# The Situation I’ve been wrestling with a messy freeform text dataset using BERTopic for the past few weeks, and I’m to the point of crowdsourcing solutions. The core issue is a pretty classic garbage-in, garbage-out situation: The input set consists of only 12.5k records of loosely structured, freeform comments, usually from internal company agents…

[Million-unit AI robot army no longer a dream: Analyzing Foxconn’s three-pronged strategy](https://www.digitimes.com/news/a20250721PD203/foxconn-ai-robot-robotics-production.html?) [TSMC Reportedly Eyes 10-Year Boom from Humanoids, Backed by NVIDIA Jetson and Tesla’s Chips](https://www.trendforce.com/news/2025/06/27/news-tsmc-reportedly-eyes-10-year-boom-from-humanoids-backed-by-nvidia-jetson-and-teslas-ai-chips/)

Easy to put together, not super expensive. Options for the Moon phase, sunrise/sunset time and UV Index, so you would be able to see if the Moon influences the timechain and when to sun your balls 😀 Short video demo: [https://www.youtube.com/watch?v=7DtQNCBLffI](https://www.youtube.com/watch?v=7DtQNCBLffI) Github: [https://github.com/kovrom/circle](https://github.com/kovrom/circle)

AI-generated content is easy to spot these days: – The em dashes – The “It’s not X, but Y” – Snappy one-line sentences – Lots of emojis … Many of us use AI to edit text, build chatbots, write reports… What technique do you use to make sure the output isn’t generic AI slop? Do…

# [https://sharing.hopper.com/invite/ianm1xn](https://sharing.hopper.com/invite/ianm1xn)