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Quantum computing is rapidly advancing, challenging enterprise security strategies to evolve just as quickly. This change prompts a critical question: Do you know what cryptography your business depends on today?  

Most organizations cannot fully answer this question. Quantum-computation methods pose a threat to today’s asymmetric cryptography, and new regulations, such as NIST’s PQC guidance, now require stronger systems. Discovering, analyzing, and planning for cryptographic changes is essential.  

Additionally, with the latest release of IBM Quantum Safe Explorer, clients running Z-Linux platforms, including IBM Linux, can now use it via the command line interface (CLI). This update delivers Quantum Safe visibility directly to mission-critical workloads, seamlessly extending these capabilities.  

Meet IBM Quantum Safe Explorer. 

IBM Quantum Safe Explorer enables developers and security teams to quickly pinpoint cryptographic elements in application code, APIs, and environments. This utility streamlines cryptographic inventory and assessment for evaluating quantum readiness.  

The tool helps track cryptographic assets, such as algorithms, keys, certificates, and libraries, across applications and infrastructure. It can generate cryptographic bills of materials (CBOMs) and assess cryptographic risks to prepare for quantum-safe transitions.  

Security and compliance professionals can use the tool to answer critical questions about quantum readiness.  

• Users can identify which cryptographic algorithms are deployed.  

• Assess whether they are outdated or insecure.  

• Locate where these algorithms reside.  

• Determine which applications use them and evaluate preparedness to adopt post-quantum solutions.  

With these new capabilities, clients using Z Linux and Linux One environments gain targeted answers to previously unresolved cryptographic questions, directly aligning with Quantum Safe Explorer’s core value.  

Unlocking Crypto Agility with IBM Quantum Safe Explorer 

Preparing for a quantum-safe future requires more than technical vulnerability scans. Organizations need visibility, agility, and management over encryption systems. IBM Quantum Safe Explorer supports diverse stakeholders, positioning CBOIMs at the center of risk management and long-term crypto-agility goals.  

Value Delivered At Two Levels 

1. For InfoSec and DevSecOps Leads: Portfolio Visibility & Governance 

Security and development leads gain clear visibility into cryptographic risks across portfolios. CBs provide a unified inventory for audits and compliance, highlight high-risk areas, and automate inventory generation in each development cycle for continuous oversight.  

Dashboards display essential metrics, including new crypto components, changing risk scores, and remediation coverage across projects. This helps DevSecOps teams add cryptographic checks to the CI/CD pipeline with little disruption.  

1. For Leadership & the C-suite, translating risk into action 

Executive dashboards distill technical details into clear business insights. Leaders quickly understand which applications depend on vulnerable cryptography, the completeness of cryptographic inventories, and areas needing agility improvements. Quantum Safe Explorer equips executives with compliance-ready evidence to demonstrate NIST quantum-safe conformance to regulators, supporting both current mandates and future requirements, such as the U.S. federal mandate for a cryptographic inventory by 2025. This enables leadership to prioritize risk mitigation and facilitate strategic planning for crypto agility investments.  

This shift allows leadership to proactively manage cryptographic risk at the business level, ensuring strategic alignment and operational readiness for evolving security requirements.  

Crypto Agility Anti-Patterns: What to Watch For 

Crypto agility requires the ability to update cryptographic algorithms across systems efficiently and reliably. Quantum Safe Explorer identifies any practices that may hinder this flexibility, including embedded algorithm versions, absent fallback mechanisms, or inconsistent library implementations.  

By identifying and mapping these issues to code paths, our solution provides teams with a clear plan for fixing them. This supports both current compliance and future resilience.  

New CLI support for Quantum Safe Explorer on Z Linux. 

This release adds CLI support for zLinux, making it easy to integrate into secure environments such as financial systems, public cloud platforms, and other regulated workloads.  

This means clients can now:  

• Run cryptography discovery natively on Z Linux without moving data off the platform.  

• Integrate QSE into CI/CD pipelines or system automation scripts.  

• Generate CBOMs on demand for audit compliance or quantum readiness planning.  

• Build a roadmap for replacing vulnerable cryptographic components over time.  

The CLI was designed for Enterprise DevOps teams to get started: install it on zLinux and configure the required access credentials. Add CLI commands to existing process scripts or automation workflows to perform cryptographic discovery. Generate CBO and reports, and track assets. Run these steps at defined intervals or during build and deployment stages to ensure up-to-date visibility.  

Why IBM LinuxOne 5? 

IBM Linux One 5 provides a secure platform for IBM Quantum Safe Explorer, allowing firms to prepare applications for the future with post-quantum cryptography.  

The system uses secure boot technology to prevent malware from being loaded during startup, improving cyber resiliency, and keeping the system safe. The crypto express 8s (CEX8s) hardware security module supports both classical and quantum-safe cryptography, meeting needs for confidentiality, integrity, and non-repudiation.  

LIDEX One 5 protects sensitive data both when stored and in use, thanks to its cybersecurity and privacy features. Its built-in crypto accelerators, confidential computing, and NIST-standardized post-quantum cryptography provide a strong foundation for quantum resistance in modern IT systems.  

Integration That Delivers: Security, Compliance, And Agility 

Combining IBM Quantum Safe Explorer with IBM LinuxOne 5 brings multiple technical benefits, such as:  

• Quantum Safe Explorer leverages LinuxOne 5’s crypto accelerators and confidential computing, enabling deep cryptographic analysis and protecting sensitive data throughout its lifecycle.  

• Simplified compliance: the combined solution makes it easier to comply with regulations such as PCI DSS, FIPS, GDPR, and the EU’s Digital Operations Resilience Act (DORA).  

What does this mean for LinuxOne clients? 

IBM LinuxOne clients are familiar with security and availability. These systems are built to process sensitive workloads with built-in encryption, hardware isolation, and high availability.  

However, even the most secure systems use cryptographic algorithms that may be decades old, and some of them are now at risk due to quantum computing. Many organizations also do not know where or how these algorithms are used.  

With this release, LinuxOne clients can now perform cryptographic discovery directly on the platform without exposing data. They can identify algorithm dependencies early, enabling crypto agility before major changes are necessary. This also helps them prepare for new NIST post-quantum standards.  

The solution makes it easier to meet compliance requirements for regulations such as FIPS, GDPR, and PCI DSS, which now require greater insight and control over cryptographic assets.  

To summarize, Quantum Safe Explorer on Z-Linux helps organizations improve their cryptography practices and plan for the future directly within their LinuxOne environments, securely, efficiently, and at scale.

Source: Extending quantum-safe visibility to LinuxONE: IBM Quantum Safe™ Explorer now available with CLI support on Z-Linux 

As the semiconductor industry moves from general-purpose computing toward specialized AI acceleration, AMD’s upcoming Gen 6 architecture, known as Morpheus, will introduce a major change: Coron, native support for IMT (for Bit integer) instructions.  

This shift toward INT4 is a significant evolution from previous architectures that emphasized FP16 and INT8 for machine learning. The transition reflects not only technological advancement but also aligns with industry trends for efficient edge inference.  

The Move to 4-bit Precision 

The main challenge for local AI, whether on a desktop PC or a workstation, is memory bandwidth and cache pressure. Large language models (LLMs) and diffusion models consume significant memory. With INT4 quantization, it can compress models much more than the current int8 standard.  

Instructions let the processor fit more data into the same amount of memory cache. For example, a model that once needed 16 GB of VRAM or system memory can now be compressed to 4-6 GB using 4-bit weights, with little loss in accuracy. For most consumer tasks with native hardware support, these operations avoid the usual quantization tax, which is the extra software work needed to convert 4-bit data back to 3 higher precision for calculations.  

Architectural Synergy: AVX 512 and the AI Engine 

NT4 support in Zen 6 is not simply an add-on; it is built into the updated AVX-512 execution units. By expanding the vector map to support 4-bit-packed integers, AMD delivers a significant boost in Token-Per-Second performance for running Local LLMs.  

Zen6 will also have closer integration between its x86 cores and the XDNA3 Neural Processing Units (NPU). The NPU manages ongoing background AI tasks, while the Zen6 cores use INT4 instructions for large on-demand tasks, such as real-time code completion or live translation. This hybrid setup keeps the CPU as a key part of the AI processing pipeline.  

Impact On Local AI Development 

For US developers using frameworks like PyTorch and TensorFlow, native int8 support makes it easier to run small language models (SLMs) like Llama3 or PHI3. In the past, running these models locally needed a high-end GPU. With Zen6, the CPU can handle adversarial inference on its own, reducing the need for cloud APIs and improving data privacy for businesses.  

Key Benefits of Gen 6 INT4 Support Include: 

• Reduced memory bottlenecks: lower-precision data moves faster through the Infinity Fabric and memory controllers.  

• Improved power efficiency: fewer bits per operation translates directly to lower joules per inference.  

• Enhanced cache locality: more parameters fit in L2 and L3 caches, reducing the need to fetch data from slower system RAM.  

Conclusion: The Future of the AI PC 

By building iMT4 support into Zen6, AMD demonstrates that the AI PC is no longer just an idea it’s an imminent, practical reality. As late 2026 nears, Zen6 is poised to reshape the expectations for performance and autonomy in local AI. For developers and businesses, the barriers to running advanced AI locally are on the verge of vanishing.

Source: AMD Introduces Ryzen AI Embedded Processor Portfolio, Powering AI-Driven Immersive Experiences in Automotive, Industrial and Physical AI 

Policy in Amazon Bedrock AgentCore lets developers set up and enforce security controls for how AI agents interact with tools, creating a secure boundary around agent activities. AI agents can adapt to handle a range of tasks, from answering customer questions to automating workflows across multiple tools and systems, but this flexibility can also introduce new security risks as agents might misunderstand business rules or exceed their intended limits.  

In AgentCore, developers can build policy engines. These are software components that automatically enforce rules. Developers store explicit policies in these engines and connect them to gateways, which control and monitor the flow of requests. The system checks all agent traffic passing through Amazon Bedrock AgentCore gateways. It ensures each request complies with the defined policies before agents can access tools.  

Policies are written in Cedar, an open-source language for creating and enforcing authorization rules. This helps developers clearly define what agents can access and what actions they can take. Policy in AgentCore also lets developers write policies in plain English, so they do not have to use Cedar. The system deciphers these natural-language rules, generates possible policies, checks them against the tools set up, and uses automated checks to spot overly broad, overly strict, or impossible-to-make rules. This helps customers find and fix problems before policies are enforced.  

Policy in AgentCore provides detailed rights based on user identity and tool inputs, making it safer to use autonomous agents at scale by handling security outside the agency’s code. Developers can focus on building new features while maintaining strong security. This removes the need for custom security work and lowers the risk of agents bypassing policies.  

Key Benefits 

PolAgentCore policy delivers three main benefits for secure, scalable AI agent deployment. Fine-grained Control: Define the actions agents can take, the tools they can use, and the conditions under which they can use them.   

• Deterministic Enforcement: Consistently enforce policies outside agent code for reliable security. Accessible Authoring: Create policies in English or Cedar for broad team adoption.EnfAll enforcement decisions are logged in CloudWatch for compliance purposes.  

Key Features 

Policy in AgentCore provides a full set of tools to manage agent interactions with policies. Main features include:  

• Policy enforcement: the system checks all agent requests against set policies before granting access to tools.  

• Access Controls: allow detailed permissions driven by user identity and tool input.  

• Policy authoring: Write clear, validated policies in Cedar. You can also create policies in plain English, which the system translates and checks.  

• Policy Monitoring integrates with Amazon CloudWatch (a monitoring service that collects and tracks metrics) to observe policy checks and decisions.  

• Structure collaboration works with VPC security groups and other AWS security tools.  

• Audit Logging keeps comprehensive logs of policy decisions for compliance and troubleshooting.

Source: Policy in Amazon Bedrock AgentCore: Control Agent-to-Tool Interactions 

Google Cloud regularly works with customers, partners, and registrars to deliver technology that meets their needs. We have been helping customers with digital sovereignty solutions for almost ten years.  

With this longstanding commitment, we are excited to share technical and commercial updates to our sovereign cloud solutions, enabling customers to gain greater control, choice, and security in the cloud without sacrificing functionality.  

Building on the first sovereign solutions we introduced years ago, we’ve massively scaled our global infrastructure footprint, now comprising more than:  

• 42 cloud regions  

• 127 zones  

• to work at the network edge locations  

• 33 subsea cable investments  

We have built important partnerships across Asia, Europe, the Middle East, and the United States. Our partners include:  

• Schwarz Group and T-Systems in Germany  

• S3NS in France  

• Minsait in Spain  

• Telecom Italia in Italy  

• Clarence in Belgium and Luxembourg  

• CNTXT in Saudi Arabia  

• KDDI in Japan  

• Worldwide Technology in the United States  

Our Pledge To Customer Choice 

Digital sovereignty means more than just managing encryption keys. It supports giving customers the flexibility their global businesses need. It also allows them to use multiple clouds and secure their data with advanced technologies.  

We have always supported customers in choosing providers and solutions that work for them. Because cloud sovereignty varies by customer, we offer a range of solutions to address different needs and risk levels.  

We back our strong customer commitments with reliable sovereign controls and solutions, all available now. Our updated Sovereign Cloud solution portfolio includes:  

• Google Cloud Data Boundary lets customers decide where content is stored or processed, and allows them to manage encryption keys (which lock and unlock data) outside Google’s infrastructure. This helps them meet specific data control needs in any market.  

Google Cloud Data Boundary customers can access a broad range of Google Cloud products, including AI services. They benefit from features such as confidential computing and external key management with key access justifications, which let them control and deny access to their data as needed. With data boundaries, sovereign controls, customers can limit data processing to the United States or the EU, select countries for local data storage, and use client-side encryption to prevent unauthorized access, even by Google, to their most critical content.  

We are also introducing User Data Shield, which uses Mandiant services (security experts) to check the security of customer applications built on the Google Cloud data boundary. User Data Shield performs regular security testing of these customer applications to help confirm that sovereignty rules are being followed.  

• Google Cloud Dedicated delivers a solution created to meet local sovereignty requirements, enabled by independent local and regional partners. For example, Google Cloud has partnered with Thales since 2021 to build a first-of-its-kind, S3NS-trusted cloud for Europe.  

This offering with Thales is intended to provide a rich set of Google Cloud services with GPUs to support AI workloads. It is operated by S3NS, a standalone French entity currently in preview. S3NS solution is designed to satisfy the rigorous security and functional resilience requirements of France’s SecNumCloud standards. We are expanding our Google Cloud dedicated footprint globally and will include Launch Next in Germany.  

For France to truly embrace digital sovereignty, it is essential to have a cloud solution that unites the greater power of hyperscale technology with the strictest local security and administrative controls. S3NS is committed to providing French organizations with access to advanced cloud services, including critical AI capabilities, all operated within France by a European operator to meet and exceed the rigorous SecNumCloud standards, said Christophe Solomon, EVP Information Systems and Secured Communications at Thales.  

• Google Cloud air-gapped is a standalone solution designed to operate without any direct or indirect connection to external networks; ie, an air-gapped system. It is intended for customers in fields such as intelligence and defense that require high-level data security and data residency controls, meaning strict oversight of where data is stored. Google, the customer, or a Google partner can take responsibility for deploying and managing this solution.  

This solution uses open-source components and includes selected AI, database, and infrastructure services. Relying on open-source technology helps ensure business continuity and resilience during service disruptions. In 2024, Google Cloud Air Gapped was approved to host the US government’s top secret and secret-level data.  

Working with Google Cloud to introduce sovereign offerings can give our joint clients greater control, choice, and security in the cloud without jeopardizing the functionality of their underlying cloud architectures, said Scott Alfieri, Senior Managing Director and Google Business Group Lead at Accenture. Google Cloud’s extensive global infrastructure, coupled with Accenture’s transformation and industry expertise, helps organizations build an agile and scalable foundation, unlocking chances for growth and continuous innovation.  

Local Control Global Security 

Security and sovereignty go hand-in-hand. When customers control their data and operations locally, they can feel more confident about security; however, true security sovereignty is not possible if outdated infrastructure exposes data to loss or theft.  

According to the Google Threat Intelligence Group and Google Cloud’s Office of the CISO (Chief Information Security Officer), cyber attacks globally are becoming more advanced. Attackers are now leveraging Artificial Intelligence (AI) tools and techniques to exploit weaknesses in older software platforms and outdated systems.  

With Google Cloud, customers receive sovereign solutions along with top security features. These include Secure by Design technology and the expertise of the Google Threat Intelligence Group and Mandiant Consulting, which work at the front lines of cyber defense and partner with over 80 governments globally.  

Google Cloud CyberSheild uses AI and intelligence-driven tools to help governments defend against large-scale threats. Mandiant managed defense services also let customers around the world strengthen their security teams with our experts.  

Google’s Sovereign Cloud Solutions let customers leverage Google Cloud’s secure foundation and access state-of-the-art security features, including:  

• Confidential Computing  

• Zero Trust  

• Post Quantum Cryptography  

• AI-Driven Defenses  

These features can be delivered faster and at a lower cost than building them in-house.  

Sovereign Solutions For Any Organization 

We are committed to building trust, giving our customers control, and helping organizations confidently handle digital sovereignty. We continue to work with customers, partners, and regulators to improve and deliver the sovereign cloud solutions needed.  

Learn more about our digital sovereignty support on our website or by contacting your account manager.

Source: Advancing sovereignty, choice, and security in the cloud for our customers May 21, 2025 

Samsung SDI announced it will present advanced battery solutions and new technologies for the AI era at InterBattery 2026, held March 11-13 at COEX in Seoul.  

At this year’s exhibition, the company will unveil a pouch-type all-solid-state battery sample under development for physical AI applications such as humanoid robots. This product aims to provide greater safety and longer operational time, emphasizing Samsung SDI’s global leadership in all-solid-state battery technology.  

Samsung SDI will also present battery solutions that boost reliability for energy storage systems (ESS) and provide more stable, high-power batteries for uninterruptible power supplies (UPS) and battery backup units (BBU). These solutions strengthen essential AI infrastructure by ensuring continuous operation and rapid response during power fluctuations.  

United by the slogan “AI thinks battery enables,” Samsung SDI will have the largest booth, featuring innovative technologies and products.  

Our goal is to show how Samsung SDI’s battery technology brings the complete potential of the AI era to life. A company official said, “With decades of expertise, we will present premium battery solutions designed for the changing needs of AI-powered industries.”  

First Public Display of Pouch-Type All-Solid-State Battery for Physical AI 

Samsung SDI will introduce its All-Solid State Battery technology at InterBattery2026. This technology, still in development, targets mass production in the second half of next year.  

The company will show a pouch-type or solid-state battery sample for the first time, designed for new physical AI applications.  

Robots have limited space for batteries and require small, lightweight cells with high energy density for long run times. They also need high power output during motion, so batteries must deliver it without overheating.  

Samsung SDI is developing all-solid-state batteries that offer superior safety and high-power output for physical AI applications, using a pouch designed to reduce weight. After focusing on prismatic batteries for electric vehicles, the company now plans to offer a wider range of battery shapes for different applications, including humanoids, robots, aviation, and next-generation wearables.  

To align with these technological advancements, this year’s exhibition theme is Inside AI, giving visitors an up-close look at how batteries are used in industries and everyday life.  

The main booth will resemble a real IT data center, allowing visitors to feel like they are inside a working facility.  

At the center of the booth, a US UPS mock-up will feature Samsung HDI’s U8A1 battery for UPS uses.  

The U8A1 combines a unique prismatic shape and LMO chemistry for high power and safety. Designed for data centers, it offers greater energy density and volume efficiency for stable, rapid power delivery.  

Unlike regular UPS batteries that only power during outages, the U8A1 also helps keep power steady during sudden spikes in AI power consumption. This feature enables continuous operation and prevents downtime, making it better suited to changing customer needs.  

Behind the UPS area, Samsung SDI will debut its high-power BBU battery, installed in data center servers to provide instant backup during outages and prevent data loss.  

The BBU uses high-nickel NCA cathodes (which store more energy) and SCN anodes (which allow faster charging) in a cylindrical battery. Annually, at the bottom, it helps release heat, reduces internal temperature, and extends battery life, enhancing overall safety.  

By connecting high-power, high-capacity cells directly to servers, the system gives instant support during power peaks and can increase data storage time by over 50% during outages, enhancing operational continuity and protecting critical information.  

Pop Art Collaboration With Um Jaewon And Exhibition Highlights 

To begin, visitors can check out power tools that use Samsung’s HDI cylindrical batteries. This gives everyone a chance to see the company’s high-power cylindrical technology up close.  

Samsung SDI’s cylindrical batteries use tapped technology, increasing power output and charging speed. For example, a circular saw with these batterie’s cuts wood faster and recharges in 15 minutes.  

In addition to the technology displays, Samsung HDI is presenting five artworks created in collaboration with Korean artist Um Jaewon, inspired by the theme Fun-tastic Power: Energy that powers joy in everyday life. These pieces contribute a creative element to the exhibition. In his work, Um Jaewon portrays ESS as a quiet hero safeguarding sustainable energy in the AI era, and he represents Samsung HDI’s high-power batteries as small cells with significant potential, symbolizing how innovation can empower and enhance daily life.

Source: SAMSUNG SDI Unveils All-Solid-State Battery for Physical AI 

At its Vision 2025 conference, Intel announced the start of risk production for its 18A process node. This marks the beginning of low-volume test manufacturing for the node.  

Intel’s Kevin O’Buckley, the senior vice president of Foundry Services, made this announcement as Intel approaches the completion of its goal to deliver five new process nodes in a four-year period a program starting in 2021 under ex-CEO Pat Gelsinger. This Vision 2025 conference is also the first to feature Intel’s new CEO, Lip-Bu Tan, on stage.  

Intel announced its four-year development plan in June 2021. Within this plan, Intel canceled high-volume manufacturing of the 20A node to reduce costs and shifted its focus to preparing it for production. The 18A node is nearing completion, and the 5N4Y plan emphasizes having nodes ready within the four-year window rather than immediately launching high-volume manufacturing for each.  

Risk production is a key step toward launching a new node. It shows Intel believes the node is close to high-volume manufacturing. The company has already built many 18A test chips, sometimes with several designs per wafer.  

During the risk production stage, Intel manufactures wafers with a single-chip design in low volumes to refine the manufacturing process and test the node and its process design kit. Following earlier research, design, and prototyping phases, Intel expects to ramp up production later in 2024.  

Risk production entails low yields and performance as Intel refines manufacturing. Customers use this stage for qualification or engineering samples without the strict yield guarantees of fully qualified manufacturing nodes.  

Some customers accept these risks to evaluate the node early and gain a head start on competitors.  

Intel has not said whether the 18A risk production is for its Panther Lake processors, due later this year, or for outside customers. Panther Lake, the first 18A processors, will enter mass production later this year. Thus, Panther Lake likely leads the risk production, matching Intel’s usual timeline from risk production to high-volume manufacturing.  

Although Intel pioneered several new technologies on its cancelled 20A node, the 18A chips will be the first productized chips to feature both backside power delivery and ribbon-FET gate-all-around (GAA) transistors. Power via provides refined power routing to improve performance and transfer transistor density, while ribbon-FET offers higher density and faster switching in a smaller area.  

Intel is also working on its broader foundry map, including the upcoming 18A node, its first to use high NA EUV lithography. Additional node extensions will help Intel Foundry Services serve more applications.  

These changes are occurring as Intel Foundry faces challenges amid shifting economic conditions. For example, Intel has delayed building its Ohio site until 2030. Still, the news about 18A risk production matches reports that Intel is already making its first 18A wafers in Arizona.  

Additional details about Intel’s timeline and future production stages will likely be provided at the Foundry Direct Connect event scheduled for late April 2024.  

Risk production, while it sounds scary, is actually an industry-standard terminology. The importance of risk production is that we have reached a point where we can freeze it. Buckle O’Buckley explained: “Our customers have validated that 18A is good enough for any product, and we now have to do the risk part, which is to scale from making hundreds of units per day to thousands, tens of thousands, and then hundreds of thousands. Risk production is scaling manufacturing up and making sure that we can meet not just the capabilities of the technology but the capabilities at scale.”

Source: Intel CEO embraces its 18A node for external customers as 18A-P gets ‘inbound interest’ — company cites increasing yields 

AI agents are evolving from simple tools to virtual team mates that help us work more efficiently. As teams adopt these agents, tracking them can be challenging. Their ability to handle complex tasks independently makes it critical to manage their identities, permissions, life cycles, and resource access securely.  

Our goal is simple, we want to give AI agents, the new digital teammates, the same protections and controls you already use for your workforce identities. The main benefit is that you can manage the security and life cycle of all AI agents from a single central location, just as you do with your human users. Today, I’m happy to tell you about the public preview of Microsoft Entra Agent ID, announced at Microsoft Build. In this first release, we’ve created a single directory for all agent identities in Microsoft Copilot Studio and Azure AI Foundry. This means that whether an agent is built by a developer or an information worker, you can see and manage the agent securely in the Microsoft Entra admin center.  

In the next six months, we’ll add more features for access management, security, and identity governance to Microsoft Entra Agent ID. We’ll also add support for agents from Security Copilot, Microsoft 365 Copilot, and other third-party solutions.  

How To Get Started 

As organizations increasingly adopt AI solutions, it’s important to know which agents have access to their environments. Starting today, you will see a new application type in the Microsoft Entra admin center that allows these agent identities. The agent ID application type lets you quickly view and track agent identities in your directory.  

To get started, sign in to the Microsoft Entra Admin Center and go to Enterprise Applications. At the top of the list, use the filter bar, set the application type dropdown to Agent ID (preview), and review the AI agents created with Copilot Studio or Azure AI Foundry in your tenant. Begin by selecting an agent, exploring its permissions and lifecycle settings, and making any required security updates. This will ensure you are actively managing your agents securely from today.  

What’s Next for Microsoft Entra Agent ID 

The features we offer today are just the beginning of our work to help you secure and manage AI Agent Identities. We understand you need more than visibility, so we are developing new tools to give you greater control over AI Agents and their access to resources.  

For example, we plan to make Microsoft Entra Agent ID work not just with agents built on Microsoft AI platforms. It will also support agents created using many other AI development tools.  

Over the next few months, Microsoft Entra Agent ID will add new features. These updates will help you strengthen your Zero Trust security and save time for both developers and identity teams.  

For Developers 

• Built-in security controls: Agent identities in Microsoft Entra will use a least-privilege approach. They will request just-in-time, limited tokens for the resources the agent needs, such as a specific file or Teams channel.  

• Instant Enterprise Boarding: agent identities will be full of identities in Microsoft Entra, so identity teams can find, approve, and audit your organization’s agents with the same tools they use for apps and users. There is no need for extra security reviews or custom co-auth flows once your agent has an identity in other Microsoft Entra tenants, each with its own policies, while you maintain a single codebase and telemetry stream.  

For Identity Practitioners 

• Richer access controls: You can set detailed conditional access policies and permissions. This ensures AI agents access only the resources they need, using real-time signals and context.  

• Enhanced lifecycle management: You will be able to automate least-privileged access from the beginning and manage AI agent identities as carefully as you do for users and services, from creation to removal.  

• Expanded auditing and monitoring: You will gain access to detailed logs and visibility into agent activities for compliance and security. You can track what each agent does.  

Better Together: We Are Working With The Industry, Our Partners, And You  

We’ve always believed security is a team sport, and this will be especially true in protecting AI agents and their identities. That’s why I am so energized by the progress we are making together as an industry. Two weeks ago, Microsoft announced our support for the agent-to-agent (A2A) protocol, and we are actively partnering with the industry to design enterprise-grade identity support for both the A2A and the popular MCP protocols.  

Here is a demo of A2A in action. Our team used Azure AI Foundry and Microsoft Entra Agent ID to create a Teams agent that finds Entra and meeting room agents in the Entra registry, then uses them to book a meeting room and invite team members.   

Today, I am also excited to announce that we are partnering with ServiceNow and Workday. As part of this, we will integrate Microsoft Entra Agent ID with the ServiceNow AI platform and the Workday agent system on record. This will enable automated provisioning of agent identities that can perform duties alongside human employees in parallel. We are working to integrate ServiceNow and Workday agent-enabled applications with Microsoft Entra ID so that every agent created in ServiceNow or Workday has its own identity.  

As the next step, try out the new Microsoft Entra Agent ID features by managing a few AI agents in your environment. Provide feedback or questions in the comments below to help us improve. We are excited about what’s next for Microsoft Entra Agent ID and look forward to hearing how you use these features.  

Ensure every identity human or agent is managed and secured together.

Source: Announcing Microsoft Entra Agent ID: Secure and manage your AI agents 

NVIDIA’s new Blackwell Ultra architecture introduces program-dependent launch, enabling preemptive scheduling of subsequent GPU kernels while the current kernel executes. This advancement in the GB300 NVL72 system enhances GPU utilization and throughput for complex AI workloads, such as agent-based AI and advanced reasoning models.  

Highlights Of Programmatic Launch And Blackwell Ultra 

• The new launch feature cuts GPU idle time between kernels and maximizes throughput for high-performance AI workloads.  

• The GB300 delivers a 1.5x boost in NVF throughput and doubles the attention task speed compared to standard Blackwell.  

• The platform targets extended context inference and test-time scalability, supporting agentic systems that require deep reasoning.  

• Blackwell Ultra supports 800 GB/s networking (Spectrum-X Quantum-X800) and works with NVIDIA Dynamo for large-scale multi-node tasks.  

• These enhancements are expected to become available through partners in the second half of 2025.  

Blackwell Ultra includes a RAS engine to detect faults and cut downtime, adding reliability and efficiency.  

AI has advanced for years by scaling pre-training with larger models, more data, and greater computing power to achieve new capabilities. Over the past five years, this approach has increased compute needs by 50 million times, but now making smarter systems is about more than just bigger models. The focus is shifting to refining models and enabling them to think.  

Refining AI models with post-training scaling boosts performance and conversational ability. Tuning with domain-specific and synthetic data enables nuanced tech understanding and better inputs. Synthetic data production has no upper limit, increasing demand for post-training compute.  

A new approach called test-time scaling has now emerged to boost AI intelligence.  

Also known as long-thinking test time, scaling dynamically increases compute during AI inference to enable deeper reasoning. AI reasoning models don’t just generate responses in a single pass; they actively think, weigh multiple possibilities, and refine their answers in real time.  

This is moving us closer to true agentic intelligence: AI that can think and act independently to tackle more sophisticated tasks and provide more useful answers.  

Switching to post-training and test-time scaling greatly increases the need for computational resources. For example, the post-training process may require up to 30 times as much computational power as the original pre-training phase when creating custom AI models. Likewise, the long thinking involved in test-time scaling can demand up to 100 times as much computation as a single inference would for solving especially complex tasks.  

Blackwell Ultra NVIDIA GB300 NVL72 

To address these needs, NVIDIA launched Blackwell Ultra, a high-speed computing platform made for advanced AI reasoning. It supports training-time, post-training, and test-time scaling. Blackwell Ultra is built for large-scale AI inference, offering smarter, faster, and more efficient AI while keeping costs down.  

Blackwell Ultra powers the NVIDIA GB300 NVL72 systems. These liquid-cooled rack-scale setups connect 36 NVIDIA Grace CPUs and 72 Blackwell Ultra GPUs, all working together as one large GPU. The system offers an NVLink bandwidth of 130 TB/s.  

Blackwell Ultra delivers even greater AI inference performance for real-time multi-agent systems and long-term context reasoning. Its new Tensor cores provide 1.5 times more AI compute FLOPS than Blackwell GPUs. The GB300 NVL72 offers 70 times more AI FLOPS than the HGX H100. Blackwell Ultra also supports several FP4 formats to improve memory efficiency for advanced AI. Coherent memory per GB300 NVL72 rack opens the door to breakthroughs in AI, research, real-time analytics, and more. It provides the large-scale memory needed to run many large AI models simultaneously, having a high volume of complex tasks from many concurrent users, improving performance and reducing latency.  

Blackwell Ultra Tensor Cores accelerate attention layers twice as fast as the previous Blackwell system. This enables efficient processing of long context lengths, which is vital for real-time AI handling millions of input tokens at once.  

Optimized Large Scale Multi-Node Inference 

Efficiently inquiring AI inference requests across many GPUs is key to keeping costs low and increasing revenue in AI factories.  

Blackwell Ultra uses PCIe Gen 6 and ConnectX-8 800G Super NIC to raise network bandwidth to 800 GB/s.  

With more network bandwidth, NVIDIA Dynamo an open-source inference framework scales AI model services across nodes. It allocates GPU workers dynamically to reduce traffic bottlenecks.  

Dynamo also offers disaggregated serving. This means it separates the context (pre-fill) and generation (decode) steps for large-language-model inference across GPUs. This setup improves performance, making scaling easier and lowering costs.  

GB300 NVL72 supports 800 GB/s per GPU and integrates Quantum-X800 and Spectrum-X networking. It efficiently scales model size, data, and reasoning for AI factories and data centers.  

• data  

• reasoning capability  

Summary 

Blackwell Ultra accelerates AI reasoning, enabling real-time insights, smarter chatbots, better analytics, and productive AI agents in finance, healthcare, and e-commerce. Organizations can run larger models and more demanding AI workloads faster and more efficiently, making advanced AI practical in real life.  

Blackwell Ultra products will be available from partners in the second half of 2025, with all major cloud providers and server makers supporting them. See below for more details.

Source: NVIDIA Blackwell Ultra for the Era of AI Reasoning 

Apple has launched the new 14-inch and 16-inch MacBook Pro models with M5 Pro and M5 Max chips. These laptops deliver enhanced performance and advanced AI capabilities. The new CPU features what Apple describes as the world’s fastest CPU core. The GPU now integrates a Neura core l Accelerator in each, along with increased Unified Memory Bandwidth. This delivers up to 4x the AI performance of the previous generation and up to 8x for ML models. These enhancements enable developers, researchers, business professionals, and creatives to leverage AI-driven workflows directly on the MacBook Pro.  
 
The laptops now have SSDs that are up to twice as fast and start with:  

• 1 TB of storage for the M5 Pro  

• 2 TB of storage for the M5 Max  

The new MacBook Pro also features the N1 wireless chip, which supports WiFi 7 and Bluetooth 6 for better wireless performance and reliability. Other highlights include:  

• up to 24 hours of battery life  

• a Liquid Retina display with Nano Texture option  

• a range of connectivity options, including Thunderbolt 5  

• a 12MP Center Stage camera  

• studio-quality microphones  

• a 6-speaker sound system  

• Apple’s intelligence features and macOS Tahoe  

The MacBook Pro is available in Space Black and Silver, with pre-orders starting March 4 and availability beginning March 11.  

MacBook Pro with M5 Pro and M5 Max sets a new standard for Pro Laptops, now up to four times faster than the previous generation, said John Ternus, Apple’s senior vice president of hardware engineering. With Neural accelerators in the GPU, the new MacBook Pro lets professionals run advanced LLMs on the device and unlock features that other laptops can’t match, all while keeping great battery life with faster unified memory and storage. Users can do even more with their work, opening new possibilities and expanding what’s possible.  

Outstanding Performance With M5 Pro And M5 Max 

The M5 Pro and M5 Max chips use Apple’s new Fusion architecture, designed specifically for AI. This approach combines two dies into a single system-on-a-chip, yielding significant performance gains. Both chips have a new CPU with up to 18 cores, including six super-cores featuring the world’s fastest CPU core and 12 new performance cores. This setup is optimized for power-efficient multi-threaded professional tasks and delivers up to 30% faster performance. The M5 Pro is ideal for users with complex workflows, such as coders working on algorithms or photographers managing large image libraries. The M5 Max is built for those who need maximum power, such as engineers running demanding simulations.  

The M5 Pro and M5 Max scale up performance from M5 and use the same advanced GPU design. Each core has a Neural Accelerator. LLM prompt execution is up to four times faster than on M4 Pro and M4 Max. This lets researchers and developers train custom models locally. Creative professionals can use AI-powered tools for editing, music, and design. Both chips also bring up to 50% more graphics performance than M4 Pro and M4 Max. Motion designers can work with complex 3D scenes in real-time. VFX artists can preview effects instantly. The neural engine is now faster and more efficient. Unified memory bandwidth is also higher, enabling advanced workflows such as intensive AI model training and massive video projects. M5 Pro supports up to 64 GB of unified memory and up to 307 GB/s bandwidth. M5 Max supports up to 128 GB of memory and up to 614 GB/s bandwidth.  

The 14 and 16-inch MacBook Pro models with M5 offer:  

• AI image generation is up to 7.8 times faster than on a MacBook Pro with M1 Pro and up to 3.7 times faster than on a MacBook Pro with M14 Pro.  

• LLM prompt execution is up to 6.9 times faster than on a MacBook Pro with M1 Pro and up to 3.9 times faster than on a MacBook Pro with M4 Pro.  

• 3D rendering in Maxon Redshift is up to 5.2 times faster on a MacBook Pro with M1 Pro and up to 1.4 times faster on a MacBook Pro with M4 Pro.  

• Gaming performance with Ray Tracing in titles like Cyberpunk 2077 Ultimate Edition is up to 1.6 times faster than on a MacBook Pro with M4 Pro.  

The 14 and 16-inch MacBook Pro models with M5 Max offer:  

• AI image generation is up to 8x faster on the MacBook Pro with M1 Max and up to 3.8x faster on the MacBook Pro with M5 Pro Max.  

• LLM prompt execution is up to 6.7 times faster than on a MacBook Pro with M1 Max and up to 4 times faster than on a MacBook Pro with M4 Max.  

• Video effects rendering in Blackmagic DaVinci Resolve Studio is up to 5.4 times faster than on a MacBook Pro with M1 Max and up to 3 times faster than a MacBook Pro with M5 Max.  

• AI video enhancement in Topaz Video is up to 3.5x faster than on a MacBook Pro with M4 Max.  

Improved Storage Speed and Longer Standard Storage 

The new MacBook Pro achieves up to double the read and write speeds of the previous generation, reaching up to 14.5 GB/s in storage benchmarks. This speed assists professionals handling 4K and 8K video content and large data sets. The M5 Pro includes 1 TB of storage, the M5 Max offers 2 TB, and the 14-inch M5 starts at 1 TB.  

More Reasons To Upgrade 

Upgrade now to the new 14 and 16-inch MacBook Pro with M5 Pro or M5 Max for a serious performance boost over older MacBook Pro models, whether you have Apple Silicon or Intel.  

• With neural accelerators in the GPU, users upgrading from M1 models will see up to eight times faster AI performance in benchmark workloads.  

• Exceptional Battery Life: The new MacBook Pro delivers up to 24 hours of battery life, giving Intel-based upgraders up to 13 additional hours and users coming from M1 models up to 3 more hours, so they can get more done on a single charge. Unlike many PC laptops, the MacBook Pro delivers the same incredible performance whether plugged in or running on battery power. Users will be able to fast-charge up to 50% in just 30 minutes with a USB-C power adapter rated at 96 W or higher.  

• Upgraders will enjoy the Liquid Retina Pro Display, which offers 1600 nits of peak HDR brightness, up to 1000 nits for HDR content, and a Nano Texture option. The new MacBook Pro offers a range of connectivity options, including: three Thunderbolt 5 ports for fast data transfer, HDMI with support for up to 8K resolution, an SDXC card slot for quick media input, MagSafe 3 for fast charging with M5 Pro, You can connect up to two high-resolution external displays, each with M5, up to 4, giving you the flexibility to set up a larger workspace.  

• Thanks to the Apple M1 chip, Wi-Fi 7, and Bluetooth 6, you get better performance and more reliable wireless connections.  

• The new MacBook Pro features a 12MP Center Stage camera with desk-view support and studio-quality microphones, so you’ll look and sound your best on calls. You’ll also enjoy an immersive six-speaker sound system with special audio support.  

An Outstanding Experience With macOS Tahoe 

MacOS Tahoe brings new features to MacBook Pro that boost productivity :   

• Spotlight now makes it easier to find apps and files and take action right from the search bar.  

• Apple’s intelligence is more powerful and better protects your privacy.  

• Shortcuts are smarter, letting you use Apple intelligence models directly.  

• Live translation built into messages, FaceTime, and the phone app helps you communicate across languages by translating text and audio.  

• Developers can add Apple intelligence features to their apps or use the core models framework for on-device intelligence tasks.  

• Continuity features include the phone app on Mac, which lets you relay calls from your phone and live activities from your iPhone so you can keep up with live updates.  

• macOS Tahoe also introduces a new design with Liquid Retina and more ways to personalize your Mac, including an updated Control Center with new color options for folders, app icons, and widgets.  

MacBook Pro And The Environment 

The MacBook Pro was designed with the environment in mind and helps Apple move closer to its goal of being carbon-neutral by 2030. It uses 45% recycled materials, including 100% recycled aluminum for the enclosure and 100% recycled cobalt for the battery. Half of the electricity used in its manufacturing comes from renewable sources, including wind and solar.  

The new MacBook Pro is built to last, is easier to repair, and offers strong software support, all while meeting Apple’s standard energy efficiency and safer materials. Its packaging is made entirely from fiber and is easily recyclable.

Source: Apple introduces MacBook Pro with all‑new M5 Pro and M5 Max, delivering breakthrough pro performance and next-level on-device AI

We are acquiring Promptfoo, an AI security platform enabling businesses to identify and address vulnerabilities in their AI systems during development.  

As companies start using AI co-workers in daily work, evaluation, security, and compliance are essential. Businesses need reliable ways to test agent behavior, spot risks before launch, and help clear records for supervision and accountability.  

Led by Ian Webster and Michael DeAngelo, the Promptfoo team has built strong tools. More than 25% of Fortune 500 companies use them. The company also offers a popular open source CLI and library for testing LLM applications. We will continue investing in and supporting the open-source project. Ongoing updates and community involvement will continue. We will also partner to improve enterprise features in Frontier.  

Promptfoo brings engineering to the evaluation, security, and testing of AI systems at scale. Their work helps businesses deploy secure and reliable AI applications. We look forward to integrating these capabilities into Frontier.  

Srinivas Narayan, CTO of B2B Applications, OpenAI  

We plan to expand multiple key features for businesses building agents on Frontier.  

• Security and safety testing will be built into Frontier. Automated checks will look for risks like prompt injections, jailbreaks, data leaks, tool misuse, and policy violations.  

• Security and evaluation will be part of the development process. Frontier will work with workflows to quickly spot, investigate, and fix agent risks. Security will be a key part of building and running enterprise AI systems.  

• Frontier will include built-in reporting and traceability for documentation monitoring and compliance.  

Promptfoo was created to provide developers with practical advice on securing AI systems. This is important as agents connect to real data and systems. Ensuring their security and validation is more important than ever. By joining OpenAI, we aim to accelerate this mission. We plan to bring advanced security, safety, and governance features to teams building AI systems.  

Ian Webster, Co-Founder and CEO, Promptfoo  

We are excited to become the Promptfoo team. We will keep building the secure, reliable AI tools businesses need.

Source: OpenAI to acquire Promptfoo