I love both of those and actually only started playing Mini Metro this month. Such synchronicity(!), although mediated by whatever is probably happening on the Play Store, this is less surprising then it would have been 50 years ago.
Thanks. This relates to some questions I've got. I was playing around with the previous generation smaller models and found that i wasn't getting any speedups from the T1 and T2 binary/ternary models compared to standard Q4 quants of straight qwen3.6 models. I was wondering whether unpacking of the ternary encoding was impacting inference speed?
If that's the case then why not just train at Q2? I guess the counterargument is that then you lose the nice properties of things like the FairyFuse kernels. I wish there were some good discussions of these trade off.
I was wondering what a book keeper is, thinking it would be some kind of librarian. Isn't the accounting sense written as a single word, i.e. bookkeeper?
OT but how are y'all sharing your skills and agents across harnesses?
I have a bunch of Claude Code Plugins and yesterday asked Codex to make them accessible to itself. It wanted to rewrite most of it. I was hoping i could get by with some symlinks or something to avoid drift.
Not just RLHF but also RLVR, and isn't that the litter lesson though?
My sense of the Sutton Dwarkesh interview was that he was calling out that he didn't mean just longer datasets, but rather learning through exploration and that's exactly RL.
"a new distributed consensus service called Meerkat powered by a consensus algorithm called QuePaxa, published in 2023 by researchers at EPFL. QuePaxa differs from Raft in that all replicas can perform writes at all times, and progress is never halted due to a timeout"
Really, does this work now? What about NotebookLM? I was using it a lot until i realised it was only analysing the transcripts and not the video because i was mostly using it for technical ones with important charts.
Hi,
Yes I'm in the same boat as you - had to switch to US language instead of UK. I've been addiing the anglisised versions of words to my dictionary as I go along so it's becoming less of an issue over time. Maybe I'll switch to FUTO in order to not have to deal with this anymore. Gboard has one nice feature though in that I have multiple languages enabled so I get correct predictive completion in non-English languages.
For learning ClearFlow, I used the Games app available from the "Clearflow Games" section on their website: https://clearflowkeyboard.github.io/
I also have the issue of the thumb getting in the way so I spent a couple of days playing the games to get my layout memory up and then it became usable without frustration and I'm not looking back now although I occasionally still forget the odd letter location.
I think this is the right direction. I'm increasingly viewing AI as coworkers and explaining it as such to higher ups as well. My colleagues also have different strengths and weaknesses and i know what to check and what i can rely on more. Being able to interact with Claude like i do with them will help with that. Unfortunately I'll need it in MS Teams for that. (Pls spare me your rants about Teams. We also use Windows. Deal with it.)
I switched to ClearFlow a month or two ago after learning of it on Hackernews. It is available in GBoard.
I'm happy with the switch. Like any keyboard switch (I've gone from Qwerty to Dvorak and now a Colemak-dh derivative with about ten years on each) it takes some time to learn the layout. Overall I'm happy with it though and there are less frustrating misinterpretations and corrections needed.
This post was swiped on it with only two corrections and the second one was my fault as i misremembered a key location.
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