1290 posts · Page 93 of 108. ← Blog
Back the agent with Azure OpenAI's Responses API, and toggle whether conversation state lives on the server or locally.
Back an agent with Azure OpenAI Responses via NewResponsesAgent, and use DisableStoreOutput to keep chat history local instead of stored server-side.
Google's GKE AI infrastructure docs list ~40 integrations. Here's a field map of which ones actually matter when the workload is a HIPAA-aware multi-agent medical AI, and where the gaps sit.
Build a GDPR Article 22 compliant explanation endpoint in Go that turns audit logs and eval stores into regulator-friendly answers for AI decisions.
Request → N-eyes approve → window-of-time → automatic expiry, with every transition written to a hash-chained audit log. The package that closes Gap #1 from the PCSE map.
Before DNA was understood, a mathematician asked whether a machine could build a copy of itself — and answered it with a cellular automaton. Von Neumann's self-reproducing automaton proved that self-replication is possible in principle, and in doing so anticipated the logic of biological reproduction. This post is about the structures cellular automata can build, the deep question of self-reproduction, and what it taught us about life itself.
Von Neumann used a cellular automaton to prove a machine can build a copy of itself — via a universal constructor and a description that is both interpreted and copied, exactly how DNA works, worked out before DNA's role was understood. CA structures from gliders to self-replicating loops, and what they taught us about life.
A cache lives or dies by one number: its hit rate. Every cache access is a small bet — that the data will be there (a hit, served fast) rather than missing (a miss, served slow, plus the overhead of caching it). Whether caching helps at all comes down to how often that bet pays off, and understanding hits, misses, and hit rate — and what you should and shouldn't cache — is the foundation of using caches effectively. Get these fundamentals right, and the rest of caching makes sense.
A cache lives or dies by one number: its hit rate. Every cache access is a small bet — that the data will be there (a hit, served fast) rather than missing (a miss, served slow). Whether caching helps at all comes down to how often that bet pays off.
The same agent primitive, wired to Azure OpenAI's Chat Completions API where the model name is your deployment name.
Back an agent with Azure OpenAI Chat Completions via NewChatCompletionsAgent, where the Model field is your Azure deployment name, not a catalog model ID.
Why HL7 v2 — a 50-year-old pipe-delimited protocol — still drives most US hospital ADT integrations in 2026, and what a clean Go parser looks like in ~300 lines.
Studying for the IAPP AI Governance Professional credential? Here's an open-source Go codebase that demonstrates ~70% of the body of knowledge in working code.
Here is cellular automata's most mind-bending result: some of them are universal computers. The Game of Life and Rule 110 — systems of a few trivial rules — can compute anything any computer can compute. A grid of cells flipping on and off by a simple neighbor rule is, in principle, as powerful as any computer ever built. This post is about how simple cellular automata achieve universal computation, and why that is one of the most profound facts in computer science.
Some cellular automata are universal computers — the Game of Life and Rule 110 can compute anything computable, from a few trivial rules. How a CA computes using emergent structures as components (gliders as signals, collisions as logic gates, stable patterns as memory), and why universal computation needing so little is one of the field's deepest facts.
There's an old joke that there are only two hard things in computer science: cache invalidation and naming things. It's a joke because caching is everywhere and sounds simple — just keep a copy of stuff you'll need again — and it's true because getting caching right is genuinely, surprisingly hard. Caching is one of the most universal and powerful ideas in computing, appearing at every layer from CPU to CDN, and understanding why it exists and when it helps is foundational to building fast systems.
There's an old joke that there are only two hard things in computer science: cache invalidation and naming things. It's a joke because caching sounds simple, and true because getting it right is genuinely hard. Caching is one of the most universal ideas in computing, appearing at every layer from CPU to CDN.
Reach a Foundry-hosted model through the OpenAI-compatible Responses API by configuring a plain openai.Client with three request options.
Reach a Foundry model through the OpenAI-compatible API by configuring an openai.Client with base URL, an Azure token credential, and the ai.azure.com scope.