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#Edge computing (8)

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Bothlent RDM-Lite-X1 AI Voice Interaction Module

Bothlent RDM-Lite-X1 AI Voice Interaction Module

RDM-Lite-X1 combines a sound card and Android mainboard in one voice-interaction module for AI robots, intelligent voice terminals, and industrial IoT systems. It uses a microphone array and a 6 TOPS NPU to support 1-5 m interaction, 180- or 360-degree sound-source localization, directional pickup, environmental sound classification, multi-speaker separation, and 0.3-second wake-up. It connects to Doubao, Coze, Qwen, Tencent Hunyuan, and MiniMax, supports secondary Android application development, and adds visual detection to acoustic processing through the AVSS multimodal approach.

COMPONENT

AI Voice ModuleSound Source Localization
CopperPilot’s Jetson AI Camera Carrier Board
0:47

CopperPilot’s Jetson AI Camera Carrier Board

@Alacritic_Super · 89 views · 2026-10-29
CopperPilotJetson
SmolWAM: A World-Action Model Shrunk to 57ms on the Edge
1:07

SmolWAM: A World-Action Model Shrunk to 57ms on the Edge

@robotsdigest · 230 views · 2026-10-13
World ModelsEdge computing
Fine-tune, Convert and Deploy Language Models on NVIDIA Jetson with Unsloth and llama.cpp

Fine-tune, Convert and Deploy Language Models on NVIDIA Jetson with Unsloth and llama.cpp

Official Jetson AI Lab tutorial: fine-tune models directly on Jetson with Unsloth and JetPack 7.2 using memory-efficient QLoRA, export to GGUF, and run locally with llama.cpp. Two hands-on examples: Qwen3.5-4B vision-language model on Jetson Orin Nano (LaTeX OCR fine-tuning), and NVIDIA Nemotron 3.5 Lightning 30B-A3B on Jetson AGX Thor (3 training steps in 44.8s, 66.1 tokens/sec with Q4_K_M quantization). No cloud required.

BLOG

NVIDIAJetson
Jetson AI Lab Tutorial: Fine-tune and Quantize AI Models on Jetson

Jetson AI Lab Tutorial: Fine-tune and Quantize AI Models on Jetson

@NVIDIARobotics · 746 views · 2026-08-31
NVIDIAJetson
Rockchip RK3588 8-Core AIoT Application Processor (SoC)

Rockchip RK3588 8-Core AIoT Application Processor (SoC)

The RK3588 is Rockchip's high-performance application processor for ARM PCs, edge computing and AIoT terminals, and is widely used in robot main controllers and edge-AI modules. Built on an 8nm process, it integrates 4x Cortex-A76 plus 4x Cortex-A55 cores with a shared 3MB L3 cache, an ARM Mali-G610 MP4 GPU, and a 6 TOPS triple-core NPU supporting INT4/INT8/INT16/FP16/BF16/TF32 mixed-precision operations. Its memory interface supports four-channel 64-bit LPDDR4/LPDDR4X/LPDDR5 with up to 32GB address space, plus eMMC 5.1 HS400 storage. Video capabilities include H.265/VP9 8K@60fps decoding and H.264/H.265 8K@30fps encoding, while the hardware ISP handles up to 48-megapixel input with HDR, 3A, LSC and 3DNR. Connectivity covers HDMI 2.1/eDP/DP/MIPI, PCIe 3.0/2.0, SATA 3.0, RGMII, USB 3.1/2.0 and Type-C, in an FCBGA1088L package (23x23 mm, 0.65 mm ball pitch).

COMPONENT

SoCRK3588
$8 ESP32-S3 Runs 29M-Parameter LLM
0:19

$8 ESP32-S3 Runs 29M-Parameter LLM

@ardchain · 566 views · 2026-07-24
Edge AIESP32
NVIDIA Cosmos 3 Edge: 4B Edge World Model for Robots
0:14

NVIDIA Cosmos 3 Edge: 4B Edge World Model for Robots

@Xudong07452910 · 664 views · 2026-07-21
NVIDIACosmos 3 Edge

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