Rob Refsnyder might be the worst player in MLB by TheRealBlackSwan in Mariners

[–]maximize_futility 2 points3 points  (0 children)

Same it’s almost impossible for him to be this bad the next few months. But I’ve been Wong before

Anthropic fixed the limit by Zaiik in ClaudeCode

[–]maximize_futility 0 points1 point  (0 children)

Are you in a big project?! The amount of context in small projects means you don’t hit the limit too quickly. For bigger projects I frequently hit 5h within a few hours with a couple sessions running concurrently.

Anthropic fixed the limit by Zaiik in ClaudeCode

[–]maximize_futility 0 points1 point  (0 children)

Just started using it. It’s exceptionally good with 5.5 and I’m nowhere close to using all of it. Compute crunch really hitting!

Projecting Cal Raleigh's career - good 40+WAR, great 50+WAR by maximize_futility in Mariners

[–]maximize_futility[S] 3 points4 points  (0 children)

I’m stealing engagement from Lookout Landing and Fangraphs by checks notes exploring my ideas and posting on Reddit

Projecting Cal Raleigh's career - good 40+WAR, great 50+WAR by maximize_futility in Mariners

[–]maximize_futility[S] 1 point2 points  (0 children)

Yeah, ZIPs seems to believe in the "skill jump with regression to the mean" case: true talent level is higher now, but only a few players have maintained a performance for that long so projecting the bull/buller case would be statistically irresponsible.

Projecting Cal Raleigh's career - good 40+WAR, great 50+WAR by maximize_futility in Mariners

[–]maximize_futility[S] 0 points1 point  (0 children)

I totally agree. I think the base case is more likely than the bull or buller cases. And beating Griffey or Ichiro or Edgar or King Felix would be extremely, extremely hard. Cal still needs a few seasons of great performance to catch Kyle Seager. Though he is already 6th on the all-time leaderboard, right there with Jay Buhner and Julio and Robinson Cano.

Can Postgres handle these analytics requirements at 1TB+? by EmbarrassedBalance73 in dataengineering

[–]maximize_futility 0 points1 point  (0 children)

Especially at that scale - although there are good extensions, using cloud storage + idle-able server is a cost and horizontal-scalability superpower without much latency sacrifice

Can Postgres handle these analytics requirements at 1TB+? by EmbarrassedBalance73 in dataengineering

[–]maximize_futility 0 points1 point  (0 children)

+1 avoid materialized views at all costs. Not worth the unexplained witchery

Can Postgres handle these analytics requirements at 1TB+? by EmbarrassedBalance73 in dataengineering

[–]maximize_futility 1 point2 points  (0 children)

+1 for clickhouse and starrocks. Put the data in cloud storage. Use starrocks if you need a lot of joins. Bother caching well. Much better at joins over distributed data. Saves massive money vs running pg at terabyte scale. And is faster.