A new analysis on Towards AI examines why large language models retain user names for roughly fifty messages before losing context entirely, revealing fundamental limitations in current AI memory arch…
On August 15, Anthropic CEO Dario Amodei argued that AI companies will earn trust by curing diseases, and the past week showcased advances in AI-driven medicine, including Moderna and Merck's INTerpat…
Aiden AI has shipped context-window recovery infrastructure in its firmware across three merged pull requests (#497, #498, #530), implementing context compression, session switching, and saved-result-…
GGML, a small math library created by Georgi Gerganov, underpins llama.cpp and is designed for CPU inference on constrained hardware, using a computation-graph-first approach that pre-allocates memory…
UPS uses its AI-powered ORION (On-Road Integrated Optimization and Navigation) system to continuously analyze millions of delivery decisions influenced by traffic, weather, fuel prices, road condition…
Most people use AI daily without understanding how it works, but learning five key concepts—tokens, context windows, temperature, and hallucination—can demystify AI behavior and improve usage. Tokens …
Tensorlake's Cloud Volumes enable a reproducible five-agent pipeline by versioning the filesystem instead of teaching agents Git, allowing every run to be snapshotted, diffed, and restored on a fresh …
Voice AI systems are shifting from cascaded pipelines to native multimodal speech-to-speech models, but the older architecture remains widely used due to its flexibility, security, and cost advantages…
Bifrost, an AI infrastructure gateway, introduces dynamic model routing through Routing Rules that use the Common Expression Language (CEL) to evaluate runtime request context and override default pro…
A guide to spec-driven development with Claude Code, executed on a Flask + SQLite expense tracker called Spendly, demonstrates how to wire slash commands, subagents, skills, hooks, and a CLAUDE.md fil…
Towards AI published a guide explaining the AI technology stack, covering Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP), and Agentic A…
OpenAI's Codex platform offers three integration surfaces—codex exec, the Codex SDK, and Codex App Server—each suited to different automation needs, according to a practical guide for developers. The …
Anthropic's Python SDK v1.0 release introduces breaking changes that require production systems to migrate carefully, according to a guide for developers and AI engineers. The guide recommends wrappin…
MIT's NANDA initiative reviewed over 300 disclosed deployments and found 95 percent of enterprise generative AI pilots delivered zero measurable return, according to an analysis arguing that value is …
Google Cloud's Data Cloud team published the Open Knowledge Format (OKF) v0.1, a file-system-based standard for packaging organizational knowledge into portable, interlinked concept files, aiming to a…
Agentic Context Engineering (ACE) improves LLM systems by evolving their context instead of their weights, using three agents—Generator, Reflector, and Curator—to maintain a playbook through small, de…
On 28 July, MCP shipped its first deliberately breaking revision, version 2026-07-28, which removes the initialize handshake and Mcp-Session-Id, making the protocol stateless and enabling load-balance…
A feature store remains essential for production AI systems in 2026, according to an analysis of MLOps architectures, because it prevents training-serving skew and other failure modes that cause model…
A developer debugging a knowledge graph pipeline on an NVIDIA DGX Spark found that a 49-billion-parameter open-weight reasoning model was silently generating long internal monologues, causing apparent…
A developer built a production-grade machine learning system to predict 30-day hospital readmissions using the UCI Diabetes 130-US Hospitals dataset, which contains 101,766 patient encounters from 130…