
The Efficient Inference Stack: AI and Energy-Aware Computing
Energy-aware AI design reduces waste by optimizing model size, hardware, batching, caching, routing, and where inference runs.
Insights, tutorials, and updates from the ZharfAI team

Energy-aware AI design reduces waste by optimizing model size, hardware, batching, caching, routing, and where inference runs.

Anthropic's June 30 model lifts coding, terminal, search, computer use, and knowledge work while exposing effort as a cost-performance control.

Knowledge graphs give AI systems structured context about people, assets, policies, products, and relationships that plain retrieval often misses.

Open-source models give teams control, but production value depends on evaluation, serving, fine-tuning discipline, security, and upgrade strategy.

A practical guide to digital identity wallets, verifiable credentials, selective disclosure, AI-assisted fraud controls, privacy, and 2026 implementation standards.

AI is pushing robotic process automation from brittle scripts toward adaptive orchestration across people, APIs, documents, and user interfaces.

AI is helping scientists interpret solar imagery, magnetosphere signals, and satellite telemetry to forecast disruptions before they reach Earth systems.

A practical 2026 guide to cryptographic inventory, NIST post-quantum standards, AI-assisted discovery, crypto agility, migration priorities, and release evidence.

Privacy-enhancing technologies help teams use AI on sensitive data through minimization, isolation, encryption, and carefully governed computation.

Mistral's June 23 model adds boxes, block types, confidence, 170 languages, self-hosting, and leading OCR scores—with unusually clear benchmark caveats.

Web-browsing agents can research, compare, click, fill forms, and verify pages, but reliability depends on state awareness and constrained actions.

Learn OpenAI Codex end to end: install Codex CLI, use the app, IDE and cloud, configure MCP, AGENTS.md, sandboxing, reviews, CI and SDK workflows.