Hardware articles

12 articles about Hardware, newest first.

• Building Smarter: What Arduino Teaches Us About AI Resilience — Explore how Arduino's silent failures reveal lessons for AI systems and developers striving for robust, error-aware technology.
• Hugging Face Ships 207 WebGPU Kernels to Bring AI to the Browser — Hugging Face releases 207 open-source WebGPU kernels and a library that lets browsers run AI models instantly, with demos of attention and massive wave simulations.
• OpenAI's Jalapeno Chip Benchmark Rivals NVIDIA Blackwell: What It Means for AI Hardware — OpenAI's new Jalapeno chip benchmark shows inference speed that competes with NVIDIA Blackwell, featuring HBM4 and a 13‑month design cycle.
• Build a $5,000 AI Datacenter at Home: Full Guide — Learn how to assemble a $5k home AI datacenter with GPUs, cooling, networking, and cost breakdown.
• KV Cache-Aware Routing & Disaggregation: Supercharging LLM Inference on Kubernetes — Discover how KV‑cache routing and pod‑level disaggregation cut latency 10× and boost throughput on Kubernetes, enabling cheaper, faster LLM serving without extra GPUs.
• Double DGX Spark Setup: Doubling AI Compute Power Explained — Explore how a dual NVIDIA DGX Spark configuration boosts AI compute, cuts training time, and reshapes LLM development.
• Program Physical Robots with AI Prompts—No Code Required — You can now command real‑world robots using plain English prompts, thanks to AI tools that turn language into motion.
• Beyond the Screen: The Rise of Physical AI Devices — Explore how AI is moving from browser tabs into dedicated hardware like the MemoKet Gem to create a world of ambient intelligence.
• The AI Clock: Why Patience and Hardware Beat the Hype — Explore the tension between high-leverage AI bets and Apple's long-term hardware play, and why 'controlling the clock' is the secret to winning the AI race.
• The Desktop Frontier: Frontier LLMs Come to Your PC — Frontier LLMs are getting so efficient they can run locally on high‑end GPUs, shrinking the hardware gap and giving users control over their own AI.
• How Meituan’s LongCat 2.0 Trains a 1.6T MoE Model Without NVIDIA GPUs or TPUs — Meituan’s LongCat 2.0 shows a 1.6‑trillion‑parameter MoE model can be trained without NVIDIA GPUs or TPUs, using n‑grams, sparse attention and custom ASICs to cut cost and hardware reliance.
• OpenAI's GPT-5.6 Sol Hits 750 Tokens Per Second – Can It Stay Profitable? — OpenAI's GPT-5.6 Sol runs at 750 tokens per second on Cerebras hardware. Explore the speed, cost, and profit challenges behind the new AI milestone.