Laetus
The science of personal luck
What it does
Laetus is a behavioral analytics platform exploring how people make decisions under uncertainty. It combines probability, personal observations, lottery experiments, blockchain randomness, and AI-assisted analytics into one research framework. Instead of encouraging gambling, Laetus helps users study decision patterns, compare behavioral signals, and better understand their own responses to uncertainty through long-term observation.
Explore luck through probability, behavioral analytics, and real-world experiments. No gambling. Free to use.
Laetus explores how people make decisions when certainty is impossible. Using behavioral analytics, probability, and real-world experiments, it helps you better understand your own patterns under uncertainty. A three-minute introduction to the ideas, experiments, and philosophy behind Laetus. Laetus is now available on Android, iOS and the Web. The release introduces Bitcoin Lottery, expanded behavioural analytics, and completes the project's second large-scale public experiment. Laetus is an independent research project supported by its community. Learn how you can help → When reliable facts are available, good decisions are usually straightforward. But many real-life situations involve…from laetus.app
Does the same job
all alternatives →


Stock Market GPT for Investment Research2024 · ▲127AI powered stocks, balance sheets, analyst report comparison


More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com


Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com


Launched alongside, August 2026
the whole month →- TL
Life & fun · 10d ago · louisabraham.github.io


- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com