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@pyloxsystems

Pylox Systems Inc.

Emilio Girard's lab. Energy measurements for learned policies on embedded hardware, speculative decoding research, on-prem inference on NVIDIA Blackwell.

Pylox Systems Inc.

This is the lab of Emilio Girard (Montréal). One person, a DGX Spark, two Jetsons, and rented Blackwell cards when a run needs them. Site: emiliogirard.com.

Public work here:

Repo What it is
joules-per-task Hardware energy measurements for learned policies on a Jetson Orin Nano: a VLA policy at 963 J per successful task cut to 489 J, plus a four-policy spectrum. Paper draft, harness, raw logs.
per-block-drafter-selection 7,309 speculative-decoding blocks with four drafters verified on identical prefixes. Workload routing is a null; per-block selection captures 61% of the oracle gap at 43% of the cost.
risk-aware-terrain-jetson IEEE T-IV 2026 terrain-navigation reproduction on the Orin with energy numbers.
cbcl-pr-jetson Class-incremental learning reproduction, five seeds, INT8/FP16 ablation.
pylox-vision-demo 8-camera detection and re-identification stack on Jetson.

Models on Hugging Face: huggingface.co/pyloxsystems. Every card carries a benchmark table, including the three adapters that lose to their base model.

Contact: pyloxsystems@gmail.com

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  1. pylox-vision-demo pylox-vision-demo Public

    8-camera on-prem AI security system. Frigate + OSNet ReID + TensorRT FP16 on Jetson Orin. 74K events processed at pilot site.

    Python

  2. pylox-fine-tune-pipeline pylox-fine-tune-pipeline Public

    Pylox Forge fine-tune pipeline — on-prem LLM fine-tuning + deployment for NVIDIA DGX Spark. QLoRA, multi-tenant vLLM, benchmark suite.

    Python

  3. deimos-autonomy deimos-autonomy Public

    URC 2026 autonomy stack for Space Concordia DEIMOS rover. FAST-LIO2 + Nav2 + dual-EKF + USGS DEM planner + ArUco visual servo + YOLOv8n TRT INT8 (4.6 MB, 446 FPS on Orin Nano).

    Python

  4. cbcl-pr-jetson cbcl-pr-jetson Public

    TensorRT FP16/INT8 reproduction of CBCL-PR (Ayub & Wagner, IEEE TCDS 2023) on Jetson Orin Nano. 50-increment CIFAR-100 class-incremental ablation across precisions, latency benchmark harness, resea…

    Python

  5. risk-aware-terrain-jetson risk-aware-terrain-jetson Public

    Edge-deployable approximation of Hu et al. T-IV 2026 risk-aware terrain navigation. APPSMC + paper-exact Eq. 11-13 risk + closed-form CVaR on Jetson Orin Nano Super: DINOv2 FP16 12.6ms / ResNet-50 …

    Python

  6. joules-per-task joules-per-task Public

    Hardware energy per successful task for a vision-language-action policy on a Jetson Orin Nano: 963 J cut to 489 J with no accuracy loss, plus a four-policy energy spectrum. Paper draft, harness, ra…

    Python

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