How AI is transforming with Dell and AMD's hybrid strategies

AI innovation isn't just happening in LLMs, it's accelerating across the entire computing stack, from silicon to algorithms. Our Global CTO & CAIO John Roese sits down with AMD CTO Mark Papermaster to discuss why enterprises need to rethink their AI strategy beyond massive foundation models. 🔑Key insights: • Training vs. inference requires fundamentally different architectures • Finely-tuned models and SLMs are changing AI economics • Only 5% of enterprises report positive ROI on AI investments so far • Hybrid deployment across cloud, edge and PC is becoming the norm Watch the full conversation to learn what separates successful AI deployments from the rest: https://del.ly/60437pQlh

Had a great conversation with Mark Papermaster of AMD about where AI innovation is really happening right now—and it's not just at the model layer. We're seeing silicon and algorithms co-evolve in ways we haven't seen before. Lower precision math baked into hardware. Inference optimizations that make 70B parameter models run on laptops. The entire stack is moving faster than any technology cycle I've been a part of or seen. But here's what struck me most in our discussion: The enterprises getting this right aren't chasing the biggest foundation models. They're thinking full-stack and matching their architecture to their actual business problems. Only 5% of enterprises are seeing positive ROI on their AI investments. The gap between the leaders and everyone else isn't about having more GPUs or bigger models. It's about understanding where to deploy what—finely-tuned models for specific problems, hybrid architectures that put compute where it makes economic sense and software stacks that work consistently across cloud, edge and PC. Worth a watch if you're navigating these decisions: https://del.ly/60437pQlh

Anthropic partners with Google to access 1 million AI chips. Claude AI training scales up with TPUs and cloud support. https://lnkd.in/gpS8fXi2 #Anthropic #ClaudeAI #AIchips #TechNews #artificialintelligencetutorial

Are you struggling to deploy and scale AI models efficiently and cost-effectively? Managing AI infrastructure can be complex, time-consuming, and expensive, which often hampers innovation and rapid deployment. In today’s fast-paced AI landscape, organizations need a solution that simplifies development, accelerates scaling, and reduces cloud costs without sacrificing performance. Runpod is a cloud platform built specifically for AI, providing powerful, cost-effective GPU resources for every workload—from training to inference—so you can focus on your models, not infrastructure. ✔️ Spin up GPU pods in milliseconds—reducing cold-start times from minutes to milliseconds for faster development cycles ✔️ Seamlessly deploy any container with support for public and private image repositories, including popular frameworks like PyTorch and TensorFlow ✔️ Scale your AI inference and training with autoscaling, real-time analytics, and serverless GPU workers across 30+ regions Get Started with Runpod Today - https://lnkd.in/durC9S8r

🤖💻 Exciting news from Google Research! AI is revolutionizing cloud computing by optimizing virtual machine puzzles. Algorithms are becoming even smarter, significantly boosting efficiency. For businesses aiming to harness AI for automation or developers integrating AI into their solutions, this is a game-changer! Dive into the AI future and stay ahead in this tech-driven world. 🚀 #AI #CloudComputing #Innovation Read more: https://lnkd.in/eZdeDaJW Want to become an authority in your field? Overpass can help: https://lnkd.in/emfFt2_2

🤖💻 Exciting news from Google Research! AI is revolutionizing cloud computing by optimizing virtual machine puzzles. Algorithms are becoming even smarter, significantly boosting efficiency. For businesses aiming to harness AI for automation or developers integrating AI into their solutions, this is a game-changer! Dive into the AI future and stay ahead in this tech-driven world. 🚀 #AI #CloudComputing #Innovation Read more: https://lnkd.in/eBDSrUVu Want to become an authority in your field? Overpass can help: https://lnkd.in/edWYiA8a

As AI models grow more complex and real-time responsiveness becomes mission-critical, relying solely on the cloud just doesn't cut it anymore. Low latency, data sovereignty, and cost efficiency are driving the move to local AI processing, and that’s exactly where edge AI shines. Our ECT-DoT chip is designed for ultra-low latency and high efficiency, which empowers us to run AI workloads securely and at the speed they demand. Read the full article on AI Business: https://brnw.ch/21wWOei #EdgeAI #LowLatency #AIChips

🚀 Big news in AI infrastructure: CoreWeave just launched CoreWeave AI Object Storage, a purpose-built object storage solution specifically designed for high-performance AI workloads. Unlike traditional cloud storage, this platform delivers an impressive 7 GB/s per GPU using its local caching technology LOTA. That means hyper-parallelized data access for faster training, lower latency, and reduced operational overhead 👇 🔥 Key differentiators: - Local-disk speed, globally accessible - Up to 75% cost savings vs. traditional AI storage - Zero egress fees, multi-cloud support, S3 compatibility - Enterprise-grade security and observability This is a massive leap forward in removing storage bottlenecks that slow down AI innovation. Faster model development at lower infrastructure cost is not just a wish — it's becoming a standard. Let's talk 🧠 👉 How will this impact your organization’s ML pipeline? Join the conversation! #AI #CloudComputing #MachineLearning #ObjectStorage #InfrastructureInnovation #CoreWeave #GPU #DataOps #MLOps

𝗔𝗻𝘁𝗵𝗿𝗼𝗽𝗶𝗰 𝗵𝗮𝘀 𝘀𝗶𝗴𝗻𝗲𝗱 𝗮 𝗰𝗹𝗼𝘂𝗱 𝗱𝗲𝗮𝗹 𝘄𝗶𝘁𝗵 𝗚𝗼𝗼𝗴𝗹𝗲 𝘃𝗮𝗹𝘂𝗲𝗱 𝗶𝗻 𝘁𝗵𝗲 𝘁𝗲𝗻𝘀 𝗼𝗳 𝗯𝗶𝗹𝗹𝗶𝗼𝗻𝘀, 𝘀𝗲𝗰𝘂𝗿𝗶𝗻𝗴 𝗮𝗰𝗰𝗲𝘀𝘀 𝘁𝗼 𝗮𝗹𝗺𝗼𝘀𝘁 𝗼𝗻𝗲 𝗺𝗶𝗹𝗹𝗶𝗼𝗻 𝗧𝗣𝗨𝘀. This agreement shows how quickly the AI infrastructure layer is becoming the center of innovation. Enterprises that scale with AI face the same challenge: turning massive compute into consistent performance. Intelligence alone is not enough without efficiency and reliability. At NetAI, we work with systems that focus on agentic behavior, scalability, and context awareness. We believe the future of AI will be shaped by how well technology can serve people, not by how large it can grow. What do you think defines the next frontier of AI: Smarter models or smarter infrastructure?

!! Microsoft Azure just hit a groundbreaking milestone: 1.1 million tokens per second in AI inference performance! This achievement isn’t just a technical flex, it’s a signal of how fast the AI infrastructure race is accelerating. As demand for generative AI continues to surge, performance at scale is becoming the new benchmark for innovation. 🔹 Why it matters: Hitting 1.1M tokens/sec means faster, more efficient AI applicationsn… from real-time copilots to enterprise-scale deployments. It’s a leap forward in making AI more responsive, scalable, and accessible. 🔹 What it shows: Microsoft’s investment in AI infrastructure is paying off, and Azure continues to position itself as the leader in the high-performance AI cloud space. This kind of progress is what fuels the next wave of intelligent applications. The future is being built … one token at a time. #AI #MicrosoftAzure #CloudComputing #GenerativeAI