Graph AI Services’ Post

#AI, HCLTech and arm collaborate on custom silicon chips optimized for AI workloads HCLTech, a leading global technology company, and Arm, a leading technology provider of processor IP, announced their collaboration to augment custom silicon chips that support AI-driven business operations.   The partnership will bring to market solutions that enable semiconductor manufacturers, system OEMs and cloud services providers to enhance the computing efficiency of their data center environments and meet evolving customer demands.   HCLTech will leverage pre-integrated Arm(R) Neoverse(TM) Compute Subsystems (CSS) to help clients minimize development risks and swiftly deliver innovative, market-customized solutions geared toward improved performance and scalability for AI workloads.   HCLTech has preferential access to Neoverse CSS as a member of Arm Total Design, an ecosystem that brings together industry leaders to accelerate frictionless delivery of Arm-based custom silicon chips. This access empowers HCLTech to stay at the forefront of cutting-edge technologies designed to efficiently manage AI workloads, including meeting the future demands of data center environments.   "HCLTech's collaboration with Arm will contribute to the development of industry-leading custom AI silicon solutions that will revolutionize the way AI workloads are addressed in data center environments. Together, we look forward to spearheading technology advancement and innovation in the semiconductor industry," said Ameer Saithu, Executive Vice President, Engineering and R&D Services, HCLTech.   "Through Arm Total Design, our partners can leverage the expertise and support of other industry leaders to bring custom silicon solutions to market faster. HCLTech is a welcome addition to the ecosystem, and we are excited to see how they leverage their custom AI silicon capabilities and Arm Neoverse CSS to innovate next-generation solutions, " said Guru Ganesean, President of Arm India. #AI,#RB

Great article from Bain & Company on the total addressable market (TAM) for AI over the next three years. It highlights how AI workloads will drive the need for innovation in storage, compute, memory, and data centers, and how companies must adapt by investing in these technologies to remain competitive.

The surge in AI is revolutionizing the demand for edge computing infrastructure. This shift is a game-changer as industries and businesses prioritize processing data locally, unlocking AI's full potential without the hassles of latency and bandwidth constraints linked with remote cloud data centers. This shift marks a strategic departure from traditional cloud-centric data management, paving the way for a more distributed computing model that brings processing capabilities closer to the data sources and the users. We recently deployed our latest NEXTDC edge data centre #PH1 in Port Hedland WA to support mining, private cloud and connectivity clients like BHP, Microsoft and Vocus for this exact use case. Recent collaborations among industry giants like Intel, AWS, Nokia, and Ericsson to offer edge AI services for complex sites such as manufacturing plants and transportation hubs underscore the momentum behind this trend. These partnerships aim to seamlessly integrate edge computing with 5G networks and cloud services, providing comprehensive solutions for high-demand applications in healthcare, finance, and other sectors where rapid data processing and stringent security measures are paramount. The push towards edge computing isn't just about expanding AI's reach; it's about optimizing its efficiency and applicability in real-world scenarios. By bringing compute closer to the data source, edge AI enables more responsive and context-aware applications, amplifying the utility and impact of AI across diverse domains. As the edge computing market continues to flourish, the relationship between cloud computing, edge computing, and private 5G networks will become increasingly indispensable for organizations seeking to fully leverage the power of AI. #ai #edgecompute #digitalinfrastructure

Shaping the Future of AI with Cutting-Edge Data Center Networks powered by NOKIA! The future of AI applications relies on robust, scalable, and high-performing infrastructure. That’s why We're excited to share Nokia’s transformative solution for DC Fabric networks, which plays a crucial role in supporting the demanding requirements of AI workloads. In collaboration with industry leaders, Nokia’s DC Fabric technology delivers unparalleled scalability and flexibility, empowering organizations to deploy AI-driven applications with confidence. This innovative approach ensures seamless connectivity, high-speed data transfer, and unmatched reliability—critical components for AI training and inference at scale. Nokia’s commitment to innovation is helping redefine what's possible in modern data center networking. As AI continues to revolutionize industries, having the right network foundation will be key to unlocking its full potential. Let’s shape the future, together! #AI #DataCenter #Nokia #Innovation #Networking #FutureOfAI Read more about this exciting collaboration and the future of AI applications here: https://lnkd.in/dwnw7ayY

In today’s rapidly evolving landscape, artificial intelligence is no longer a luxury—it’s a business imperative. That’s why I’m particularly impressed with Insight’s latest innovation: AI Infrastructure-as-a-Service (AI IaaS). This offering removes the traditional barriers to entry. By simplifying the deployment and management of AI environments, Insight enables organizations to focus on driving business outcomes—without being weighed down by the complexities of infrastructure. The flexibility of Insight’s AI IaaS also ensures alignment with existing cloud strategies, allowing organizations to accelerate their AI capabilities with minimal disruption. This is the kind of forward-thinking solution that empowers businesses to harness the full potential of AI, fueling innovation and competitive advantage. #Leadership #AIInnovation #EnterpriseSolutions #DigitalTransformation #Insight #FutureOfWork Stephen Moss | Joyce Mullen | Dee Burger | Juan Orlandini | Craig Weinstein | Fredrick Nijm | Matt Collins | Megan Amdahl | Jeremy Nelson

Is your organization ready for AI? Cisco’s AI Readiness Index reveals a surprising gap: while 98% of businesses feel increasing urgency to deploy AI, only 13% are fully prepared to leverage its potential. Key challenges: Infrastructure strain: 79% need more GPUs to support future AI workloads. Data readiness: 80% report inconsistencies in pre-processing and managing data. Talent gaps: Only 31% feel equipped with the skills necessary for AI adoption. Governance hurdles: Cultural and leadership resistance to AI adoption is rising. Despite these hurdles, businesses are doubling investments, recognizing AI's long-term potential to transform operations and innovation. Preparing infrastructure, upskilling talent, and building agile strategies are critical to bridging the readiness gap. How is your organization addressing AI readiness? #AIReadiness #ArtificialIntelligence #Cisco #Innovation #DigitalTransformation #Leadership

Being cost effective is very important for long term adoption of AI stack for #enterprises, so always ask "How many chips does it take to run my workload?" before making the decision. We at #Sambanova offer #SambaNovaSuite which not only do inference at world record speed in cost effective manner, but also enable you to use your private data to train your private models. #GenerativeAI #LLMs #AIStack

5 Ways Equinix Infrastructure Supports Your AI Journey As AI continues to transform businesses across industries, having the right infrastructure is crucial for success. Equinix, a global leader in digital infrastructure, offers solutions that can significantly streamline your AI projects from development to deployment. Let's explore three practical ways Equinix's infrastructure can support your AI journey: 1. High-Performance Computing with Equinix Metal Equinix Metal provides bare metal servers on demand, perfect for computationally intensive AI workloads. Practical example: Imagine you're training a large language model. With Equinix Metal, you can quickly spin up a cluster of high-performance GPU servers, complete your training in hours instead of days, and then spin them down when you're done. 2. Hybrid and Multi-Cloud Connectivity via Equinix Fabric Equinix Fabric enables direct, private connections between your on-premises infrastructure and multiple cloud providers. Practical example: You're developing an AI-powered recommendation engine that needs to access data stored in AWS, while your model training happens on Google Cloud Platform. Equinix Fabric allows you to create low-latency, secure connections between these environments. 3. Edge Computing for Real-Time AI with Equinix Edge Services Equinix's edge computing solutions bring computation and data storage closer to the point of data generation. Practical example: Consider an AI system for autonomous vehicles. By leveraging Equinix's edge locations, you can process sensor data locally, making split-second decisions without the latency of sending data to a central cloud. Curious to learn about the other ways Equinix can support your AI journey? Visit our website for the full article, including more practical examples and insights on how Equinix's infrastructure solutions can streamline your AI projects from development to deployment. #AI #DigitalInfrastructure #CloudComputing #EdgeComputing #Equinix https://lnkd.in/efJnsYAh