SenseCap Watcher Updates: Use self-hosted LLaVa!

SenseCAP Watcher has three big feature updates: self-hosted LLM with #llava and #llama models, custom local model training with @EdgeImpulse and finally push-to-talk functionality for task creation on the go. Based on @EspressifSystems #esp32 S3 and #himax HX6538 (Cortex M55 + Ethos-U55), made by @SeeedStudioSZ Watcher runs a local neural network inference with #ai accelerator and if necessary sends the data for further analysis for a multi-modal #largelanguagemodel, making it an intelligent conduit for the LLMs! Kickstarter campaign link: https://www.kickstarter.com/projects/seeed/sensecap-watcher-open-source-ai-assistant-for-smarter-spaces?ref=2cz4au Wiki page: https://wiki.seeedstudio.com/getting_started_with_watcher/ Landing page: https://www.seeedstudio.com/watcher Fruit detector project: https://studio.edgeimpulse.com/public/516135/live https://www.kaggle.com/datasets/mbkinaci/fruit-images-for-object-detection/data