Results for “rto”

Industrial communication protocols for Zephyr RTOS. Covers Modbus RTU (serial), Modbus TCP (Ethernet/Wi-Fi), and CANopen basics. Trigger when building factory automation controllers, industrial sensors, or medical equipment interfaces.

Guides backup, restore, snapshot, PITR, retention, and disaster recovery planning for PostgreSQL and AWS, emphasizing tested restores and RTO/RPO alignment.

Build system management for Zephyr RTOS. Covers West workspace initialization, manifest management, Sysbuild multi-image builds, Kconfig symbols, and CMake integration. Trigger when setting up workspaces, configuring builds, or troubleshooting build-time errors.

Specialized hardware interfaces and system reliability for Zephyr RTOS. Covers LVGL GUI development, Audio I2S/Codecs, Watchdog timers, and Fault Injection. Trigger when building human-machine interfaces (HMI), audio devices, or high-reliability mission-critical systems.

Storage management for Zephyr RTOS. Covers Non-Volatile Storage (NVS) for persistent settings, flash partition management in Devicetree, and runtime flash layout access. Trigger when implementing persistent data storage, managing flash wear leveling, or configuring device partitions.

Developing for multicore systems in Zephyr RTOS. Covers Symmetric Multiprocessing (SMP), Asymmetric Multiprocessing (AMP) with OpenAMP/RPMsg, inter-processor communication (IPC) patterns, and Linkable Extensions (LLEXT). Trigger when designing for SoCs with multiple homogeneous or heterogeneous cores.

Static human-browsable catalog of the Zephyr RTOS skill set. Skill selection is handled by the zephyr-agent-skills entry point and by zephyr-cli skills suggest; this index is a reference listing only, not a task skill.

Custom board bringup for Zephyr RTOS using Hardware Model v2 (HWMv2). Covers directory structure, board.yml metadata, core configuration files (Kconfig, defconfig, CMake), and revision management. Trigger when creating new board definitions or porting Zephyr to custom hardware.

Integration of advanced IoT protocols for Zephyr RTOS. Covers OpenThread mesh networking, Matter-over-Thread device development, Golioth Cloud SDK patterns, and LoRaWAN basics. Trigger when building smart home devices, wide-area sensor networks, or cloud-integrated hardware fleets.

Power management and performance optimization for Zephyr RTOS. Covers system power states (Idle, Suspend, Off), device-level power management, residency hooks, and code/data relocation for speed efficiency. Trigger when optimizing battery life, reducing latency, or managing memory constraints.

Disaster recovery has exactly two quantitative inputs, and every architectural

Train and fine-tune transformer language models using TRL (Transformers Reinforcement Learning) with support for SFT, DPO, GRPO, KTO, RLOO, and reward model training via CLI commands.

Train, evaluate, distill, quantize, export, and run inference for RT-DETR object detection models using NVIDIA TAO.

Train, evaluate, export, and run inference on TAO action-recognition models for classifying temporal actions in video clips using RGB, optical flow, or joint input.

Essential Zephyr RTOS kernel services. Covers thread lifecycle and priority, the logging subsystem for diagnostics, and the interactive shell for real-time hardware inspection and debugging. Trigger when writing application flows, adding logging to modules, or creating interactive CLI commands.

Fine-tune and align language models using reinforcement learning with TRL, including SFT, DPO, PPO, GRPO, and reward model training.

Expert guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training

Expert guidance for implementing GRPO/RL fine-tuning with TRL for reasoning and task-specific model training.

P10 CTO mode — define strategic direction, design org topology, manage P9 teams. Use when user says 'CTO模式', 'P10', '战略规划', '架构委员会', or when facing cross-team architectural decisions. Produces: strategic input templates + org design.

Guides building Expo Router navigation with file-based routing, layouts, tabs, protected routes, and deep linking.

P10 CTO mode — define strategic direction, design org topology, manage P9 teams. Use when user says 'CTO模式', 'P10', '战略规划', '架构委员会', or when facing cross-team architectural decisions. Produces: strategic input templates + org design.

Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.

Guide federal systems through the NIST Risk Management Framework (SP 800-37 Rev 2) to achieve an Authorization to Operate (ATO), covering categorization, control selection, assessment, and continuous monitoring.

RNN+Transformer hybrid with O(n) inference. Linear time, infinite context, no KV cache. Train like GPT (parallel), infer like RNN (sequential). Linux Foundation AI project. Production at Windows, Office, NeMo. RWKV-7 (March 2025). Models up to 14B parameters.

Expert guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training

Install, initialize, verify, and troubleshoot RTK (Rust Token Killer) for AI coding agents. Use when you need to reduce shell-command token output, confirm that the correct `rtk` binary is installed, choose between Homebrew, install.sh, or Cargo installation, wire `rtk init` for Claude Code, Codex, Gemini CLI, Cursor, Copilot, Windsurf, Cline, or OpenCode, or use compact wrappers such as `rtk git status`, `rtk read`, `rtk grep`, `rtk test`, `rtk lint`, and `rtk gain`. Triggers on: rtk, rust token killer, token saver cli, rtk init, rtk gain, codex rtk, gemini rtk, opencode rtk, claude hook token reduction.

Expert guidance for GRPO/RL fine-tuning with TRL for reasoning and task-specific model training

Fine-tune LLMs using reinforcement learning with TRL - SFT for instruction tuning, DPO for preference alignment, PPO/GRPO for reward optimization, and reward model training. Use when need RLHF, align model with preferences, or train from human feedback. Works with HuggingFace Transformers.

R object-oriented programming guide for S7, S3, S4, and vctrs. Use when designing R classes or choosing an OOP system.

Train, evaluate, export, and run inference for monocular depth estimation models using Metric Depth Anything v2 or Relative Depth Anything architectures via the TAO toolkit.