Cristian Córdova 🐧

🔥 ¿Cuánto cuesta un rack de IA Vera Rubin NVL72 que acaba de presentar $DELL 🔥 Precio real estimado (2026): Entre 1-2,5 Mn$ por rack ya integrado, probado en fábrica y listo para enchufar (incluye servicios de despliegue de Dell). • Rack básico compute: ~400-800k • Rack AI Networking como he puesto en la foto: $1M–$2.5M • Rack full GPU liquid-cooled (con Blackwell/Rubin): puede superar los 4-9 Mn$ !!! Hay que tener en cuenta que los precios siempre son personalizados y no únicos, dependiendo de los requerimientos del cliente.

I've got an agent in a loop optimizing a renderer with the goal to minimize frame times (and tests to measure). It got times down from 88ms to 2ms and allocations down from ~150K to 500. Sounds good, right? Wrong. This is exactly why agent psychosis is a big fucking problem. As an experiment, I rewrote the Ghostty core render state in Go, with access to identically laid out data structures as Ghostty and the exact same validation tests. I made a purposely naive renderer (simple, correct, but slow). 88ms per frame with 150,000 allocations (horrendous, lol)! I then kickstarted a Ralph loop to bring the frame times down. I told it it can't modify input data structures or the public API or tests (they're correct), but it can do anything else it wants. It got to work. It has worked for about 4 hours. I've spent around $350 on this experiment so far. The results? 88ms => 1.5ms 150K allocs => ~500 allocs Incredible right? Nope. My hand-written renderer I ported has frame times (same benchmark) of ~20us (0.020ms) and 0 allocations in the update path. This is the problem with psychosis and lacking systems understanding. If you don't understand the system, you're going to accept that this is an incredible result. If you understand the system, you'll see better solutions immediately and can do roughly 75x better on throughput. The people who blindly trust agent output are in the former camp. They're sheeple, overdrinking from a fountain of mediocrity. Standard disclaimer: I use AI all the time. I like AI. The point I'm making is to not blindly accept results. Think. Analyze. Learn.

NEW: AI consultant reveals a client accidentally spent $500,000,000.00 in a single month after failing to set employee limits on Claude usage.

vLLM v0.22.0 is out! 459 commits from 230 contributors (63 new). 🎉 Highlights: DeepSeek V4 hardening (NVFP4 fused MoE, full+piecewise CUDA graph, ROCm support), experimental Rust frontend in-Tree, batch-invariant Cutlass FP8 (28.9% lower e2e latency), Model Runner V2 advances, multi-tier KV cache offloading. Thread 👇

Vamos a contratar a 2 o 3 personas a través de la UMA para experimentar sin miedo en ciberseguridad e IA te vienes al sótano de Google Málaga, tienes acceso a Gemini y la factura de tokens deja de ser tu problema la pregunta es "sencilla": ¿qué construirías? (sí, es en serio)

Nvidia’s new ARM-based SOC is rumoured to feature: - Up to 20 CPU cores - Up to 6144 Blackwell CUDA cores - Use a TSMC 3nm process - Up to 128GB unified memory This has the potential to be an M5 Max competitor for AI-developers.

breakTheViciousCircle