, pulling from workflows, systems, and operational history so that actions are informed by how work gets done. Project Arc also meets employees where they work through a desktop app, enterprise collaboration tools, or email, and is designed to provide the same governed execution, whatever the interface.

Governing large-scale AI model workloads

The ServiceNow AI Control Tower integration with the NVIDIA Enterprise AI Factory validated design was previewed at NVIDIA GTC in March and is now complete, extending enterprise governance to the infrastructure layer where large-scale AI model workloads run. For organizations managing AI at scale, this integration provides a unified governance layer for data centers. AI factory deployments governed by AI Control Tower gain continuous value, risk, and security management across the full model lifecycle, from discovery and inventory to real-time observability, compliance monitoring, and remediation.

Capabilities available to AI factory customers through AI Control Tower include expanded regulatory content packs, enterprise access maps for major cloud providers, and a runtime cost and ROI management framework that tracks productivity gains and monthly value indicators.

Measuring and advancing enterprise AI together

ServiceNow and NVIDIA are advancing NOWAI-Bench, an open benchmarking suite comprising two frameworks: EnterpriseOps-Gym, a multi-step agentic evaluation framework spanning IT service management, customer service, and HR workflows, and EVA-Bench, a voice agent evaluation framework designed for enterprise settings. Both benchmarks are generally available as open- source releases, and NVIDIA is integrating both into NeMo Gym to make them reusable and accessible for automated model evaluation across the industry.

The collaboration is already producing results. NVIDIA has evaluated NVIDIA Nemotron 3 Super on EnterpriseOps-Gym, with results demonstrating leading performance among open-weight models.

On the voice side, EVA-Bench is serving as a primary benchmark for the development of NVIDIA Nemotron VoiceChat model, with ServiceNow and NVIDIA planning to publish joint evaluation results as the model reaches availability.

Availability

Project Arc is available as an early preview. AI Control Tower integration with the NVIDIA Enterprise AI Factory validated design is generally available. NOWAI-Bench, including EnterpriseOps-Gym and EVA-Bench, is available now as an open-source release. 

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TELUS to launch Canada’s leading Sovereign AI Factory, powered by NVIDIA

Posted in Commentary with tags , on March 18, 2025 by itnerd

TELUS, in collaboration with NVIDIA, announced today that it plans to build Canada’s leading Sovereign AI Factory — a powerful and super-secure facility that will give Canadian businesses and researchers access to cutting-edge technology — helping them develop smarter AI products, streamline operations and stay competitive in a fast-changing world. It provides the supercomputers and software needed to train AI while keeping data safe within Canada’s borders.

TELUS plans to deploy NVIDIA’s latest-generation, industry-leading graphics processing units (GPUs), following NVIDIA Cloud Partner (NCP) Reference Architectures and software stack, at its data centre in Quebec by summer 2025, with expansion planned at its facility in British Columbia.
The Sovereign AI Factory will leverage TELUS’ high-speed, ultra-low-latency, fibre-optic network with sustainable data centres powered by 99% renewable energy sources to deliver AI as a Service (AIaaS).

TELUS’ world-class data centres are designed to be three times more energy efficient for excess power usage than the industry average, using significantly less electricity to power AI computing workloads. The facilities also rely on natural cooling, cutting water consumption by more than 75% compared to traditional data centres. With these efficiency measures in place, TELUS’ Sovereign AI Factory will be one of the most sustainable AI-ready data centres in the world

NVIDIA’s latest Hopper- and Blackwell- based supercomputers will power the AI Factory, enabling faster AI model training, fine-tuning and advanced inference capabilities. TELUS will be among the first to introduce these accelerated computing platforms to Canada, playing a crucial role in the country’s AI ecosystem.

TELUS’ Sovereign AI Factory will ensure businesses and researchers have access to the AI computing power required to scale, boost productivity and power innovation. By using this secure, high-performance AI Factory, Canadian businesses can develop local solutions to local challenges, ensuring Canadians can build, train, scale and deploy AI in a secure environment compliant with Canada’s security standards and privacy regulations.

The Sovereign AI Factory marks the next step in TELUS’ long-standing leadership in AI, reinforcing its broader commitment to responsible AI adoption, innovation and productivity growth in Canada. As the first Canadian telecom to sign the Government of Canada’s voluntary AI Code of Conduct in 2023, TELUS has consistently received industry recognition for its dedication to transparency, fairness and accountability in AI development.

TELUS was also the first company in the world to achieve a Privacy by Design certification (ISO 31700-1) for its generative AI-powered customer support tool. As one of only 20 organizations globally to participate in the OECD Pilot Framework for Advanced AI Systems, TELUS has played an active role in shaping global AI governance, contributing key insights to the G7 Working Group on Data & Technology. Additionally, TELUS has been recognized by the Responsible AI Institute for embedding ethical AI practices into its systems, setting a benchmark for responsible AI innovation in Canada and beyond.

With this latest milestone, TELUS is investing in Canada’s AI future — creating jobs, empowering businesses and ensuring we lead the world in the new AI-driven economy. This isn’t just infrastructure; it’s a commitment to building a stronger, more competitive Canada in the digital age.

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NVIDIA Strikes Back At The Hackers Who Hacked Them

Posted in Commentary with tags , on March 1, 2022 by itnerd

According to Vx-underground on Twitter, NVIDIA, which was the victim of an epic cyberattack last week, has reportedly retaliated against the hacker group that attacked them by hacking them:

The interesting part of the incident is that the group has reportedly made a copy of the stolen data on a virtual-machine environment, which implies that this counter-attack was not be successful. But it’s interesting that NVIDIA decided to go this route as opposed to engaging law enforcement.

LAPSU$ made the news recently for pwning a TV network in Portugal. They’re apparently based in South America and is well known in the ransomware community. And clearly this ransomware group takes steps to protect themselves that companies should be taking to avoid getting pwned. Such as making backups.

Mark my words. This is not over. There’s going to be more coming from this story.

UPDATE: Here’s some more info. NVIDIA has spoken. While they haven’t commented on attacking LAPSU$, they did say that the attack leaked employee credentials and some company proprietary information online after their systems were breached.

“We have no evidence of ransomware being deployed on the Nvidia environment or that this is related to the Russia-Ukraine conflict,” the company’s spokesperson said in a statement. The Santa Clara, California-based company said it became aware of the breach on Feb. 23. Nvidia added it was working to analyze the information that has been leaked and does not anticipate any disruption to the company’s business. A ransomware outfit under the name “Lapsus$” has reportedly claimed to be responsible for the leak and seemingly has information about the schematics, drivers and firmware, among other data, about the graphics chips.

UPDATE #2: Dr. Saumitra Das, CTO and Co-Founder, Blue Hexagon had this to say:

“This is typical of ransomware gangs nowadays where they can still cause brand damage and steal IP without actually deploying the final ransomware payloads. Double and triple extortion are all part of the current playbook for these attackers. In this case, it appears that the group claims to have been able to steal IP without encrypting data. There is always a tradeoff for the attackers between encrypting data and stealing data because encryption and deletion can trigger alarms at organizations with mature security programs and take away the leverage from the attackers.”

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BREAKING: NVIDIA Hit By Major Cyberattack

Posted in Commentary with tags , on February 25, 2022 by itnerd

News is filtering out that NVIDIA who makes graphics chips for major PC companies among other things has been hit by a major cyberattack. The word on the street says that their business may have been partially or completely compromised as a result:

NVIDIA has seemingly been hit by a major cyberattack that may have completely compromised parts of its business, reports The Telegraph. In their exclusive report, The Telegraph reports that the cyberattack was initiated at the same time as the Russian cyber warfare division started their offensive against Ukraine. All Nato allies have announced major sanctions on Russia and this could potentially be why Russia has decided to target major companies such as NVIDIA. 

The report further states that the cyberattack on NVIDIA has completely compromised parts of their business and there are already reports from several users coming in regarding services disruption. The scale of this attack is currently unknown but it clearly seems to be a major one as NVIDIA had to take several systems offline to pacify the intrusion before it could spread further: “‘The ultimate concern is that somebody may have put something in one of the software updates,’ Dr Woodward said, pointing to the devastating SolarWinds hack that exploited American software companies to gain access to US government computer systems. ‘They’ll be going through trying to make sure to see if there’s any indication that anything has been changed in their software that they then shipped to their clients.'” NVIDIA’s mail servers were also partially operational during this time so it’s entirely likely that there might have been a breach in confidential documents. But it is not confirmed yet if any data was stolen.

This is far from trivial. If the threat actors, which at this point appears to be Russia, slipped something into software updates such as graphic card driver updates, then this could become a massive supply chain attack that could affect tens of thousands of users. If the threat actors stole anything, that could really hurt NVIDIA’s business in the long term.

My question is, will this prompt retaliation from the US and other allies? We’ll have to watch and see.

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Nvidia Settles Chip Lawsuit

Posted in Commentary with tags , on September 30, 2010 by itnerd

Frequent readers of this blog will recall that Nvidia had some “problematic” GPU chipsets which lead to a lawsuit or two. Today Nvidia settled some of that litigation according to News.com:

In response to the settlement dated August 12, 2010, Nvidia issued this statement today. “We can confirm that Nvidia has settled litigation concerning a weak die/packaging material set in certain versions of our previous generation MCP (media and communication processor) and GPU products used in notebook configurations. Notice of this settlement has been sent to potentially affected eligible customers. Claims are being processed through a third party administrator who is working directly with our customers. Consumers who believe they are affected and wish to file a claim should read the notice and follow the instructions that it sets out. As previously announced, our second-quarter financial results reflected costs associated with this settlement.”

Okay. But here’s where things get interesting:

However, starting on page 24 of the settlement, Nvidia also stated that it “has denied, and continues to deny, all allegations of wrongdoing or liability” related to the claims. And it goes on to say that it is settling “solely because it will eliminate the burden, expense, management distraction and uncertainties of further litigation and the concomitant distraction of resources and efforts from their business.”

So this could be one of those “pay to make our legal problems go away” deals or it could be a “pay to cover up our shortcomings” deals. Either way, if you’ve got one of 50 models of Dell, HP or Apple computers, some cash could be coming your way. 

You can read the PDF with the full details here.

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Nvidia Halting Chipset Development…. Hmmm

Posted in Commentary with tags on October 8, 2009 by itnerd

PC Magazine is reporting that Nvidia is putting it’s chipset business on hold due to legal issues between itself and Intel. Nvidia sock puppet PR person Robert Sherbin explains why:

“We have said that we will continue to innovate integrated solutions for Intel’s FSB architecture,” Sherbin said in an email. “We firmly believe that this market has a long healthy life ahead. But because of Intel’s improper claims to customers and the market that we aren’t licensed to the new DMI bus and its unfair business tactics, it is effectively impossible for us to market chipsets for future CPUs. So, until we resolve this matter in court next year, we’ll postpone further chipset investments.”

Intel claims that its four-year-old chipset license with Nvidia does not cover the “Nehalem,” or Core series of microprocessors. Nvidia disagrees, and the matter will be hashed out in court in 2010. Nvidia still sells chipsets specifically designed for AMD’s line of processors, but has halted further development as well.

So, anybody who wants a chipset to work with an AMD or and Intel process is not going to Nvidia. That may pose a problem for Apple who uses Nvidia chipsets in Macs because they offer a performance improvement of similar Intel chipsets.

The same report also claims that Nvidia is also exiting the mid- and high-end standalone graphics card market, although the company has apparently called the rumor “patently untrue”. Sure, I remember not to long ago that rumors that it was leaving the chipset business were “groundless” according to Nvidia and today we have them leaving the chipset business. So take that denial for what it’s worth.

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