LLM

I started writing weeknotes as part of learning generously when I started at Recurse. But the distinction between Recurse and non-Recurse has increasingly blurred and I’d like to continue making weeknotes after I never graduate. To that end, I’m trying out a new format for my weeknotes. Tell me what you think! See previous weeknotes via the weeknotes tag. Updates Decided to extend to a 12-week batch at the Recurse Center. You can continue following my progress by filtering for posts with the Recurse tag. “QS Rubicon”: After 8 years of doing extensive self-tracking and ML-powered Quantified Self projects, I’ve decided to just stop collecting most data. I have plenty to say about the whole experience, so it should probably be its own blog post or talk. But the immediate feeling of being “out of control” is still something I’m trying to reflect on. Inputs / outputs Wrote and published 4 posts Make games people play: What Paul Graham doesn’t tell you about delighting 7-year-olds. AImong Us: a reverse Turing Test game: Can you outwit a gang of LLMs? What OpenAI’s o1 really means: The AGI is dead. Long live the AGI. RC Weeknotes 05: Move fast and make games. AAAHHH! The Creative Coding prompt at RC this week was “Aaaahhhh!” I whipped up something between a click trainer game and a psychological torture device. It also works on mobile if you like torturing yourself on the go. Participated in an intense Rock Paper Scissors tournament at RC. It involved multiple rounds of submitting a Python bot (with no dependencies) that played 200 rounds against some simple bots as well as the other participants’ bots. I managed to finish 3rd using a third-order Markov model with a stop-loss heuristic to switch back to the Game Theory optimal random play style. Made massive improvements to my dotfiles for better macOS package management with advanced Homebrew wizardry, and better LSP configuration for Python and Markdown in NeoVim. Improved PR to llm with tests. Try AAAHHH full screen at aaahhh.vercel.app ...

Week 5 of Recurse: Move fast and make games.

The AGI is dead. Long live the AGI.

Can you outwit a gang of LLMs?

An open source newsreader app I built using LLM embeddings to semantically prioritise arXiv and Github updates.

Winning EF’s Bio x AI hackathon with a multimodal LLM for lab protocol automation.

The past 18 months in AI have been a whirlwind-clusterfuck of acceleration, innovation, and chaos.

We used LLaVA and Claude to build a crazy multimodal LLM health assistant. OpenAI made it redundant the next week.

There is a trifecta of variables that just about everyone building generative AI systems cares about — cost, quality, and latency. As is often the case in computing, there is a trade-off between these properties. And all three are bought with the currency of performance.