Checked with vast Amon Tobin discography with all his aliases as his discography is a very complicated edge case for any recommendation algorithm: Stone Giants/Figueroa is listened by people who like Amon Tobin but the former is pure indie rock and folk and should not show Amon Tobin itself but more something like Current93.
Don’t know how to solve this issue but it but it break any recommendation algorithm for last 20 years
That judgment is an essential skill of an experienced programmer, and it is required at every level of the big picture, from high level architecture decisions to the development of particular features: what should I polish and what needs to be developed fast? How exactly should I cut corners in the safest way?
So lastfm become relevant again because slop will not appear statistically in user scrobblings because of vast amount of "musicians" required to be profitable: if I listen to 1000 AI artists with one track produced and Linkin Park then my average will be Linkin Park
Cannot call lastfm algorithm advanced in any sense. Just opened Amon Tobin page: "similar artists: Kid Koala and DJ Kush", which is an impressively shallow understanding of the last 20 (!!) years of his life, and this happened with almost every artist on the platform, because the average sum of tastes of every listener does not exist in reality. E.g. in the case of Amon Tobin, Kid Koala is the average of similarities between early albums and recent releases, which is just not true, his music cannot be averaged throughout his career. I love my Web 2.0 youth, but the average similarity algorithm doesnt deserve praise. Its not better, its nostalgia and lack of faang-style unlimited greed which confused with better quality
Edit: of course spotify-style recommendations are much much worse, I just mean that lastfm doesnt have good algorithm either because artists are not consistent in releases. What is an average between electronic cult classic "The last resort" and every other Trentemoller album in strict indie rock style? This average does not exist
The main issue is an ability to rebuild literally any part of the system from sources. A few changes here and there allow cheaters to bypass anticheat protection in a significant amount of ways
I’m author of relatively popular open source project (4.8k stars, 100k+ downloads/months), lived on donations for five years. I use and am eternally grateful for the following oss plans:
- Unlimited browserstack. This would cost thousands of dollars
- Free netlify hosting. Server side analytics is still $9/m, but anyway
These plans have one thing in common: they are not limited in time. Open source cannot be built on an unstable foundation.
The six-month anthropic offer is just ridiculous. Bland PR move, I can’t express how miserable this plan is. It just not for us
ISS and MIR combined are not a "large market". How many radiators they require? Probably a single space dc will demand a whole orders of magnitude more cooling
In rust you could use multiple allocators at the same time. Allocation failure handled by allocator, converting panic to some useful behavior. This logic is observable in WASM, as there are OOMs all the time, which handled transparently to application code
So I assume there is no real blockers as people in this tread assume, this is just not a conventional behavior, ad hoc, so we need to wait and well defined stable OOM handlers will appear
Why not? It’s a common equipment and it’s not count as "digital device forbidden in analog studio" as you connect synth directly to it, just to make sure that your front waves are in sync
It’s important for electronic music to have consistent and predictable pitch, otherwise djs on stage will have hard time to play (they loop a start of the song and play it together with tail loop of previous song), so Daft Punk need to intentionally choose fractional BPM as mastering engineers will not change pitch even slightly
Instead of offloading batch computations to a proprietary cloud, it’s better to actually optimize the incredibly slow and unstable computational kernel.
In any case that’s not the happy path, Mathematica gets stuck in symbolic computations for ages. My FFT-based research in Mathematica slowed to a crawl, tens of minutes of waiting, even with 90% of the code compiled to binary. MATLAB finishes this task in milliseconds.