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Cisco Reimagines Security for Data Centers and Clouds in Era of AI 

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News Summary:
Cisco powers and secures AI-scale data centers and clouds, safeguarding every application and device regardless of distribution or connectivity.

  • In today’s highly distributed landscape, the window from vulnerability to exploitation is shrinking rapidly.
  • Defending against this complex threat environment is beyond human scale.
  • Cisco Hypershield enables customers to deploy security wherever needed: in the cloud, data center, factory floor, or hospital imaging room.
  • With AI-native security, customers can autonomously segment networks, enjoy distributed and instant exploit protection without patches, and experience self-qualifying software upgrades with zero downtime.

News in Detail:
Cisco, the leader in security and networking, today unveiled a radically new approach to securing data centers and clouds in response to the increasing demands the AI revolution has put on IT infrastructure. Cisco is rearchitecting how we harness and protect AI and other modern workloads with industry-first, Cisco Hypershield. With this unprecedented innovation, Cisco is tipping the scales in favor of defenders, building on its recent announcements to accelerate AI infrastructure with Cisco’s ethernet switching, silicon and compute portfolio.

Cisco Hypershield protects applications, devices and data across public and private data centers, clouds and physical locations – anywhere customers need it. Designed and built with AI in mind from the start, Hypershield enables organizations to achieve security outcomes beyond what has been possible with humans alone.

“Cisco Hypershield is one of the most significant security innovations in our history,” said Chuck Robbins, Cisco Chair and CEO. “With our data advantage and strength in security, infrastructure and observability platforms, Cisco is uniquely positioned to help our customers harness the power of AI.”

Hypershield is a revolutionary new security architecture. It’s built with technology originally developed for hyperscale public clouds and is now available for enterprise IT teams of all sizes. More a fabric than a fence, Hypershield enables security enforcement to be placed everywhere it needs to be. Every application service in the datacenter. Every Kubernetes cluster in the public cloud. Every container and virtual machine (VM). It can even turn every network port into a high-performance security enforcement point, bringing completely new security capabilities not just to clouds, but to the data center, on a factory floor, or a hospital imaging room. This new technology blocks application exploits in minutes and stops lateral movement in its tracks.

“AI has the potential to empower the world’s 8 billion people to have the same impact as 80 billion. With this abundance, we must reimagine the role of the data center – how data centers are connected, secured, operated and scaled,” said Jeetu Patel, Executive Vice President and General Manager for Security and Collaboration at Cisco.

“The power of Cisco Hypershield is that it can put security anywhere you need it – in software, in a server, or in the future even in a network switch. When you have a distributed system that could include hundreds of thousands of enforcement points, simplified management is mission critical. And we need to be orders-of-magnitude more autonomous, at an orders-of-magnitude lower cost.”

Security enforcement with Hypershield happens at three different layers: in software, in virtual machines, and in network and compute servers and appliances, leveraging the same powerful hardware accelerators that are used extensively in high-performance computing and hyperscale public clouds.

Hypershield was built on three key pillars:

AI-Native: Built and designed from the start to be autonomous and predictive, Hypershield manages itself once it earns trust, making a hyper-distributed approach at scale possible.
Cloud-Native: Hypershield is built on open source eBPF, the default mechanism for connecting and protecting cloud-native workloads in the hyperscale cloud. Cisco acquired the leading provider of eBPF for enterprises, Isovalent, earlier this month.
Hyper-Distributed: Cisco is completely reimagining how traditional network security works by embedding advanced security controls into servers and the network fabric itself. Hypershield spans all clouds and leverages hardware acceleration like Data Processing Units (DPU) to analyze and respond to anomalies in application and network behavior. It shifts security closer to the workloads that need protection.

Cisco, with its industry-leading expertise in networking, security and extensive partner ecosystem, together with NVIDIA, is committed to building and optimizing AI-native security solutions to protect and scale the data centers of tomorrow. This collaboration includes leveraging the NVIDIA Morpheus cybersecurity AI framework for accelerated network anomaly detection, as well as NVIDIA NIM microservices for powering custom security AI assistants for the enterprise. NVIDIA’s class of converged accelerators combine the power of GPU and DPU computing, to augment Cisco Hypershield with robust security from cloud to edge.

“Enterprises across all industries are seeking the security that can protect them against ever expanding cyber threats,” said Kevin Deierling, Senior Vice President of Networking at NVIDIA. “Together, Cisco and NVIDIA are leveraging the power of AI to deliver powerful, incredibly secure data center infrastructure that will enable enterprises to transform their businesses and benefit customers everywhere.”

As a revolutionary new security architecture, Hypershield is solving three key customer challenges in defending against today’s sophisticated threat landscape:

Distributed Exploit Protection: Attackers are adept at weaponizing newly published vulnerabilities faster than defenders can patch. With defenders seeing nearly 100 new vulnerabilities every day, according to Cisco Talos Threat Intelligence, this can lead to catastrophic results. Hypershield delivers protection in minutes by automatically testing and deploying compensating controls into the distributed fabric of enforcement points.
Autonomous Segmentation: Once an attacker is in the network, segmentation is key to stopping their lateral movement. Hypershield perpetually observes, auto-reasons and re-evaluates existing policies to autonomously segment the network, solving this in large and complex environments.
Self-qualifying Upgrades: Hypershield automates the incredibly laborious and time-consuming process of testing and deploying upgrades once they are ready, leveraging a dual data plane. This completely new software architecture allows software upgrades and policy changes to be placed in a digital twin that tests updates using the customer’s unique combination of traffic, policies and features, then applying those updates with zero downtime.

Built into the Security Cloud, Cisco’s unified, AI-driven, cross-domain security platform, Cisco Hypershield is expected to be Generally Available in August 2024. With Cisco’s recent acquisition of Splunk, customers will gain unparalleled visibility and insights across their entire digital footprint for unprecedented security protection.

“AI is not just a force for good but also a tool used for nefarious purposes, allowing hackers to reverse engineer patches and create exploits in record time. Cisco looks to address an AI enabled problem with an AI solution as Cisco Hypershield aims to tip the scales back in favor of the defender by shielding new vulnerabilities against exploit in minutes – rather than the days, weeks or even months as we wait for patches to actually get deployed,” said Frank Dickson, Group Vice President, Security & Trust at IDC. “With the number of vulnerabilities ever increasing and the time for attackers to exploit them at scale ever decreasing, it’s clear that patching alone can’t keep up. Tools like Hypershield are necessary to combat an increasingly clever malicious cyber adversary.”

“Cisco Hypershield takes aim at the complex security challenges of modern, AI-scale data centers. Cisco’s vision of a self-managing fabric that seamlessly integrates from the network to the endpoint will help redefine what’s possible for security at scale,” said Zeus Kerravala, Founder and Principal Analyst of ZK Research. “For instance, this level of visibility and control across a hyper-distributed environment prevents lateral movement of attackers, enabled through a unique approach to segmentation that’s autonomous and highly effective. While this may seem fantastical, the time is right given recent AI advances combined with the maturity of cloud-native technologies like eBPF.”

“At AHEAD we believe cybersecurity should be integrated into everything we do. Bolted-on security is more expensive and less effective,” said Steven Aiello, Field Chief Information Security Officer at AHEAD. “Cisco Hypershield ensures that cyber protections are included into the fabric of the enterprise. Distributed Exploit Protection will be a massive win for blue teams – legacy synthetic patching was primarily limited to edge devices, allowing lateral movement once an attacker breached the perimeter. It’s a great day for cyber-defenders!”

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Intel Core Series 3 Extends AI-Ready Performance to Value and Edge Computing Segments

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Intel has introduced its latest Intel Core Series 3 mobile processors, aimed at expanding advanced computing capabilities to value buyers, commercial users, and essential edge deployments.

The launch reflects a broader shift in the industry, where performance, efficiency, and AI readiness are no longer confined to premium systems but are increasingly expected across all tiers of computing.

Built on the architectural foundations of Intel’s newer Core platforms and leveraging advanced process technology, the Core Series 3 processors are designed to deliver a balanced combination of performance, battery efficiency, and scalability. The focus is on enabling reliable, everyday computing while supporting emerging workloads, including AI-driven applications.

Driving Value-Oriented Performance

Intel positions Core Series 3 as a significant upgrade path for users operating on older systems. Compared to five-year-old PCs, the new processors deliver up to 47% improvement in single-thread performance and up to 41% gains in multi-thread workloads. GPU-based AI performance also sees notable enhancements, enabling improved responsiveness in modern applications.

This performance uplift is complemented by a strong emphasis on efficiency, with reduced processor power consumption and optimisations aimed at extending battery life for mobile systems.

AI Capability Moves to the Mainstream

One of the key differentiators of the Core Series 3 platform is the introduction of hybrid AI-ready architecture within the value segment. With support for up to 40 platform TOPS, Intel is enabling a new class of systems capable of handling AI workloads at the device level.

The platform also integrates modern connectivity standards, including Thunderbolt 4, Wi-Fi 7, and Bluetooth 6, ensuring compatibility with next-generation peripherals and networks.

Expanding into Essential Edge Deployments

Beyond traditional laptops, Intel is positioning Core Series 3 as a scalable solution for edge computing environments. The processors are designed to support a wide range of applications, including robotics, smart buildings, retail systems, and industrial deployments.

By combining AI acceleration with energy efficiency, the platform aims to deliver the performance required for real-time processing while maintaining operational reliability in diverse environments.

Ecosystem and Availability

Intel expects broad adoption across the ecosystem, with more than 70 designs from OEM partners set to launch across multiple form factors. Consumer and commercial systems powered by Core Series 3 are rolling out through 2026, while edge-focused deployments are expected from Q2 onwards.

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62% OF SAUDI LEADERS ARE FAILING TO USE THEIR DATA EFFECTIVELY, NEW CLOUDERA REPORT FINDS

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Cloudera, the only company bringing AI to data anywhere, today released its latest global survey, The Data Readiness Index: Understanding the Foundations for Successful AI, examining how prepared enterprises are to support AI at scale. Surveying more than 300 IT leaders in the EMEA region, including strong insights from Saudi Arabia, the report finds that while AI adoption is growing, most organizations still lack the data foundation needed for success.

The findings highlight a sharp contrast in how effectively organizations track their data. Nearly 9 in 10 EMEA  IT leaders claim complete visibility into where all their data resides, compared to just 32% of respondents in Saudi Arabia. Furthermore, 62% of Saudi respondents cite data access restrictions as a major roadblock to effective data use.

This gap highlights an emerging ‘AI readiness illusion’: the belief that organizations are prepared to scale AI even as critical data challenges remain unresolved.

“Enterprises aren’t struggling to adopt AI, they’re struggling to operationalize it beyond experiments,” said Sergio Gago, Chief Technology Officer at Cloudera. “AI is only as effective as the data that fuels it. Without seamless access to all their data, organizations limit the accuracy, trust, and business value that AI can deliver. You can’t do AI without data.”

AI Adoption is High, but ROI Remains Elusive

While AI is now deeply embedded across the enterprise, achieving consistent returns on investment remains difficult due to a sharp geographical divide in implementation hurdles. Across EMEA, the struggle is largely centered on the inputs, with data quality issues (18%) and cost overruns (16%) cited as the primary causes of lackluster ROI. However, Saudi Arabia presents a different challenge focused on execution. In the Kingdom, weak integration into workflows is the overwhelming barrier at 29%, nearly doubling the concern over data quality, which sits at 15%.

These regional nuances are further tangled by significant infrastructure limitations. Around 65% of respondents in KSA report that performance constraints have hindered operational initiatives, highlighting the immense difficulty of scaling AI across fragmented environments.

Bridging The Data Gap

At the core of these challenges is a significant disconnect between data optimism and operational reality.

The report highlights that 95% of KSA respondents are highly confident in their data, but only 32% of that data is currently fully governed. While this outpaces the broader EMEA region, where only 26% of data is governed despite 91% confidence, it highlights a critical execution gap that organizations are now racing to fill.

The Kingdom is uniquely positioned to bridge this divide with 100% of Saudi respondents ready to adopt new governance frameworks, and 79% being extremely willing to transform their operations. This regional commitment suggests that Saudi Arabia’s proactive approach will likely outpace its peers in the race toward AI and digital maturity.

Strategic Alignment and the Accountability Gap

While leadership in both the EMEA and KSA regions understands the necessity of data infrastructure, the execution and accountability frameworks are worlds apart. More than 90% of EMEA respondents report a well-defined data strategy tied directly to business objectives, while only over half  (53%) of Saudi Arabian respondents feel the same level of alignment.

Accountability and internal culture further widen this divide. In EMEA, 69% of leaders hold the CIO or CTO chiefly responsible for data readiness, whereas in Saudi Arabia, only 35% place ultimate responsibility on this role, indicating a more emerging ownership structure.

Beyond accountability and alignment, respondents in Saudi Arabia face a unique internal hurdle: 50% struggle with insufficient data literacy, while nearly a third (32%) cite a lack of executive sponsorship.

Data Readiness Will Define the Next Phase of Enterprise AI

As enterprise AI shifts from experimentation to execution, data readiness is emerging as the defining factor separating leaders from laggards.

Organizations able to fully access and govern all their data, wherever it resides, are far better equipped to deliver trusted, scalable AI. Notably, every respondent in the report indicated their organization is willing to adapt existing frameworks to support true data readiness.

As enterprises confront the limits of the AI readiness illusion, the path forward is clear: unlocking AI’s full value will require more than ambition; it will demand genuine data readiness. Those that close this gap will be best positioned to drive lasting impact and lead the next era of intelligent business.

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OPTRO LAUNCHES AI-POWERED GRC CAPABILITIES FOR THE MODERN ENTERPRISE WITH AI GOVERNANCE, CYBER RISK, AND CONTINUOUS CONTROL MONITORING

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Optro, the leading AI-powered GRC platform empowering enterprises to transform risk into opportunity, has announced several product capabilities to boost the effectiveness of customers’ risk management programs and enable them to innovate with AI confidently and responsibly. These capabilities follow shortly after the company changed its name to reflect what its AI-powered GRC platform enables: a single, coherent view across infosec, compliance, risk, and audit.

“Cyber risk now moves at machine speed, and legacy GRC tools can no longer keep up,” said Happy Wang, Chief Product and Technology Officer at Optro. “By leveraging AI to predict cyber risk, surface real-time insights, and accelerate mitigation, we help organizations shift from reactive reporting to proactive risk defense—building a true system of action that is ready for the AI era.”

Optro’s latest Risk Intelligence report found that AI governance program maturity is advancing, but unevenly. AI adoption continues to outpace AI governance, with 85 percent of organizations reporting they have integrated AI into their core operations or deployed it across multiple functions, while only a quarter report comprehensive visibility into employee AI use. At the same time, only 34 percent of organizations report their AI governance program is strategic and continuously improving. As these challenges become increasingly prevalent across industries, Optro has released the following product capabilities to help customers turn clarity into action:

  • Unified AI Governance: Serves as the essential orchestration layer for AI governance. By bridging the gap between policies & frameworks, your AI tech stack, and human oversight, this capability enables a unified, automated approach. We ensure that AI risks are visible, compliance is streamlined, and governance policies are enforceable across your entire organization.
  • Cyber Risk: Vulnerability Risk Monitoring: Provides a clear narrative of how a specific vulnerability affects an organization’s security posture and bottom line. This AI-powered functionality enables customers to understand the true business impact of a vulnerability. Included with IT and Cyber Risk Management (formerly IT Risk Management), it’s a paradigm shift in how organizations defend their digital perimeter.
  • Continuous Control Monitoring: With AI-driven recommendations for the controls best suited for automation, and a library of ready-to-use monitor templates, teams can bypass manual setup to start monitoring controls immediately. This capability helps customers reduce manual effort, improve consistency, and gain more timely visibility into control performance. By automating evidence collection and surfacing potential issues earlier, teams can address gaps more efficiently and move toward a more continuous approach to assurance.
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