Duncan Stewart’s Post

this is a rack of processors for a data center that is liquid cooled. historically , telcos have operated data centers, although not at the scale of the big cloud hyperscale players. the revolution in generative AI, especially the need for generative AI processors, means that telcos need to think about liquid cooling inside their data centers. liquid cooling is much more complex and can be difficult to retrofit. generative AI processors use roughly 10 times as much power as traditional data center chips, so liquid cooling is sometimes the only option. this happens to be a super micro solution, but there are others of course

AI, ML and GenAI are taking us from automation to autonomous networks, and from closed to open networks. And yet the transformation goes well beyond tools like AI, ML and GenAI, and encompasses culture, skills and overall approach to operating our increasingly complex networks. I had the pleasure of going through all these topics (and a few more) with Brandon Larson, who is working on the transition to autonomous and open networks at Mavenir, working on new products and listening to operators and partners. If you did not join the live #SparringPartners, you can listen to it now: https://lnkd.in/e2pgNU55 #automation #5G #openRAN #ORAN #cloud #virtualization #disaggregation #Ai #GenAI #ML #RAN #openran #autonomousnetworks #autonomous

The connection between accelerated computing and operational efficiency is indisputable. It’s not just the obvious things like how fast projects get completed or products get to market when AI is used. It’s also the impact of AI on data center efficiency… we’re talking about savings on things like hardware, energy, floor space and operating costs. It may not be intuitive, but getting AI systems to run faster actually makes data centers more energy- and cost-efficient – on-premises and in the cloud. Read more about harnessing accelerated computing for AI and LLM's 👉 https://bit.ly/4a6zqNs #AcceleratedComputing #GPU #LLM

We covered a lot of territory in this conversation breaking down Autonomous networks, the difference between Automation & AI, how to apply ML to Telco and the new skillsets and culture needed.

We’re making #AI a reality for every ambition 🤩 Unlock the potential of generative AI applications through the new integration between NVIDIA NIM Agent Blueprints and Cisco’s AI solutions. The full story 👇🏼 http://cs.co/6040WeAcs Cisco Data Center and Cloud

We’re making #AI a reality for every ambition 🤩 Unlock the potential of generative AI applications through the new integration between NVIDIA NIM Agent Blueprints and Cisco’s AI solutions. The full story 👇🏼 http://cs.co/6040qAhmO Cisco Data Center and Cloud

We’re making #AI a reality for every ambition 🤩 Unlock the potential of generative AI applications through the new integration between NVIDIA NIM Agent Blueprints and Cisco’s AI solutions. The full story 👇🏼 http://cs.co/6049orYXP Cisco Data Center and Cloud

When the question is, “What’s next in technology?” The answer is #HPEDiscover 2024. 💡 HPE President and CEO Antonio Neri, and NVIDIA Founder and CEO Jensen Huang, will share a big announcement during a groundbreaking keynote on June 18. Save your seat now. #HPEDISCOVER #DISCOVER2024 #AI #HPE #GPUS #NVIDIA #GENERATIVEAI Marc Domenech

Unleash the power of your proprietary Telco data models with Unacast Turbine! Create new internal insights, sell innovative products, and drive the AI-driven future. Unacast Turbine anonymizes user trace records with speed and scale on Google Cloud, transforming them into valuable population behavioral patterns. By blending your privacy-safe data with our AI and machine learning, Telcos can optimize operations or package information into groundbreaking solutions for new revenue opportunities. Learn more here: https://bit.ly/3AZooNv #Turbine #GoogleCloud #Telco #Data #MachineLearning #AI #Unacast

Embedded AI prioritizes privacy and real-time processing by handling data locally, ideal for sensitive or instantaneous decision-making applications, but it may be relatively limited by hardware constraints and scalability challenges. On the other hand, Cloud computing offers vast computational resources and scalability, facilitating access to advanced AI models and accommodating fluctuating demands, yet it raises concerns over privacy, security, and reliance on stable internet connectivity.  Grape Up & Addepto