Mary Bentley’s Post

In today's fast-paced business world, quick resolutions are crucial. Complex computational issues require powerful solutions, and High-Performance Computing (HPC) is the answer. From semiconductors to healthcare, industries are leveraging HPC to gain insights faster, manage risks, and bring products to market swiftly. Why HPC? ✅ Accelerate data analysis and AI ✅ Enhance scalability and flexibility ✅ Improve cost-efficiency and agility Embrace HPC to solve your toughest challenges! #HybridCloud #HPC #IBMCloud

Is a pivot from dependence on centralized server architecture to a distributed alternative inevitable. I think so. Cloud computing is not a novel innovation. IBM built an enormous business, decades ago, (as did several of its competitors, Burroughs, NCR, etc) on "timesharing" compute infrastructure provided by "mainframe" computers. But the debut of a personal computer, in the early 1980s (back then I owned an Osborne 1, packed up the device resembled a Singer Sewing Machine) kicked off perhaps a pivot bigger than today's pivot to humanlike communication software. Scott Lyon's press release, "New chip built for AI workloads attracts $18m in government support" gets me thinking a pivot to broadly distributed compute and storage architecture is on the horizon: #edgecomputing #distributedcomputing #aiinfrastructure https://lnkd.in/eSBCuU_9

Microsoft introduces Azure Maia, an innovative series aimed at advancing AI infrastructure #AI #AIinfrastructure #artificialintelligence #AzureMaia #Electronics #llm #machinelearning #Maia100 #Microsoft #Scalability #semiconductortechnology #Sustainability #Techgiants

#Baremetal as a service plays a significant role in #AI by providing dedicated physical servers to AI practitioners and researchers without the overhead of managing hardware infrastructure. Here's how Bare Metal as a Service (#BMaaS) contributes to AI initiatives: 1. High Performance: #BMaaS offers direct access to physical hardware, enabling AI workloads to leverage the full computational power of #CPUs and #GPUs without the performance penalties associated with virtualization layers. 2. Customization: #BMaaS providers allow users to customize server configurations based on their specific AI requirements, including the choice of CPUs, GPUs, memory, and storage options. This flexibility enables users to tailor the infrastructure to their exact needs, optimizing performance and cost-effectiveness. 3. Scalability: #BMaaS platforms provide on-demand access to a scalable pool of physical servers, allowing AI practitioners to quickly scale up or down based on workload demands. This is particularly beneficial for AI projects that require large-scale parallel processing or training of deep learning models. 4. Resource Isolation: With dedicated physical servers, BMaaS ensures that AI workloads have exclusive access to hardware resources, minimizing performance fluctuations and ensuring consistent performance even under heavy workloads. 5. Data Privacy and Security: #BMaaS solutions offer enhanced data privacy and security compared to shared virtualized environments. Since each user has dedicated hardware, there is a lower risk of data leakage or unauthorized access, making BMaaS suitable for handling sensitive AI datasets and models. Cost Efficiency: While bare metal servers typically involve higher upfront costs compared to virtualized solutions, BMaaS providers often offer flexible pricing models, including pay-as-you-go or subscription-based plans. This allows AI practitioners to optimize costs based on their usage patterns and budget constraints. Overall, BareMetal as a Service plays a crucial role in supporting AI initiatives by providing high-performance, customizable, scalable, and secure infrastructure for running compute-intensive AI workloads. It enables AI practitioners to focus on developing and deploying advanced AI models without the burden of managing underlying hardware infrastructure. For more information, contact at parmeet@arrowpc.co.in

🔍 Exploring the Backbone of the AI Revolution 🔍 Artificial intelligence is transforming industries worldwide, driven by powerful AI servers. These servers, equipped with cutting-edge GPUs and advanced technology, handle complex data processing at lightning speed. They're powering AI research and enabling real-world applications across sectors like healthcare, finance, and manufacturing. #AI #ArtificialIntelligence #TechInnovation #AIInfrastructure

How AI is Revolutionizing Data Centers: Hope and Hype for the Future ! The data center market has been dominated by a select few so called 'Super 7' for the past decade, but the rise of heterogeneous computing is changing the game. With specialized computing environments requiring hardware like GPUs and TPUs, AI-powered systems are on the horizon. Imagine 'AI factories,' specialized data centers designed for training and deploying AI models with unmatched efficiency and speed. But that's not all. Unaligned cloud service providers are emerging, offering businesses greater flexibility and control over their data and workloads. As the data center market evolves, it will be fascinating to see how these trends play out and what groundbreaking innovations emerge. Stay tuned! #DataCenter #AI #CloudComputing #Innovation

As demand for chips continues to surge from AI and cloud computing advances, the Canadian and Quebec governments are partnering with IBM to solidify the future of the chip supply chain in North America by advancing the assembly, testing, and packaging capabilities at IBM's plant in Bromont, Quebec. “Semiconductors power the world, and we’re putting Canada at the forefront of that opportunity,” said Canadian Prime Minister Justin Trudeau. Demand for computing resources has surged as we enter the age of AI, IBM’s Senior Vice President and Director of Research Dario Gil said. But rising to the moment is something IBM Research does. “IBM has long been a leader in semiconductor research and development, pioneering breakthroughs to meet tomorrow’s challenges. said Gil “As one of the largest chip assembly and testing facilities in North America, IBM's Bromont facility will play a central role in this future.” “We are proud to be working with the governments of Canada and Quebec toward those goals,” Gil added, "To build a stronger and more balanced semiconductor ecosystem in North America and beyond.” Click below to read more. https://lnkd.in/ghe8NQUs

AI will remake data centers, OCP says: The Open Compute Project (OCP), an industry initiative focused on redesigning hardware for growing infrastructure demands, has turned its focus to the hardware requirements of artificial intelligence, anticipating a massive impact. A key emphasis is  liquid-cooled data centers, with OCP board member and Sun Microsystems co-founder Andy Bechtolsheim among the chief proponents. At this week’s OCP Global Summit in San Jose, CA, the topic of what AI will mean for computer hardware took center stage. “(AI) is not a trend but a major shift in the way technology is going forward to impact our lives,” said OCP Board Chair Zaid Kahn, general manager of Microsoft’s silicon, cloud hardware, and infrastructure engineering, during a keynote presentation. Kahn predicted that AI will drive tremendous rounds of investment in IT infrastructure and data center buildout in the very near future. To read this article in full, please click here #MachineLearning #ArtificialIntelligence #DrivenByData #AI #NetworkIntelligence #IIot #CTO #DataDriven

If you want sustainable innovation, you need a rock-solid foundation. Backing up every AI capability or outcome is enterprise storage. Through conversations with colleagues and partners about customer priorities, we see that organizations need: - sustainability of their storage infrastructure, considering the amount of energy data centers take to power AI and other emerging technologies - cost savings as the expenses associated with powering and training artificial intelligence increase - higher performance as well as flexibility as enterprises look for easier ways to move workloads at need This makes NetApp’s recent upgrade of its AFF all-flash storage line (which already consumes less power and reduces costs) particularly exciting for partners.  NetApp’s Director for Solutions Engineering, Grant Caley, does a great job of breaking down the benefits of this new line-up for Computer Weekly.  https://ow.ly/Z9Ph50RSsxR  #AI #EnterpriseStorage

Great overview on resilience. The difference between AI workloads on traditional CPU vs GPU technology is very insightful. What I also found insightful was your take on Silent Data Errors being very hard to detect. The next step in innovating to take on these challenges is to evaluate the value In-Chip monitoring provides while going from Preventative to Predictive and Prescription monitoring for improved Reliability and Time to Failure predictions.