September 15th, 2026: Model codes, advisor agents, and deepfake enforcement
AI controls moved into model rules, regulated workflows, and domain seizures, while access and oversight became practical design questions.
A publication for curious technical minds
Know what changed.
Understand why it works.
A daily, sourced guide to artificial intelligence, paired with the mathematics that turns headlines into understanding.
Today's signal
The Daily Digest
A short, sourced guide to the AI developments worth opening today.
Browse all Daily DigestsEarlier editions
More Daily Digests
September 14th, 2026: SSD inference, policy resistance, and paired coding agents
Colibri streams DeepSeek V4.1 Flash from SSDs, US leaders resist an AI slowdown, and Cognition pairs frontier and cheaper coding models.
September 13th, 2026: Evaluators, private benchmarks, and managed agents
Anthropic opens its lab to embedded evaluators, Real-SWE tests agents on private code, and OpenAI turns its Codex harness into an API.
September 12th, 2026: Mathematicians challenge AI as agent costs meet benchmarks
Mathematicians contest proof races, UK statistics trace an AI-linked GDP contribution, and paired tests challenge agent token savings.
Build the foundation
Math for AI
Inner Products Measure Alignment in Attention
Compute a dot product, read its sign and magnitude geometrically, and see how query-key scores become attention weights.
L1, L2, and L-infinity See Size Differently
Compare L1, L2, and L-infinity vector size, see their unit balls change, and distinguish parameter penalties from input-robustness budgets.
Vector Norms Measure Size, Not Meaning
Calculate L1, L2, and L-infinity vector norms, verify their defining rules, and see what an embedding magnitude can—and cannot—tell you.