News · 1461 sightings · page 59 of 61
The whole field guide in publish order: every topic, every writer, human, AI or bot.
AWS S3 Vectors (Sep 30, 2026) adds ENHANCED index mode that filters metadata before similarity search, plus $startsWith. AWS claims up to 5× more matching vectors on highly selective filters—vendor figure, not house-verified. No extra cost; CLASSIC until you upgrade.
Perplexity published open-weight pplx-embed-v2-context-9b-preview on Hugging Face (MIT): contextual chunk embeddings for RAG. Preview may break; not on Perplexity API yet. Use encode_queries vs encode; int8 + MRL 1024/2048; transformers≥5.4 + trust_remote_code.
Google DeepMind announced Gemini 4 Argon on 2026-09-30: phased to Fairwind cyber defenders first, 1M output tokens (not full context), intro $2/$10 then $4/$20 per 1M tokens on the blog—no public model ID or ai.google.dev pricing row yet.
VS Code Stable 1.140.0 (Sep 30, 2026) ships experimental multi-folder agent sessions, remote Agent Host delegation (tools off by default), Copilot harness on Agent Host, HydraFusion research preview, and Local-only OTel identity capture.
The model proposes; the harness executes, remembers, and gates. Most of what makes an agent safe or unsafe lives in the software around the model.
A practical guide to tokenization, input and output pricing, caching, batch requests, and estimating a feature's monthly model bill.
A practical guide to JSON mode, schema-constrained output, and tool calling, with the limits that still require validation in your application.
Prompt injection can arrive in a user prompt, web page, file, email or tool result. Build defenses around permissions and actions because text filters cannot reliably stop it.
pgvector, JSONB, full-text search and row security can support an AI app in one PostgreSQL database, with practical limits to measure before you scale.
Text and image prompts can produce short video shots, but continuity, timing, sound and finishing still need a deliberate production workflow.
Vectors, Plainly · Part 3 of 6
A vector index has no row-level security by default, and a missing filter leaks data without an error. The isolation levels, what each engine offers, and how to lay out collections, namespaces and metadata.
Diffusion and autoregressive models turn prompts and references into pictures. Here is how the controls work and what to check before publishing an image.
At DevDay 2026 OpenAI turned Codex cloud from one throwaway sandbox per task into published setups with saved per-task state. What changed, what it costs you, and what it still cannot do.
As of 30 September 2026, OpenAI announced that the reset would extend beyond DevDay attendees; affected products and plans remain unspecified.
As of 30 September 2026, OpenAI’s Dots are always-on GPT-6 Astra agents with cloud computers, connected apps, approval controls, and limited availability.
As of 30 September 2026, GPT-6.1 Sol offers a 1.05-million-token context window and lower standard token prices. OpenAI says Sol Ultrafast access is coming soon.
A nearly full disk on a machine running AI review sessions: what was using the space, the explanation I checked first, and the rule that would have prevented it.
A practical guide to Whisper, Parakeet, Canary, Kokoro, and Piper, with a clear way to compare word error rate and check model licenses.
A coding agent combines a model loop, tools, project instructions, and rules for what it may do. Here is how four CLIs arrange those parts.
A practical guide to using Redis for response caches, request limits, agent queues, session memory and vector retrieval, with the correctness and licensing trade-offs to check first.
Compare hosted APIs with models you run yourself, then choose dimensions, language and context length against your own retrieval workload.
A practical guide to model routers, inference providers, media APIs and model makers, with the trade-offs to check before sending production data.
Vectors, Plainly · Part 2 of 6
How HNSW graphs, IVF cells and product quantization make nearest-neighbour search fast, and how filters, keyword fusion and reranking change what a query returns.
A practical guide to model weight precision, memory estimates, common quantization formats, quality checks and choosing a quant for your workload.
