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DataFunTalk
DataFunTalk
Dec 15, 2024 · Artificial Intelligence

China's Large‑Model Survival Battle: How Start‑ups Face Giant Competition and Market Realities

The article analyses the fierce competition in China's large‑model market, contrasting the heavy‑asset compute race and talent‑driven challenges faced by startups against big firms, while sharing personal experiences, algorithmic hurdles, and potential niches such as embodied AI, finance models, and real‑time recommendation systems.

AlgorithmEmbedded AIartificial intelligence
0 likes · 15 min read
China's Large‑Model Survival Battle: How Start‑ups Face Giant Competition and Market Realities
Tencent Architect
Tencent Architect
Apr 6, 2022 · Artificial Intelligence

Award-Winning AIoT Projects from the 2021 TencentOS Tiny AIoT Innovation Competition

The 2021 TencentOS Tiny AIoT Innovation Competition showcased over 50 original projects, including award‑winning multi‑functional pedestrian detection devices, AI‑enhanced smart wheelchairs, and endangered‑animal recognition systems, each demonstrating low‑power embedded AI, edge computing, and cloud integration for diverse real‑world applications.

AIoTEmbedded AISmart Devices
0 likes · 8 min read
Award-Winning AIoT Projects from the 2021 TencentOS Tiny AIoT Innovation Competition
Tencent Architect
Tencent Architect
Apr 1, 2022 · Artificial Intelligence

TencentOS Tiny AIoT Showcase: Pedestrian Detector, Smart Wheelchair, Wildlife Tracker

The 2021 TencentOS Tiny AIoT Innovation Competition featured over 50 original projects, with award‑winning solutions such as a multi‑function pedestrian detector, a smart wheelchair powered by AIoT, and an endangered‑animal tracking system, all demonstrating low‑power embedded AI, cloud integration, and versatile real‑world applications.

AIoTEmbedded AIPedestrian Detection
0 likes · 10 min read
TencentOS Tiny AIoT Showcase: Pedestrian Detector, Smart Wheelchair, Wildlife Tracker
JD Retail Technology
JD Retail Technology
Aug 2, 2021 · Artificial Intelligence

Real-time Monocular Human Depth Estimation and Segmentation on Embedded Systems (HDES-Net)

The paper presents HDES‑Net, a lightweight real‑time monocular human depth estimation and segmentation network designed for embedded platforms, using MobileNetV1 backbone with ASPP and depth‑wise separable convolutions, achieving high accuracy on CAD‑60 and EPFL‑RGBD datasets while running at up to 199.93 FPS on a Tesla P40 and 17.23 FPS on a Jetson Nano after TensorRT optimization.

Depth EstimationEmbedded AIHDES-Net
0 likes · 8 min read
Real-time Monocular Human Depth Estimation and Segmentation on Embedded Systems (HDES-Net)