Core Insights - Qunche Intelligent recently completed a new round of financing led by Alibaba Group, with multiple existing shareholders participating. The funds will be used to accelerate technology product development, implement embodied applications, and expand industry ecosystems [2][4]. Group 1: Company Overview - Qunche Intelligent was established at the end of 2023 and has previously completed several rounds of financing totaling hundreds of millions in Pre-A++ and Pre-A+++ rounds [4]. - The company focuses on embodied intelligence technology, rapidly iterating its self-developed large models for the physical world and launched the upgraded product Noematrix Brain 2.0 this year [4][8]. Group 2: Technological Advancements - Qunche Intelligent has made significant breakthroughs in key technology areas, including a no-ontology data collection scheme, a universal end-to-end model scheme, and a large-scale deployment system for human-machine collaboration [4]. - The company aims to streamline the entire process from data collection to deployment, covering the complete technical chain from data acquisition, model pre-training to post-training [4]. Group 3: Market Position and Collaborations - Qunche has established partnerships with several leading companies in the retail and home sectors to promote the mass delivery of integrated hardware and software embodied intelligence solutions [6]. - The company plans to leverage its advanced large model products and data-to-model closed-loop capabilities to continuously provide innovative and practical embodied intelligence solutions to clients and partners [6]. Group 4: Leadership and Vision - Qunche Intelligent is led by Professor Lu Ce Wu, a prominent figure in the field of embodied intelligence, who possesses both academic depth and industry experience, enabling the company to have full-stack capabilities from technology research and development to commercial delivery [8]. - The company’s core technology is based on force-driven embodied intelligence, breaking through traditional trajectory control frameworks to build a comprehensive autonomous decision-making system that covers perception, cognition, planning, and execution [8].