Llama 4 Explained: Scout, Maverick, and Behemoth (MoE)
Llama 4 explained: Meta's Scout, Maverick, and Behemoth mixture-of-experts models - architecture, context window, benchmarks, license, and how to deploy them.
Vector Database Benchmarks 2026: Pinecone, Weaviate, Qdrant
A 2026 vector database benchmark: Pinecone, Weaviate, Qdrant, and Milvus on recall, latency, throughput, and cost - with what changed in the second half of 2026.
AI Model Supply Chain Security: SBOM, Signing, Provenance
AI model supply chain security in 2026: model SBOMs, signing and attestation, poisoned weights, registry trust, and provenance for the ML pipeline.
LLM Observability and LLMOps: Tracing, Evals, Drift
An LLM observability and LLMOps architecture: OpenTelemetry GenAI traces, spans, online evals, and drift detection for production LLM and agent systems.
GPT-5.6 Explained: OpenAI’s Sol, Terra, and Luna
GPT-5.6 explained: OpenAI's Sol, Terra, and Luna tiered family - architecture signals, reasoning modes, benchmarks, pricing, access, and how it compares in 2026.
NVIDIA GB300 NVL72: Blackwell Ultra Architecture (2026)
NVIDIA GB300 NVL72 explained: Blackwell Ultra GPUs, the 72-GPU NVLink rack, memory and power, and how it scales AI training and inference at rack level in 2026.
Embedding Models Benchmark: OpenAI, Cohere, Voyage, BGE
A 2026 embedding models benchmark: OpenAI, Cohere, Voyage, and BGE on retrieval quality, dimensions, cost, and MTEB - with what changed for 2026.
AI Inference Cost Optimization: GPU FinOps in 2026
An AI inference cost optimization decision record: continuous batching, KV-cache, quantization, speculative decoding, spot GPUs, and autoscaling the inference path.
LLM Gateway Architecture: The Control Plane for AI Apps
An LLM gateway architecture for production AI: routing, semantic caching, rate limits, budgets, fallbacks, and observability across multiple model providers.
Fine-Tuning vs RAG vs Long-Context: A 2026 Cost/Quality Decision
A 2026 cost and quality decision record for fine-tuning vs RAG vs long-context LLMs: token economics, latency, accuracy trade-offs, and a decision matrix.