AI Hardware and Infrastructure
AI chip development, cloud infrastructure, compute optimization, hardware trends
Infrastructure engineers, hardware founders, cloud architects, investors
GPU scarcity, compute costs, power consumption, supply chain complexity
From TPU to Your Own Custom Silicon: A Founder's Journey
How AI hardware choices make or break a startup: GPU shortages, cloud versus owned clusters, custom chips, and what each option really costs founders.
Surviving the GPU Apocalypse: A Founder's Guide to the Shortage
How AI hardware choices make or break a startup: GPU shortages, cloud versus owned clusters, custom chips, and what each option really costs founders.
The 6 AI Infrastructure Mistakes That Are Secretly Killing Your Startup
Six costly AI infrastructure errors: betting only on NVIDIA, dismissing custom silicon, one data center, the wrong cloud, no GPU plan, ignoring inference.
15 Lessons on Building a Custom AI Chip
How AI hardware choices make or break a startup: GPU shortages, cloud versus owned clusters, custom chips, and what each option really costs founders.
Why the Future of AI Is Not in the Cloud 338
How AI hardware choices make or break a startup: GPU shortages, cloud versus owned clusters, custom chips, and what each option really costs founders.
The Counterintuitive Truth About AI Chip Design 869
The best chip fits the workload; it is not the fastest. Custom silicon like TPUs, Trainium and Dojo, edge chips, data center co-design and the talent gap.
Edge AI vs. Cloud AI: The Ultimate Showdown for Developers
Cloud GPUs bring cost and latency real-time AI can't afford; edge AI cuts both. Where TPUs, custom silicon and quantum computing fit in a hardware plan.
The Top 7 AI Hardware Trends to Watch in 2027
How AI hardware choices make or break a startup: GPU shortages, cloud versus owned clusters, custom chips, and what each option really costs founders.
Why the Future of AI Is Not in the Cloud 232
Cloud AI is a good start and a costly finish: GPU bottlenecks, data gravity pulling compute to the edge, and why custom silicon like TPUs points the way.
I Ditched the Cloud for Bare Metal and My Bill Dropped 62%
Cloud AI pays a hypervisor tax; bare metal gives direct hardware access and more performance. When to switch, and why custom silicon comes next.
The Counterintuitive Truth About AI Chip Design
The GPU shortage forced leaner AI, custom silicon is costly and slow, and edge chips are rising. The right hardware for the problem beats the fastest chip.
The Counterintuitive Truth About AI Chip Design 340
More GPUs rarely fix the problem: fit hardware to the job, weigh custom ASICs when stock chips fall short, watch edge AI, skip the TPU and quantum hype.
11 Lessons on Building a Custom AI Chip
How AI hardware choices make or break a startup: GPU shortages, cloud versus owned clusters, custom chips, and what each option really costs founders.
Behind the Scenes of a Hyperscale AI Data Center 524
GPU waitlists, cloud bills that eat a seed round, power, cooling and supply chains: what AI data centers take, and why custom silicon is the long game.
Why Most Founders Get AI Infrastructure Completely Wrong
AI startups stumble on hardware, not models: GPU shortages, cloud lock-in, ignored edge AI. The case for owned hardware and custom silicon; skip quantum.
What AI Hardware Teaches Founders
How AI hardware choices make or break a startup: GPU shortages, cloud versus owned clusters, custom chips, and what each option really costs founders.
The 5 AI Infrastructure Mistakes That Are Secretly Killing Your Startup
Five AI infrastructure mistakes: NVIDIA-only hardware, ignoring TPUs and custom silicon, skipping the cloud, chasing quantum, building only for today.
What AI Hardware Teaches Founders
How AI hardware choices make or break a startup: GPU shortages, cloud versus owned clusters, custom chips, and what each option really costs founders.
Custom AI Chips: Tech and Tough Choices
How AI hardware choices make or break a startup: GPU shortages, cloud versus owned clusters, custom chips, and what each option really costs founders.
What It Really Takes to Build a Hyperscale AI Data Center
GPU lead times, networking, power and cooling, custom chips, scarce talent, software and water use: the physical limits behind AI data centers.
- What I’ve Learned About AI Hardware Trends for 2027
- Building AI Data Centers: What It Really Takes
- My Take: Behind the Scenes of a Hyperscale AI Data Center 894
- My Take: Why the Future of AI Is Not in the Cloud 206
- What AI Hardware Teaches Founders
- My Take: The Economics of AI: Why Your GPU Isn't the Real Cost
- My Unfiltered Truth About AI Chip Design
- The Truth About the GPU Shortage Nobody Is Talking About
- NVIDIA's Next Move: What to Expect After the H100 Dominance
- Quantum Computing: Is It the End of GPUs as We Know It?
- The 7 AI Infrastructure Mistakes That Are Secretly Killing Your Startup
- How to Build a Petascale AI Cluster (The Counterintuitive Guide)
- I Simulated a Quantum Computer on a GPU and Here's What Happened
- The Real Reason Your AI Models Are So Slow (It's Not Your Code)
- The Top 10 AI Hardware Trends to Watch in 2027
- Behind the Scenes of a Hyperscale AI Data Center 321
- Behind the Scenes of a Hyperscale AI Data Center 776
- The Counterintuitive Truth About AI Chip Design 5
- How to Build a Greener AI Data Center
- The 4 AI Infrastructure Mistakes That Are Secretly Killing Your Startup
- What Building a Custom AI Chip Involves
- The 8 Infrastructure Mistakes That Almost Sank My Startup
- 10 AI Infrastructure Mistakes That Are Secretly Killing Your Startup
- The Counterintuitive Truth About AI Chip Design 36
- The Counterintuitive Truth About AI Chip Design 498
- Why the Future of AI Is Not in the Cloud
- 12 AI Infrastructure Mistakes That Kill Startups
- 13 AI Infrastructure Mistakes Killing Your Startup
- The Truth About AI Chip Design