Guglielmo Camporese
249 posts

Guglielmo Camporese
@gucamporese
ai researcher @disneyresearch - prev applied scientist at @amazonscience (aws ai labs & alexa ai). tweets = personal opinions.











"You can order grocery online in Switzerland too" 🤡 Consumer convenience in 2026 can be (not in CH): • Open Wolt App • Buy meat from good quality butcher • Buy veggies, fruits and diary from organic shop • Buy fish, seafood from seafood place, etc (in general: buy everything from high quality specialty shop) • Pay, shop prepares the order, then delivered in < 20-40 minutes, all tracked with the app like an Uber Eats delivery order In Switzerland: • Only buy grocery from one industrial retailer (either Coop or Migros, for decent stuff) • Go to Coop site, spend 5 minutes registering • Get some good Swiss beef steak in • Issue 1: reach 100 CHF in spending or they won't even ship it (= if you're 1 or 2 people, it's unpractical: 100 CHF of fresh food will expire) • Issue 2: SCHEDULE DELIVERY FROM TOMORROW (what the fuck) • Issue 3: one hour of delivery time, scheduled days in advance. Bro 😂 Do I have to create a Google Calendar to receive grocery? • Issue 4 (low prio but worth mentioning): seems also like delivery fee is not even free after 100 CHF of spending (it's like 7 CHF or something) It's a 6/10 experience, compared to 9/10 experience you can have in many places like Warsaw, Cyprus, Croatia etc. Also: • Favorite ice cream shop doesn't do delivery (the one that delivers on Uber Eats is too mid)



I packaged up the "autoresearch" project into a new self-contained minimal repo if people would like to play over the weekend. It's basically nanochat LLM training core stripped down to a single-GPU, one file version of ~630 lines of code, then: - the human iterates on the prompt (.md) - the AI agent iterates on the training code (.py) The goal is to engineer your agents to make the fastest research progress indefinitely and without any of your own involvement. In the image, every dot is a complete LLM training run that lasts exactly 5 minutes. The agent works in an autonomous loop on a git feature branch and accumulates git commits to the training script as it finds better settings (of lower validation loss by the end) of the neural network architecture, the optimizer, all the hyperparameters, etc. You can imagine comparing the research progress of different prompts, different agents, etc. github.com/karpathy/autor… Part code, part sci-fi, and a pinch of psychosis :)








