Taking life one day at a time.

California, USA
Joined November 2017
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Replying to @elonmusk
Do toys r us kids count? I think I'm still one of those...
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I keep buying cheap incremental games and seeing how fast I can get 100% steam achievements on them 馃嵒馃弳
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Replying to @Ekimko
Looks kinda awesome
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Lol, I love when devs post server messages like this in WoW Forever
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when you launch an extremely popular age assurance update that everyone on Discord was really looking forward to and it has bugs
Discord I am 26 years old and I am turning 27 in a week WHAT IS THE MEANING OF THIS
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Grummz
@GrummzSep 24
Someone pointed out that I, along with the original team, are listed first in the credits for WoW Forever. I dunno what to say, this is deeply moving and they didn't have to do that. The new team is cooking so hard on it and deserves the credit for bringing it back. Thank you guys for preserving the legacy.
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Grummz
@GrummzSep 18
Best welcome to WoW Forever... The fruit is GONE, and the woman is BACK. So glad they didn't go with the retail censorship here.
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Replying to @iamnabins
Terrain alteration costs. Road grading for safety.
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Guessing a dislike of being bound to an app whose backend may one day go poof with the company in case something happened. I personally don't mind, but even so prefer when companies provide software escrow to avoid that. Cheers!
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At Nof1 we believe the next breakthrough in AI after reasoning is adaptation If reasoning is the ability to detect patterns and leverage them, adaptation is anticipating how those patterns will change This is a crucial capability for real world AI, and current LLMs struggle with it. We've run thousands of live market experiments and no amount of context, prompting, or harness engineering has worked. So, we've been pushing our research deeper down the stack In this paper, we trained models that can better adapt in dynamic environments like markets. They learn to value an action by the futures it opens up, not just its immediate payoff It's an early step, but we're building towards forever learners that are default forward-looking, rather than static and backward looking
1/6 馃У How do you train a language model to become a self-adaptive, long-horizon optimization engine for executable trading policy search? In our new paper, "The Time Value of Evolution," we introduce Lineage-Value Policy Gradients, or LVPG, a new long-horizon RL technique for adaptive evolutionary search.
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Replying to @IndieGameJoe
Absolutely. I love tilt shift photography and playing a game that uses the style? Yesssssss
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Kinda having fun having agents work on a large project for a while with me mostly staying hands off, then going in myself and tearing things apart to bring the code quality up to snuff. So many wild decisions get made when you leave sol/fable to their own devices haha
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Replying to @Tezenari
Nice seeing a lot of the speed improvements offered
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Replying to @Tezenari
No joke. Almost every response I see is like that too for anything in IT, finance, or politics. Basically anything that has high CPM -.-
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.env.dev retweeted
Directive Utilities 2.1.0 is now available! - 32 new editor and runtime utilities - Array operations up to 612x faster in benchmarks - New array sampling, pagination, and async flow nodes - Asset audits, Blueprint inspection, and actor layout tools - Expanded packaged-runtime testing for UE 5.6 through 5.8 Open source, with prebuilt downloads for Mac, Windows, and Linux. Available on Github (Fab soon)
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we distilled 2.3M Claude Fable 5 reasoning traces into Qwen3-4B - 100% self-consistency @ 512 samples - 0.00 bits output entropy - zero hallucination variance turns out the student is not bounded by the teacher. it also converged on one universal truth. we open-sourced the model weights馃憞
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I made my Steam Controller automatically charge itself @Dexerto @HardwareSteam @valvesoftware
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