时令 发自 凹非寺 量子位 | 公众号 QbitAI 谷歌开源Gemma 3 270M闪亮登场！ 只需几分钟即可完成微调，指令遵循和文本结构化能力更是惊艳，性能超越Qwen 2.5同级模型。 此模型小巧又高效，可以直接在浏览器里本地运行，不用联网，也能生成有创意的内容，比如睡前故事。 发布当天，网友也懵了：以为是270B，结果居然才0.27B。 不仅如此，还有人使用这款迷你模型构建了自己的OCR应用程序。上传一张图片或PDF文件，即可用LLM即时将其转换为结构化的 Markdown格式。 值得一提的是，新模型只有 4个注意力头 ，比Qwen 3 0.6B少12个，真是切实符合其轻量化的定位。 下面让我们一起看看这款迷你Gemma 3到底有哪些亮点？ Gemma 3 270M核心功能 Gemma 3 270M充分体现了这种" 为工作选择合适工具 " 的理念。 作为一款基础模型，它开箱即可精准遵循指令，而微调能彻底释放其真正实力。 经过专门优化，它在文本分类、数据提取等任务中，都能做到准确、快速且成本可控。 简单总结，新模型的核心功能可概括为以下4部分： 紧凑且高效的架构 这款新模型共包含2.7亿参数，其中1.7 ...

Core Viewpoint - The embodied intelligence industry is expected to experience explosive growth by 2025, driven by technological advancements and application traction, shaping both the technical roadmap and commercialization pathways [1]. Group 1: Technological Developments - Upgrades in perception capabilities and multimodal integration are crucial for the development of embodied technologies, with a focus on tactile perception, particularly in dexterous hands, enhancing precision and feedback [1]. - Multimodal sensor fusion technology allows robots to process various types of information simultaneously, significantly improving environmental perception accuracy and comprehensiveness [1]. - Large model-driven algorithms are enhancing robots' understanding of the world, particularly in humanoid robots, by improving perception, autonomous learning, and decision-making capabilities [1]. - Lightweight model design is becoming a pressing need for industry implementation, requiring low-computation, multimodal, and cross-platform models [1]. Group 2: Simulation and Data Ecosystem - The continuous improvement of simulation environments and data ecosystems is vital for embodied intelligence, providing efficient training platforms for robots [1]. - Simulations based on physical world principles help in modeling and analyzing various phenomena, aiding robots in understanding physical interactions and operations [1]. - The alignment of simulation and real-world environments is a key challenge that researchers are working to overcome [1]. Group 3: Community and Resources - The "Embodied Intelligence Heart Knowledge Planet" serves as a technical exchange platform for various stakeholders in the field, including members from renowned universities and leading robotics companies [6]. - The community has compiled over 40 open-source projects and nearly 60 datasets related to embodied intelligence, along with mainstream simulation platforms and various learning pathways [6][12]. - Members can access a wealth of resources, including research reports, technical learning routes, and job opportunities in the embodied intelligence sector [11][14].