You built a RAG pipeline. It retrieves 20 chunks, sends 20,000 tokens to the LLM, and 16 of those chunks are noise. Your RTX 6000 Ada has 48 GB of VRAM — and your KV cache just ate 40 of them. Memo...
Your chatbot forgets who it’s talking to after 15 messages. Your RAG pipeline hallucinates because the relevant answer is buried in token 47,000. You’re paying $3.20 per conversation because you se...
Your RTX 6000 Ada has 91 TFLOPS of FP32 compute. During inference, almost none of it matters. Training and inference stress completely different parts of the GPU. Understanding which bottleneck do...
In February 2026, Anthropic shipped a C compiler written almost entirely by Claude Code. 16 agents, working in parallel across ~2,000 sessions, produced over 100,000 lines of Rust that compiles the...
Goldman Sachs deployed Claude-powered AI agents to 12,000+ developers and back-office staff, achieving 30% reduction in client onboarding times and saving thousands of manual labor hours weekly. Th...
Bank of America’s AI assistant Erica handles over 3 billion customer interactions annually using the ReAct pattern. When a customer reports suspicious charges, Erica doesn’t just hallucinate an ans...
A financial services company deployed an AI agent to process customer support tickets. Within 48 hours, a crafted prompt injection allowed an attacker to extract API keys from the agent’s memory,...
OOM debugging is a waste of time. If a model is on the Hugging Face Hub in Safetensors, you can estimate most of the VRAM it will need before downloading weights — by reading only the metadata hea...
Everyone wants to throw Transformers at every computer vision problem. The research papers show impressive gains. The hype is real. But I wanted to know: What happens when you actually run the sam...
The cloud isn’t always the answer. Sometimes the best deployment strategy is no deployment at all—let the user’s hardware do the work. Train in PyTorch, export to ONNX, run anywhere: browser, deskt...