I once worked for a company who had an accountant who used a gaming laptop. They didn't play games, but it was the only decent one they could get with a number pad.

I really enjoyed The Quarry. Although I killed pretty much everyone.

Ooo. I haven't listened to most of those, might to give them a go. I did enjoy The Doctors Daughter though. Jago & Litefoot probably still my favourite BF spinoff.

I haven't used Twitter much in years really. But after switching to Lemmy during the reddit API debacle I thought I'd give it a go and am really enjoying it. I've set up a ton of filters to block out stuff I don't want to see, and joined a couple of instances for two different personas. I'm not using the official mobile client. On Android I use Tusky and Megalodon. Tusky is my daily driver and feels like how I remember the Twitter app from 7 or 8 years ago. Megalodon is nice for cross instance discovery, but has a couple of UI quirks that prevent me from using fully. My SO uses Ice Cubes on iOS and that looks pretty sweet. Personally I found the switch comparable to Lemmy. It took me a month or two to build up a good number of active people to follow to get to the stage of having an interesting feed. It also seems to have got a lot more active in the last week. When I have dropped into Twitter it's a dumpster fire on top of a cesspit. I don't think I could go back. I'd absolutely recommend giving Mastodon a go.

I imagine that the compression is linked to the dataset, so if you update or retrain then you maybe lose access to the compressed data.

The research specifically looked at lossless algorithms, so gzip

"For example, the 70-billion parameter Chinchilla model impressively compressed data to 8.3% of its original size, significantly outperforming gzip and LZMA2, which managed 32.3% and 23% respectively."

However they do say that it's not especially practical at the moment, given that gzip is a tiny executable compared to the many gigabytes of the LLM's dataset.