Research library
Technical guides
Detailed explanations of AI systems and software engineering, with equations, implementation context, and sources.
16 articles · Page 1 of 2
How AI Watermarking Works: Text, Images, Audio, and What the Mark Actually Proves
How AI watermarks work in text, images, audio and video, what C2PA adds, what Article 50 and California's SB 942 require, and what a detected mark proves.
One Shared Key Let Anyone Decode What Claude, GPT and Gemini Were Hiding in Their Reasoning
One shared key sealed the reasoning blocks Anthropic, OpenAI and Google return to clients, letting a weaker model decode a stronger sibling's thoughts.
How AI Finds Vulnerabilities: Fuzzing, Reasoning, and Validation
How AI agents find software vulnerabilities: hybrid fuzzing, static analysis, LLM reasoning, validation, benchmarks, and patch workflows.
TPU v8 vs Blackwell: How AI Silicon Is Splitting Into Training and Inference Chips
Training and inference need different silicon. TPU v8t/v8i architecture, comparison to Blackwell's unified design, and per-token cost implications.
Compressed Sparse Attention: How DeepSeek V4 Reached 1M Context at 27% of the FLOPs
DeepSeek V4 hits 1M context at 27% of V3.2's per-token compute. How Compressed Sparse Attention and Heavily Compressed Attention combine to do it.
KV Cache: The Hidden Memory Wall in LLM Inference
The KV cache memory wall in LLM inference: the math behind long context costs and architectural solutions (GQA, MQA, MLA, paged attention).
Small MoE Models: How Sparse Routing Makes Efficient AI Possible
Small-scale Mixture of Experts: sparse routing lets 47B models match 70B dense equivalents. Mixtral, DeepSeek-MoE, Phi-MoE, efficiency math.
AI Video: From Diffusion to Directors
How AI video generation works: diffusion foundations, temporal modeling, audio sync, and the multimodal architectures behind Seedance 2.0.
How AI Benchmarks Actually Work
The benchmarks behind AI model claims: SWE-bench, ARC-AGI-2, GPQA Diamond, and more. What they measure, how they work, and what they miss.
Agentic AI Architecture Patterns
A guide to agentic AI patterns: ReAct loops, tool-use protocols, multi-step planning, memory, and multi-agent coordination in production.
Mixture of Experts: Sparse AI Architectures
MoE architectures explained: gating mechanisms, expert routing, load balancing, and why sparse models deliver frontier AI at fraction cost.
Foundations of Transformer Reasoning
A technical deep-dive into transformer architectures, attention mechanisms, scaling laws, and emerging techniques for reliable AI reasoning.