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Run Asterbot - an AI agent where each capability (search, memory, LLM) is a sandboxed, swappable WASM component via WASI. Learn how components are authorized and discovered.
Practical playbook to run a scoped, auditable automation pilot—linking sensors, digital twins, ML decisions and ERP—based on Roland Busch’s Siemens strategy.
Reproducible tutorial to build an APEX-Agents-style test harness measuring AI agents' ability to stitch context across Slack and Google Drive. Includes configs, logs and rollout gates.
Screenshots of a deleted Reddit thread claiming OpenAI leaked a Super Bowl spot—Alexander Skarsgard with a shiny orb and wraparound earbuds—were fabricated. Read how the hoax spread.
Guide to Sediment — a Rust single-binary, local-first semantic memory for LLM agents. Use four tools (store, recall, list, forget) to add private, persistent context.
On 27 Jan 2026 the Bulletin set the Doomsday Clock to 85 seconds before midnight. Read a concise guide for builders and founders on governance, resilience, and risk artifacts to prepare.
Describes PCE (Planner-Composer-Evaluator) that turns LLM reasoning assumptions into decision trees, then scores paths by likelihood, goal gain and execution cost to reduce communication.
Use the OpenClaw CLI onboarding to set up a local Gateway (port 18789) with token auth, seed ~/.openclaw/workspace, install a user daemon, and connect a messaging channel.
Summarizes AEC: split grounded facts for commitments from a belief store for pruning, query vs simulate by uncertainty, and gate commitments with SQ-BCP—reduces replanning.
Describes 'adversarial explanation attacks'—how LLM explanation framing keeps users trusting incorrect outputs. Reports a 205‑participant study and gives pragmatic builder controls.
Agent-Omit trains LLM agents to omit redundant internal thoughts and observations using cold-start omission data plus omit-aware RL; includes a KL-divergence bound and Agent-Omit-8B results.
AgentArk distills multi-agent debate into a single LLM via three hierarchical distillation strategies, shifting computation to training to cut inference cost while preserving reasoning.