accraze

hell yeah im doing similar! it's been a lot of fun so far. My review agent has a very large backlog, but MusicBrainz + AcoustID have been super helpful for figuring metadata tags etc.

https://github.com/accraze/musiclib-agent

RIP - my coding playlist is filled with his work, love all the Ashra & Ash Ra Tempel material too.

Good, I worked at WMF for a bit and the fundraising narrative was one of many reasons why I left. Wikipedia is doing just fine, but there are just way too many “special projects” that need to be reconsidered. Also way too much frivolous international travel for staff members.

For inference, we extended KServe (previously KFServing from Kubeflow) to fit our on-prem cluster needs. Highly recommended!

+1 for Searx - love the idea of meta-search

Wow, Bungle's California tour is the stuff of legends. I've only seen videos but I still can't figure out how they managed to pull it off live. Never saw Bungle, but I did see Fantomas on the Suspended Animation tour, which was another one of those albums I have no clue how they managed to perform night after night.

Agreed! I saw Magma in Portland, OR on their 2016 tour. I remember how effortless they made everything look, all the songs seemed to blend in and out of each other, so surreal. It felt like I was watching some intergalactic opera/theater presentation, probably one of the best concerts I've ever seen. Wish I could understand Kobaïan...

agreed! org-mode is seriously the most lightweight tool i use on a daily basis. also the various exporters have helped me out more times than i can count now.

i recently moved over to mediawiki due to work, but it is a behemoth compared to org-mode.

+1 for Merzbow

IMO nothing else in Funkadelic's catalog came close to 'Maggot Brain' except maybe 'Good Thoughts, Bad Thoughts': https://www.youtube.com/watch?v=rlHpaypcQrw

I had forgotten about this track, thanks for reminding me - revisiting Up for the Downstroke this afternoon

Nice, I've been using org-roam/org-mode for the past year and really love it now. Also been using org-journal as a sort of zettlekasten box for fleeting notes and linking to other stuff. Org-mode is really fantastic for this IMO, it's definitely been worth the learning curve.

+1 for both Cheapskates Guide and Ran Prieur, both very influential to me in different ways!

Interesting, can you go into more detail about how you discover new music? I used to use Discogs quite a bit, but I think there is more potential for "discoverability" on Wikipedia in some sense.

I make experimental tape collage gloom-hop/psych stuff as Idol Eyes: https://idoleyes.bandcamp.com/

also I run a small experimental record label that does tapes + lps: https://sunhypnotic.bandcamp.com/

Are you me? I also work in ML and am raising a child in a small seaside town. Your comments are very similar to my experience. I was told going remote and leaving the city was career suicide, but it's been quite the opposite. The amount of assumed travel (pre-covid) was a bummer and often happened at inconvenient times at multiple companies, but I still wouldn't trade it. I never talk about tech outside of work, which is nice, although a little lonely at times. In some ways I think my worldview has broadened by not living in a tech hub anymore. Work-life balance is super healthy, I don't spend as much time in front of screens anymore either. The pros totally outweigh the cons in my opinion.

I think "participatory" means something similar here within an ML context. It favors building community-based algorithmic systems and focuses on lowering the barrier to participation, so that non-expert users can be involved during the machine learning development cycle.

I'm not aware of any seminal papers per-say, although here are a few that I've read recently... first one is something I maintain at $DAYJOB:

1) Halfaker, A., & Geiger, R. S. (2020). Ores: Lowering barriers with participatory machine learning in Wikipedia. ArXiv:1909.05189 [Cs]. http://arxiv.org/abs/1909.05189

2) Martin Jr. , D., Prabhakaran, V., Kuhlberg, J., Smart, A., & Isaac, W. S. (2020). Participatory problem formulation for fairer machine learning through community based system dynamics. ArXiv:2005.07572 [Cs, Stat]. http://arxiv.org/abs/2005.07572

Also checkout PAIR: https://research.google/teams/brain/pair/

Alot of IML seems to focus on building interfaces, so this one was pretty good:

1) Dudley, J. J., & Kristensson, P. O. (2018). A review of user interface design for interactive machine learning. ACM Transactions on Interactive Intelligent Systems, 8(2), 1–37. https://doi.org/10.1145/3185517

Three papers stick out for me in the IML / participatory machine learning space this year:

1) Michael, C. J., Acklin, D., & Scheuerman, J. (2020). On interactive machine learning and the potential of cognitive feedback. ArXiv:2003.10365 [Cs]. http://arxiv.org/abs/2003.10365

2) Denton, E., Hanna, A., Amironesei, R., Smart, A., Nicole, H., & Scheuerman, M. K. (2020). Bringing the people back in: Contesting benchmark machine learning datasets. ArXiv:2007.07399 [Cs]. http://arxiv.org/abs/2007.07399

3) Jo, E. S., & Gebru, T. (2020). Lessons from archives: Strategies for collecting sociocultural data in machine learning. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 306–316. https://doi.org/10.1145/3351095.3372829

Also a great read related to IML tooling for audio recognition:

1) Ishibashi, T., Nakao, Y., & Sugano, Y. (2020). Investigating audio data visualization for interactive sound recognition. Proceedings of the 25th International Conference on Intelligent User Interfaces, 67–77. https://doi.org/10.1145/3377325.3377483

lol +1 for audio libraries / drivers on linux. spent many hours on the "battle of configuration".

+1 for Loop-Finding-Jazz-Records. Jan Jelinek's work as Farben is also really great for programming, very organic yet subtle techno.

I've used AWS quite a bit and recently started using GCE for a project. One thing that stands out is Google Cloud Platform does not feel as mature as AWS, some features are still beta or invite only (like Cloud Functions for serverless code). Also, AWS I believe has more data center coverage around the globe.

One major pro is Google Cloud's pricing was much more straightforward and easier to estimate.

some sort of NLP/RNN chatbot thing

Seconding this, docs are some of the best way to get involved. Alot of open source docs are very bare bones and maintainers are usually more than happy to get a docs PR.

I've been using GoCD for the past couple of months and I'm really liking it so far. Its very flexible and relatively straight-forward to setup on your own VM. The plugins work similar to the way Jenkin's does it. Also the UI is very clean.

soundslice is awesome!

yeah I would like to know about this too, any sort of NLP tools for Chinese or Japanese would be helpful.

Homebrew is what keeps me working on a Mac, plus now that Docker for Mac is out....

Awesome! I made mix #21 under the name Idol Eyes a couple years back, cool see this site is still going strong :)