218 karma · joined April 25, 2022
[1] https://candrewlee14.github.io/blog/2024-03-07_apple-vision-...
- looking at your hands
- looking at clocks
- trying to read
It’s funny that diffusion models often make those exact same mistakes. There’s clearly a similar failure mode where both are drawing from a distribution and losing fine details. Has this been studied?
With that being said, I’ve been doing some practice!
Recently, I tried the Apple Vision Pro and I wrote about my experience. If you’re interested about my formerly-skeptical opinion on the future of AR/VR, check it out :)
I happen to be super interested in systems programming (OSes, DBs, PLs), but I've worried that those fundamentals might be superseded by AI, whether through a higher-level abstraction or just better automated code generation. Glad to hear an experienced opinion to the contrary.
I think I'll need to come back and read this a couple more times to pull out all the advice here, I appreciate this much to chew on :)
My undergrad degree capstone project was a flow-based visual C. elegans strain builder[1]. The team worked with two researchers who taught us a lot about genetics and basic C. elegans biology. They are a fascinating model organism, and it was a super fun project to work on. Even though it's got a very small potential userbase, it did have a potential userbase (which was more than you could say about most capstone projects). We used some interesting technology to build it (Tauri[2]: Rust + Web Frontend), learned some biology along the way, and ended up with a great prototype.
Since none of the software team had any background in genetics, modeling the data was pretty difficult. We'd meet with researchers, they'd teach us new genetics concept, we'd build our models, then the next week they'd say "OH we forgot to tell you about this caveat", then we'd go back to the drawing board, update the schema (thank heavens for migrations), rinse and repeat. It was a lot of fun though :) I couldn't have asked for much more out of a capstone project.
At the same time, I really like go. No other AOT-compiled language I know of makes concurrency so easy: `go foo()`. It’s wonderfully simple and I love that using the language doesn’t cram my working memory. It feels like all the space is there for my problem. It isn’t the right tool for some jobs, and of course, you’re perfectly entitled to your opinion. But I think it’s a welcome tool in the toolbox.
I recently had to implement Raft in Go, and I don’t know of a better language for that. Feel free to inform me otherwise. The race condition checker, RPC libs, and simple concurrency let me focus on the algorithm implementation. The iteration speeds for me were super fast too since Go keeps compile times snappy.
These are all useful tradeoffs for me to keep in mind when deciding the right tool for the job. I wouldn’t consider these “lies” personally, but maybe I do have the wool pulled over my eyes :)