DevOps.com’s Post

The AI infrastructure race is heating up—and it’s not subtle. Billions are pouring into compute, chips, and cloud infrastructure. Why? To dominate future markets, own the AI stack, and scale faster than competitors. 📊 Spend analysis 🧠 Strategy insights ⚠️ Risks to watch Whether you lead IT, invest in tech, or build future-focused products—this is the AI shift you need to understand. 👉 https://ow.ly/EJQk50Xl2tp #AI #DigitalStrategy #Innovation #TechLeadership #CloudInfrastructure #BigTech #FutureOfWork

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?

As 2025 ends and 2026 approaches, the high failure rate of AI projects, particularly those on cloud platforms, is becoming alarming. Reports, like the MIT study, highlight dismal ROI, while firsthand audits reveal recurring issues. The good news? It's fixable. The bad news? Acknowledging the problem is the first step toward effective solutions. Are companies willing to face the reality of their AI investments? #AIProjects #CloudPlatforms #ROI #Technology #Innovation #Auditing

Anthropic's Google Cloud deal signals hyperscalers winning in the AI infrastructure gold rush. Custom silicon is now a key differentiator. https://lnkd.in/eJN8MADp #ai #artificialintelligence #intelligence #anthropic #google #cloudcomputing #machinelearning #aigenerated

Is your cloud infrastructure ready for the next wave of AI? 🚀 A leading AI company is making a massive investment in specialized AI hardware, signaling a major shift in how enterprises are approaching AI infrastructure. This expansion involves a significant deployment of specialized processing units. The investment is valued in the tens of billions of dollars. The new infrastructure is expected to come online within the next few years. This move highlights the growing importance of specialized hardware for AI workloads. It suggests a future where companies prioritize tailored infrastructure for optimal AI performance and efficiency. Are general-purpose cloud solutions enough, or will specialized hardware become the new norm? What do you think this investment means for the future of AI infrastructure? Share your thoughts in the comments! 👇 #AI #CloudComputing #ArtificialIntelligence #Infrastructure #MachineLearning

𝗜𝘀 𝘆𝗼𝘂𝗿 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗔𝗜 𝗺𝗼𝗱𝗲𝗹 𝗰𝗼𝘀𝘁𝗶𝗻𝗴 𝘆𝗼𝘂 $𝟭𝟬,𝟬𝟬𝟬 𝗮 𝗺𝗼𝗻𝘁𝗵 𝘁𝗼 𝗿𝘂𝗻? 𝗜𝘁 𝘀𝗵𝗼𝘂𝗹𝗱𝗻'𝘁 𝗯𝗲. The biggest shift in cloud strategy isn't about storage anymore, it's about the exponential cost of LLM inference. An unoptimized model can hemorrhage budget, especially when deploying at scale or moving to the Edge. At Amlgo Labs, we believe efficient AI is achievable AI. The answer lies in Model Compression. We break down the two essential techniques - Quantization and Pruning. This can dramatically reduce your model size, cut latency, and deliver up to 80% cost savings without sacrificing critical accuracy. Swipe through to understand the technical blueprint for the future of AI FinOps. 👇 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝗳𝗼𝗿 𝘁𝗵𝗲 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆: What percentage of your total cloud bill is currently tied up in AI inference? Share your number and biggest headache with us and let us provide you our solution! #AmlgoLabs #ModelCompression #AIEfficiency #FinOps #Quantization #EdgeAI #GenerativeAI

Ever wonder why Big Tech is pouring billions into AI? 🤯 It's not just about innovation; a massive wave of capital expenditures is shaping the future of enterprise solutions and cloud services. Discover the forces driving these immense tech investment trends! 🚀 Read the full article: https://lnkd.in/dXzkWQVy #BusinessStrategy #EnterpriseSolutions #CloudServices #DigitalInnovation

Is AI the future or the present? AI is transforming from a trial to a triumph for businesses. Research shows 25% of companies already enjoy steady returns from AI, with 35% anticipating similar success soon. Initial benefits involve automation, quicker replies, and enhanced customer support, while greater transformation potential awaits. The shift is influencing infrastructure plans: • While 64% of AI tasks are in the cloud, over half of businesses aim to expand on-premises and colocation for improved security, latency, and compliance. • The main hurdles now are integration, scaling, and talent rather than data. • AI is evolving from generic models to custom-built LLMs and exclusive solutions. • Centralized training will persist for 73%, but inference will shift closer to users and data. The indication is unmistakable. The AI era isn't approaching—it's already happening. Infrastructure must evolve rapidly to match. 👉 Explore the complete report here for detailed insights: https://lnkd.in/eVjBW92c  DataBank  #ai #digitalinfrastructure #cloud #colocation #futureoftech #datacenters #businessgrowth #databank

The enterprise AI revolution is here, and the focus is moving from web apps to intelligent agents that reason and interact with your core business context. Our very own Rohan Grover, Sr Director of Product for Google Distributed Cloud, sat down with Justin Boitano, VP of Enterprise AI Products at NVIDIA, and analyst Elias Khnaser to discuss how our deep technical partnership is making AI anywhere a reality. This conversation is packed with insights on: ✅ Enabling compliance without compromise ✅ Igniting your "dark data" ✅ Simplifying the adoption and management of AI capabilities This is a must-listen for any enterprise leader grappling with how to use AI to unlock AI on-premises without compromising security or performance. Listen now: https://lnkd.in/gfK7-__g #GoogleCloud #NVIDIA #AI #GenAI #EnterpriseAI #Gemini #ITLeaders #CXO #GDC #DistributedCloud https://google.smh.re/5EAz

Tigris Data Secures $25 Million in Series A Funding to Revolutionize AI-Optimized Cloud Storage “In the age of AI, lock-in isn’t just costly; it slows you down. Innovation today is about performance, speed of iteration, and shipping faster than ever. If your data is trapped, your ability to innovate is trapped with it,” said Ovais Tariq, Co-Founder and CEO of Tigris Data. “With Tigris, AI teams get storage built for their workflows, including limitless training, borderless inference, collaborative agents, compute freedom, and faster iteration.” Read More: https://lnkd.in/dwgBupv7 #AI #AIoptimizedcloudstorage #AITech365 #DataManagement #news #objectstorage #TigrisData