"compatible" instead of "comparable."
It boggles my mind how you can train a frontier model but not write a tweet without an obvious typo.
HN user
"compatible" instead of "comparable."
It boggles my mind how you can train a frontier model but not write a tweet without an obvious typo.
does it support fts/vector on edges of the graph?
are you a maintainer on npm?
congratulations!
We think this is a pretty sad day for research: Some context about Chroma's model. https://x.com/maxrumpf/status/2037365748973384154?s=20
This is the tech report for a model I helped work on. I'm biased, but it turned out very well.
We essentially let the model learn to retrieve like a human would: Make a first search, read the results, and then make another. This lets the model be vastly better than pre-programmed pipelines. We test this extensively and compare against implementing this with API models (like Sonnet 4.5 and GPT-5.1). SID-1 compares favorably.
Happy to answer any questions or get feedback. First and foremost: Enjoy the read. It's much more detailed than most tech reports.
This comment section is scary. Hacker news advocating FOR nanny technology?!
Excel is awful in almost every way, but I just wish more software was as customizable.
I can get (even more) customization by using pandas etc., but it's usually much slower and you get much less of an intuition about the data.
I imagine color consistency will be such a pain here.
The weirdest thing people do is make up criteria that YC supposedly uses to reject people. There was such a huge diversity in our batch: From 20 y/o to 40+. Foreign, domestic. Credentialed, not credentialed. $1M rev run rate, $0 run rate. Just apply.
The abstract and the rest of the paper don't really match imo. It's not really allocating more to some sequences, but just introducing ~dropout. Might be different sides to the same coin, but was still a weird read.