Kled V3 推出数据采集平台，实验室可指定所需数据，平台能在 72 小时内向 50 万+ 自愿贡献者网络部署采集任务。平台提供覆盖图像、视频、音频、文本和标注的 108 个可配置模板，贡献者用手机按指令和示例完成采集。其核心价值在于缩短反馈闭环：定位模型失败点、转化为采集任务、获取真实世界新样本、再训练评估。
You can't scrape a dataset that doesn't exist yet.
Think about training a model on people performing a specific task, in a specific environment, from a specific camera angle.
Someone has to go and capture those examples.
This is what makes Kled V3 interesting.
Labs can specify the data they need, and Kled can deploy collection tasks to its network of 500,000+ opt-in contributors within 72 hours.
108 configurable templates across image, video, audio, text, and annotation. Contributors capture the data on their phones, with instructions and examples of what qualifies.
The opportunity here is a much tighter feedback loop:
Identify where a model fails.
Turn that failure into a collection task.
Get new examples from the real world.
Train and evaluate again.
The ability to repeatedly collect the exact data a model is missing could be very powerful.
This is Kled V3. We've solved data collection for artificial general intelligence. Any consumer dataset that can exist, can now be collected from physical reality in under 72 hours. All powered by the largest and most comprehensive data application layer on the planet. (Thread)在 X 查看被引用的帖子
来源：elvis · x.com