AI tools for “ui”

…detection with a BERT text encoder for language-guided detection — detects objects described by text prompts without a fixed class vocabulary. Use when training, evaluating, exporting, quantizing, or running…

…tao_automl, bayesian search, hyperband, ASHA, LLM-guided search, autoresearch, or wants to tune train/evaluate/inference/distill/prune/quantize for a TAO network. Model actions use the resolved image; venv…

…a HuggingFace ViT/DETR/ SegFormer into tao-pytorch", "build a TAO trainer + deploy pipeline for an HF CV model", or pastes a HuggingFace model URL/ID and wants it turned into a TAO model. Covers the full 7-phase…

…video training data", "generate video QA datasets", "build CoT reasoning traces from videos", "auto-label videos", or run the video_reasoning_annotation pipeline. Triggers include "video annotation", "video CoT",…

…annotations from images with KITTI labels, build region descriptions, produce grouped grounding phrases tied to bboxes, run a double-check verification pass on grounding expressions, auto-label traffic /…

…evaluate quality (nn_score), and search per-sample (guidance, crop_ratio) parameters. Three modes: full (Phase 0→7: finetune then generate), finetune_only (Phase 0→1: train only), inference_only (Phase 0, 2→7:…

…"run video_clip train/evaluate/inference/export", "build a Video-CLIP TensorRT engine", "InternVideo2-CLIP on KPI chunks", or "TAO video_clip on vadr1_chunks…

…backend image, optionally plans explicit clean source builds, prepares checkpoints, validates the first update in-process, and returns token-weighted losses and task-aware…

…reference implementation (ONNX, labels, custom parser required). Use when building a new perception microservice repo, validating the VSS integration contract, extending that scaffold for segmentation frame-mask…

…compose mount gotchas, nvinfer config, runtime TRT engine build, deployment, and a segmentation-capable model addendum…

…Doctor for new operators, changes, or repairs, using requirements, a partial spec, reference code, or an existing operator. Accept text, files, and public URLs. Record unresolved requirements without inventing…

Install and configure the NVIDIA PVA SDK, NVVPU compiler, and L4T target runtime from the selected installation guide. Use when the user requests PVA environment setup on a development host and board.

…host and VPU code, independent CPU reference, sample, build integration, tests, and documentation. Verify with pva-build-test and use pva-debug within the configured attempt…

…for requested NVIDIA PVA work. Use before Spec, OpGen, Build-Test, or Debug. Verify references to the installed SDK documentation, inspect only the requested capabilities, and prove that either NVVPU or ASIP/Chess…

…and return the repaired source to the caller for a fresh…

Build and verify an NVIDIA PVA operator with the public PVA SDK. Use alone or from OpGen. Run optional EMU correctness, a fresh L4T build with the NVVPU or ASIP/Chess backend that Doctor proved, direct-SSH Tegra…

Use when a user asks to build, optimize, backtest, rebalance, or analyze a stock portfolio with Mean-CVaR, Mean-Variance/SOCP variance caps, efficient frontiers, scenario generation, or NVIDIA cuOpt.

Official NVIDIA-authored guidance for PhysicsNeMo ShardTensor domain parallelism — integrate domain parallelism into training/inference scripts (new or existing) with DDP or FSDP2, write and register shard patches to…

Official NVIDIA-authored guidance for navigating PhysicsNeMo — pick the model, datapipe, or example for a SciML/AI4Science task (surrogates, forecasting, downscaling, physics-informed, inverse, generative). Points at…

…Robotics, Genesis, and Drake. Evaluate Newton first for suitable new workflows, select ovnewton when supported shared-stage integration adds value, then verify setup. Use for simulator comparisons, migration…