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This comprehensive analysis demonstrates that systems with two 64-core Intel® Xeon® processors can effectively support enterprise-scale RAG deployments, handling up to 32 concurrent users with optimized configurations that comply with targeted SLAs. These results validate Intel® Xeon® as a viable foundation for production of RAG systems, offering operational simplicity and cost-effective scaling for enterprise workloads by eliminating GPU dependencies and reducing infrastructure complexity.

Small Language Models (SLMs) are emerging as the nimble, quick-thinking counterparts to LLMs providing specialized knowledge in a way that is lean, fast and cost-effective.

Explore how Agentic AI is reimagining enterprise workflows, industry processes, and leadership priorities with Baris Sarer, Global AI Leader for the Technology, Media, and Telecommunications (TMT) Industry at Deloitte.

This blog will introduce a new Intel® AMX Detection Tool that tells you when your platform supports AMX and whether your OS has enabled it.

For Falcons.AI COO Bobbi Stattelman, the future of AI isn’t about chasing the next breakthrough at any cost—it’s about building solutions that make the world safer, easier to navigate, and more sustainable. In a landscape crowded with massive models and cloud-heavy architectures, Falcons.AI is proving that impact comes from focusing on real problems, not hype.

The next era of robotics innovation is already here…are you ready? 

The robotics industry is at an inflection point. While robots have long been deployed for narrow, repetitive functions or single tasks, they are evolving into multi-capable systems powered by physical AI that engage with the world around them in complex ways. These systems perceive their environments, adapt to changes, and can collaborate with humans or other machines. 

For innovation integrators exploring this emerging reality, the opportunity is significant — but so are the challenges. To successfully deploy advanced robotics, organizations must ensure interoperability, manage skills gaps, and maintain stringent security throughout operations at the edge. Intel brings its longstanding robotics investments and expertise together, to help simplify this path.  

The newly launched Intel® Robotics AI Suite offers a curated, industry-focused, collection of reference applications, qualified AI hardware systems, acceleration libraries, benchmarking tools, and microservices that help organizations fast track and evaluate physical AI workloads for robotics.  Fully integrated with Intel® Core™ Ultra processors, the Robotics AI Suite enables organizations to predict and plan innovation across robotics use cases with affordable scalability. 

Accelerate robotics deployment with the Intel® Robotics AI Suite 

The Robotics AI Suite empowers organizations to adapt new AI capabilities to develop features and realize faster returns on investment with these core components: 

Reference applications that show how capabilities like perception, locomotion, manipulation, and imitation learning can be applied in practice. Streaming media analytics pipelines to gather inputs from sensors and multi-cameras to enable spatial intelligence. Advanced AI Algorithms for object detection and motion and task planning. Vision-Language Models optimized to accelerate AI inference with video and text inputs to provide context. 

Teams can evaluate, adapt, and scale robotics solutions with less risk and a clearer view of performance requirements and costs. Companies who do not have a good sense of which AI model to choose for their robotics project and wonder which CPU and GPU will be most efficient can try out the Robotics AI Suite, Open Edge Platform, and OpenVINO™ to see exactly how physical AI workloads perform. Using robotics reference applications, performance and benchmarking tools, robot builders can qualify AI hardware systems to achieve repeatable, scalable performance, and sustain optimal efficiency at scale. 

Optimize performance with the Intel® Core™ Ultra processors   

Broadly speaking, modern robots contain two essential halves. One is the real-time control system that moves the joints and ensures safe, precise timing. The other is the vision and AI perception side that allows a robot to see and understand its environment to make decisions about how to move around in it. 

Traditionally, these two halves would have been managed by separate processors, sometimes from different companies and with different software stacks. According to Matthew Formica, Senior Director and Head of Edge Product Marketing & AI PC/Edge AI Software Developer Relations at Intel, this is changing.  

“You’re seeing the latest processors from Intel be able to handle both the real-time controls capability and enough AI processing to do the vision and AI perception half, all in one processor,” Formica explained on the Intel on AI podcast. “So, it makes it much simpler for a robot designer to build with one part to lower costs and reduce complexity, cut development time, and ship robot innovation to market faster and more cost-effectively than they could before.  

Formica says this new wave of hardware innovation, including Intel® Core™ Ultra processors (series 2) is challenging the industry’s perception of what robots should cost, enabling new innovations across different robot types. “Suddenly, things that were not affordable to do before become cost effective to think about realistically doing it,” he said. 

On top of processor performance, Intel adds technological innovations like Time Coordinated Computing (TCC) to further optimize performance by prioritizing real-time workloads’ access to cache, memory, and networking resources to support high availability for robotics systems across distributed edge deployments. 

Partnering to accelerate physical AI with Intel 

Intel, from the beginning, has recognized the value of going to market with an innovative, open ecosystem and cultivates broad partnerships with ODMs, OEMs, and ISVs to support robotics on x86. Global hardware and software partner integrations provide alternatives for deploying robotics solutions that deliver long term affordability and scalability, and a legacy of expertise to build robotics on. Partner contributions to the Robotics AI Suite include integrations for multi-camera and sensor inputs that enable precise perception and object detection. Software extends functionality for the ROS 2 framework to adapt locomotion. Hardware builders partnering with Intel integrate best-known configurations for AI systems qualified on Intel silicon to power the next generation of robotics. The Robotics AI Suite is updated with quarterly releases on the GitHub open-source community for builders to adapt. Backed by a predictable roadmap of silicon innovation, Robotics innovators can confidently plan features that scale.  

Here is what robotic partners and suppliers have to say about collaborating with Intel: 

“Our collaboration with Intel is all about helping robotics companies move faster—from idea to product. With Intel’s robotics expertise, AI suite, and pre-validated support for RealSense™ Depth Cameras like the D435, D457, and D555, we’re making it easier to innovate, scale, and accelerate the adoption of physical AI.” 
-Nadav Orbach, CEO, RealSense 

“Our strategic partnership with Intel reflects our shared commitment to advancing Physical AI for next-generation manufacturing. By integrating Intel’s all-in-one compute platform and Robotics AI Suite with Techman Robot’s industry-leading AI-vision-integrated collaborative robots, we accelerate deployment and enhance flexibility in real-world factory applications. Together, we make Physical AI more accessible and impactful for industries such as semiconductor, electronics, and smart manufacturing.” 
-Scott Huang, COO, Techman Robot 

“Fourier is thrilled to partner with Intel to advance the frontier of embodied AI. We look forward to the launch of Robotics AI Suite will extend this partnership between Intel and Fourier to deliver efficient, scalable solutions for real-world deployment.” 
-Willys Zhai, Vice President, Fourier 

A simpler, easier way to accelerate robotics innovation 

With a foundational toolkit to quickly develop and scale up robotics solutions, innovators can focus on their most ambitious robotics plans with a tangible, predictable TCO and get beyond start-up challenges with a predictable and scalable path to operationalize functionalities for all kinds of robots. 

The Robotics AI Suite empowers every organization to move faster, scale smarter, and imagine robotics in ways that were not affordable or realistic before. Here are a few possible outcomes using the suite: 

Shorten development cycles by reusing tested code for core robotics functions such as perception or motion planning.
Reduce up-front costs by validating workloads with community-driven benchmarks before committing capital to hardware or custom R&D.
Integrate seamlessly with open solutions, minimizing complexity and proprietary lock-in.
Scale with confidence by extending modular, non-proprietary components across new robots, environments, or use cases without re-architecting from scratch.
Deploy securely with hardware- and software-based security features, including support for functional safety requirements and near zero-touch manageability. 

This is just the beginning for the Robotics AI Suite, with more functionality coming to build the next wave of modern robots powered by Intel® Core™ Ultra processors. Try it out today! 

Discover Intel’s Robotics AI Suite  https://intel.ly/AI-robotics 

Learn more about Intel AI Suites: https://www.intel.com/content/www/us/en/software/edge-platform-industry.html 

Highlights

GLEVR, a new graph-based AI framework from Intel and University of Colorado researchers, achieves more than 12% improvement in recognizing fine-grained keystep actions in first-person videos and wins the Ego-Exo4D keystep recognition challenge at CVPR 2025.The system leverages multiple camera viewpoints during training but only needs a single egocentric camera during actual use, making it practical for real-world applications such as smart assistants and training systems.By representing video clips as connected nodes in a graph structure, the framework efficiently captures long-term patterns in activities while remaining computationally lightweight.

The article highlights how Intel® AI for Enterprise RAG enables oversight through tools for tracing data flow, performance telemetry, and log analysis. Happy to announce that the Intel® AI for Enterprise RAG version 1.5.0 has just been released.

From hospital corridors to classroom desks, artificial intelligence is doubling its capabilities every six months—but the real breakthrough isn’t in what AI can do, it’s in how we’re finally making it work responsibly for real people.