One of my best and most productive work situations was remote with a week[0] together every quarter. Key to this was scheduling the next trip while we were together to make sure it was on the books. We got to meet new team members, share some meals together, work through new architecture designs with a whiteboard, and plan. Not much got done during that week, but we sure got a lot done each quarter.
[0]: This was actually Monday-Thursday with travel on Friday
Thanks for sharing. I've been on a path of algo music with JavaScript (I also do not enjoy JavaScript) and have mostly just guess-and-checked my way through it. I'm going to work through this as my advent of code project.
Yesterday I put up a little dictionary of synth sounds that I'm building out to help me on my journey (https://synthrecipes.org). The goal to be able to export any particular sound in a format for different live coding environments. Sounds are defined in a JSON format like https://synthrecipes.org/recipes/acid-bass.json. I'll open source it today so other can submit sounds.
Music is funny. I played the closed hi-hat sound (https://synthrecipes.org/#closed-hi-hat) a couple of times and my brain instantly started playing AC/DC's, Back in Black. I probably haven't listened to that song in 15 years and now I'm shuffling AC/DC on Spotify.
This Sonic Pi example really blew my mind when I first heard it. Such a rich sound out of three notes.
use_synth :hollow
with_fx :reverb, mix: 0.7 do
live_loop :note1 do
play choose([:D4,:E4]), attack: 6, release: 6
sleep 8
end
live_loop :note2 do
play choose([:Fs4,:G4]), attack: 4, release: 5
sleep 10
end
live_loop :note3 do
play choose([:A4, :Cs5]), attack: 5, release: 5
sleep 11
end
end
A lot of great recs in this thread, but I'll a couple others I didn't see listed yet:
Mort Garson: Mother Earth's Plantasia
Hiroshi Yoshimura: Surround
Satoshi Ashikawa: Still Way (Wave Notation 2)
Shameless plug... Search BirdyMusic.com in Spotify/Apple Music/YouTube Music to hear some ambient music algo generated based on realtime Birdnet detections and weather in my backyard.
Steve Jobs passed away the day after Siri’s release, and I don’t think anyone else had the confidence and internal credibility to push the hard organizational changes Siri needed, similar to when he moved Apple to a single P&L when he returned.
Until LLMs came along, there wasn’t much you could do to improve Siri’s underlying technology. You could throw a thousand monkeys at to add more phrases it could match on and improve the interface to let you know what you could do. But that’s about it.
LLMs would help a lot, but there was a lot of low hanging fruit. During my time at Apple I worked on some of the evaluation of Siri's quality and saw first hand how the org issues affected Siri's path forward.
Good question. While I had a fairly narrow view of a very large system, I'll give my personal perspective.
I worked on systems for evaluating the quality of models over time and for evaluating the quality of new models before release to understand how the new models would perform compared to current models once in the wild. It was difficult to get Siri to use these tools that were outside of their org. While this wouldn't solve the breadth of Siri's functionality issues, it would have helped improve the overall user experience with the existing Siri features to avoid the seemingly reduction of quality over time.
Secondly, and admittedly farther from where I was... Apple could have started the move from ML models to LLMs much sooner. The underlying technology for LLMs started gaining popularity in papers and research quite a few years ago, and there was a real problem of each team developing their own ML models for search, similarity, recommendations, etc that were quite large and that became a problem for mobile device delivery and storage. If leadership had a way to bring the orgs together they may have landed on LLMs much sooner.
Despite my positive experience between building systems based on intent recognition and how much better LLMs are than “1000 monkeys”, it seems like the two examples we have of LLM backed assistants - Google and Amazon - that it made them worse from reports.
If someone has the resources to do this, it is Apple. For a product that can be used by billions of people, having an engineer dedicated to a single intent wouldn't be that wasteful :D
Private repositories are only allowed for things required for FLOSS projects, like storing secrets, team-internal discussions or hiding projects from the public until they're ready for usage and/or contribution.
They are also allowed for really small & personal stuff like your journal, config files, ideas or notes, but explicitly not as a personal cloud or media storage.
So the ToS says only private repos that support FLOSS, but then backdoors into "small & personal stuff" which is pretty loose and up to Codeberg's discretion so probably not the best place for your private side project repos.
You're right, and after thinking about it a bit more, I think this TOS is actually more confusing than what came before. Saying explicitly that, e.g. MIT licensed software was allowed (because that license is approved by OSI), makes it unambiguous. This feels like if someone complained or had too many repos they're liable to get nuked from orbit. That being said Forgejo is FLOSS and this service is hosted for free so they're allowed to set whatever terms they want. I'll delete my upthread comment as it's misinfo.
No problem. I'm confused by it as well. I migrated a repo that is more source available than open source and didn't realize that it probably is against ToS until afterwards.
I also wasn't understanding the value looking at the first two examples, but the pricing packages example I do think I would struggle to implement in a clean way using traditional css.
What if the company selling the screwdriver kept telling you your could use it as a hammer? What if you were being bombarded with marketing the hammers are being replaced by screwdrivers?
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