#Data/Training

AIShanghai company Maniformer has opened a crowdsourcing platform that pays ordinary people to record everyday tasks, such as folding clothes or making tea, as training data for robots. The platform lists 22 categories, over 5,000 task types and more than 50,000 real scenes, and nearly 20,000 users signed up during a closed test from August 15 to September 15. Maniformer also announced a RMB 100 million subsidy plan and a goal of 1 million daily active users and 1 million robot trainers within two years.

AIGeekPark reports that Krinwave, a Shenzhen company, has completed a new 400 million yuan round with XVC and Sequoia China as new investors. The company says its low-frequency ultrasound captures brain structures through the skull, which conventional high-frequency devices cannot, and it aims to supply hardware and its kOS software platform to brain-computer interface and NeuroAI groups.

AISharpa has unveiled the D01 humanoid robot, the W02 dexterous hand and the AE01 exoskeleton data glove at IROS. The article says the D01 has full-body electronic skin, and the W02 has 21 active degrees of freedom and a hand about 30% smaller than the W01.

AIDeveloper Niko1221 open-sourced Strata, an engine that runs quantized Qwen3.8-Flash-Next, a 125B-parameter model, on consumer GPUs with at least 12GB of VRAM. It loads the MoE model into RAM and keeps only frequently used experts in VRAM, and uses a lightweight model for speculative decoding. On an RTX 5070 with 64GB RAM, the Q2_0 quantization generates 94 tokens per second, and an RX 9070 XT reaches 60 tokens per second.

AILiving Models paired Gemma 4 with BOTANIC-1, a model trained on plant DNA across 320 species, to identify which mutations alter crop traits. In a melon yield test, the pipeline ranked the target mutation first out of 2,494 candidates in under four minutes. Google AI says the approach could help researchers engineer climate-resilient crops faster than traditional breeding trials.

AIEmpero announces Homebrew, an open agent that builds AI models for users. According to the post, users describe what they want, and the agent picks a base model, prepares data, sets parameters, and runs training. The project is available on GitHub at empero-org/homebrew-ai.

AIMind Lab unveiled Mint Recursive, a post-training and inference platform for industry use, alongside Macaron-V1.1, a model post-trained entirely on it. Macaron-V1.1 is a 752-billion-parameter model built from GLM-5.3 with four two-billion-parameter LoRA expert modules for chat, agents, coding, and generation. The platform is serverless and bills by token usage, and it collects feedback from models in use to support continued training.

AIQianjue Technology founder Gao Haichuan argues that robotics will not see one breakthrough that suddenly lifts the whole industry, and he judges the company by deployment results rather than research papers. Qianjue, founded in 2023, has completed a Series A+ round worth a nine-figure RMB sum, with first orders coming from restaurant, cleaning, and hotel service robots. Gao says customers care about task completion, failure rates, and price rather than whether a predictive world model is used.