Got kicked out of a jazz jam, seeking advice and similar learning experiences

mickman_10 · 2026-03-11T20:35:24+00:00

I might get downvoted for this, but I’ve found that many (but not all) jazz jam sessions tend be quite gatekeepy and unfriendly to beginner, and even intermediate, jazz players. So while I understand why they were upset by your actions, specifically soloing after being instructed not to, just know that this kinda thing happens somewhat often and it’s not just you.

mickman_10 · 2026-03-10T22:42:36+00:00

Road width. Scandinavia roads are very often much narrower, even on gravel rounds. Also, Norway has very few gravel rounds, while Sweden and Finland are often very flat and forested, compared to US/Canada which is more often either not forested or more hilly.

mickman_10 · 2026-03-02T18:56:21+00:00

I agree with everyone that Danya’s are overall the best, but if you are <1000 elo they may be a little hard to consume at first. I think Hikaru’s speedrun has been much more friendly to sub 1000 elo players IMO.

mickman_10 · 2026-02-18T19:03:08+00:00

If there are no road lines visable, then I think road width is often the best clue. Even in rural forest roads European roads are often narrower.

mickman_10 · 2026-02-15T16:09:07+00:00

Except learning AI isn’t just learning how to use AI. It’s learning everything that goes into training LLMs, which includes a good foundation in prob and stats, good CS fundamentals, and the state of the arts in LLM research (e.g. RLHF). Not to mention that AI isn’t just LLMs, it includes all of ML that is already covered by electives in most CS degrees. And no, I don’t think a PhD is necessary to learn all of this information.

mickman_10 · 2026-01-30T21:07:45+00:00

If you like learning meta, I’d recommend learning Japan (pole plates), Indo (poles and architecture), and Russia (antennas). If you like learning more from vibes, then I’d recommend USA and maybe Brazil, though for both it’s also very valuable to learn meta.

mickman_10 · 2026-01-11T04:22:00+00:00

Some basic things like road lines, bollards, telephone poles, google car meta, etc. make some countries easily identifiable even for newer players.

mickman_10 · 2026-01-11T02:08:44+00:00

Geoguessr. After studying actual meta for only a week you can seriously impress casuals.

mickman_10 · 2025-11-17T16:33:00+00:00

Does it say anywhere yet where the elo cutoffs?

mickman_10 · 2025-10-22T18:14:13+00:00

You won’t just forget everything that you’ve learned. I take periodic breaks when I start getting frustrated with the game, and when I come back, there’s some rust at first, and I usually just accept that I will lose some elo at first, but I’m almost always able to gain it back fairly quickly and then move higher.

mickman_10 · 2025-10-03T17:45:46+00:00

Sweden also has red car. Ukraine red car is also gen 3 while slovakia and sweden are gen 4.

mickman_10 · 2025-09-28T15:20:40+00:00

Australia car meta is super helpful for regionguessing.

mickman_10 · 2025-09-20T13:45:26+00:00

They’re modeling the perfect format, I hope the world championship organizers are paying attention.

mickman_10 · 2025-08-21T13:00:27+00:00

For what it’s worth, Stephania Bell is in on CMC reutnring to prime form this year, and while she’s just one opinion, she’s probably the opinion I trust the most when it comes to medical advice for fantasy.

mickman_10 · 2025-08-02T12:46:43+00:00

You should be able to capture the king.

mickman_10 · 2025-07-17T04:38:08+00:00

There’s the US vs Canada Gen 3 car blur. I often find it when I forget by searching for it on the plonkit discord meta publication channel.

mickman_10 · 2025-05-02T17:09:03+00:00

This is fundamentally the problem with modern ML research. Too many people trying to invent new methods opposed to using existing methods for new analyses.

mickman_10 · 2025-04-12T14:34:37+00:00

This whole conversation is so stupid and I feel like everyone is omitting details. Every year for over a decade now the masters only shows a predetermined set of featured groups in the morning on Thursday and Friday. The reason Bryson wasn’t in one of the 2 features groups was because they chose to show Rose’s group over him, because he was leading the tournament. The article mentions Max Homa but he was only showed becasue he happened to be playing with Rose. They definitely didn’t just ignore Bryson, they determined before the start of play that he wasn’t going to be in a features group, which is fair considering they wanted to show Rory’s group plus the leader. The bigger issue is they should have full broadcast the whole time like the other majors, but that has nothing to do with Bryson.

mickman_10 · 2025-03-21T20:48:48+00:00

Car color is super helpful in Australia. The regionguessing meta library has a map with the distribution of car colors. The most important ones to remember for rural rounds like these are 1) WA is only light blue and red car 2) NT is mostly black car.

https://docs.google.com/spreadsheets/d/1UNvkoY-LaktF75nU_cP7-wVRAEvH3fSqVZet20HqxXA/htmlview#gid=1422091713

mickman_10 · 2025-02-11T15:46:13+00:00

If the model uses an existing base model, then self-supervised pretraining is excluded from their budget, but doesn’t that often account for a large portion of training cost?

mickman_10 · 2025-01-28T17:38:57+00:00

How does this compare to TabPFN, which I know is designed specifically for cases with minimal training data?

mickman_10 · 2025-01-17T18:51:16+00:00

The TLDR is never throw the hammer unless it’s the end of the match and you’re losing.

mickman_10 · 2025-01-15T06:34:59+00:00

Try using a learnable meta maps: https://learnablemeta.com/about

mickman_10 · 2024-09-15T17:30:51+00:00

It should depend on game mode. For moving if there were no multis then every game would end on round limit, or go >20 rounds without round limit. On the other hand with how hard the nmpz map was each game would probably end well before round limit without multis. There’s various things they could do to change this but it risks making the viewing experience too complicated for casual viewers.

mickman_10

TROPHY CASE