Nvidia
Infrastructure & Cloud
The $450B Treadmill: How GPU Obsolescence Is Rewriting Hyperscaler Economics
Hyperscalers will spend $450B on AI infrastructure in 2026 while depreciating GPUs over 5–6 years. A 2–3 year refresh cycle is breaking the math.
AI & Automation
NVIDIA’s Agent Toolkit: What Algerian Developers Need to Know
⚡ Key Takeaways NVIDIA's Agent Toolkit — open-sourced at GTC 2026 on March 16 and already backed by 17 enterprise...
Startups
Frore Systems: From Qualcomm Spinoff to $1.64B Unicorn on AI Cooling
⚡ Key Takeaways Frore Systems closed a $143 million Series D round in March 2026, bringing total capital raised to...
AI & Automation
Eli Lilly’s LillyPod: 1,016 GPUs and Pharma’s AI Supercomputer Gamble
⚡ Key Takeaways LillyPod’s 1,016 NVIDIA Blackwell Ultra GPUs deliver over 9,000 petaflops of AI performance — each single GPU...
Startups
Cerebras IPO: The Wafer-Scale Chip Challenging Nvidia’s AI Reign
Cerebras raised $1B at a $23B valuation and targets a Q2 2026 IPO. Its WSE-3 chip claims 21x faster inference than Nvidia.
Infrastructure & Cloud
NVIDIA’s Groq Deal: How the Vera Rubin Platform Reshapes AI Inference
NVIDIA's $20B Groq deal yields the LP30 LPU with 35x inference efficiency per watt. The Vera Rubin platform unifies GPUs and LPUs for trillion-parameter AI.
Infrastructure & Cloud
Adani’s $100 Billion Bet: India’s Play for AI Data Center Supremacy
⚡ Key Takeaways Bottom Line: India’s $240 billion AI infrastructure pledge — led by Adani’s $100B and Reliance’s $110B —...
AI & Automation
NVIDIA and the GPU Economy: How One Company Controls the AI Hardware Pipeline
NVIDIA dominates the AI chip market with its CUDA moat and GPU platform strategy. Here’s how the GPU economy works and what threatens it.
AI & Automation
AI Infrastructure: The Physical Foundation of Artificial Intelligence
Explore the physical foundation of AI: chips, GPUs, data centers, cloud platforms, and the geopolitics of computing power.
AI & Automation
The AI Infrastructure War: GPUs, Data Centers, and the Compute Race
The global AI infrastructure race: GPU economics, data center buildout, compute scaling laws, energy challenges, and what it all means for the future of AI.
AI & Automation
AI Compute Scaling: Why the Shift from Training to Inference Changes Everything
Inference now consumes two-thirds of all AI compute, reshaping hardware, economics, and business models. The cost per token is dropping 10x yearly.
