Tyler

Investing in gaming @TIRTAVentures

I play too much cs2 and wow classic

50 dkp minus

[Tyler @tsmatses]

@NotAmberBerries It’s totally bizarre

[Tyler @tsmatses]

@ZacharyDiaz lol

[Tyler @tsmatses]

@QuestTheLine Different for me last night

[Tyler @tsmatses]

only in wow #orcbis

[Tyler @tsmatses]

Happy wow day

[Tyler @tsmatses]

@sonii You had your time

[Tyler @tsmatses]

@ramiabih Affliction leveling is really special and satisfying

[Tyler @tsmatses]

@EsfandTV Wow eternal would’ve been great

[Tyler @tsmatses]

Guild leader making us do bt/mh still when the games ded in a month #wow

[Tyler @tsmatses]

@FwoiblesWoW Yall nailed it, great job

[Tyler @tsmatses]

@CooliSushi This looks awesome

[Tyler @tsmatses]

@HHaandr Raiding in a top guild competitively is even more fun when things go wrong and the raid lead makes you stay up until 2am to push kill times 😅

[Tyler @tsmatses]

@Nicolascole77 ✋

[Tyler @tsmatses]

@olson_dan Seems like many qol improvements for those who don’t have much time

[Tyler @tsmatses]

@hthieblot No need to quit, can raid log for life 🫠

[Tyler @tsmatses]

@ZacharyDiaz Such a great day

[Andrew Carr 🤸 @andrew_n_carr]

Presenting compute-optimal scaling laws for human motion generation!!!

Human motion generation has historically been niche and difficult to scale. Animators, roboticists, motion analysts, and game developers all see the potential, but it rarely lives up to the rigor required in production.

We have long believed this is because all prior systems have been fantastically data constrained. Until today, we haven't been able to prove that scaling would actually help.

Today we present our flagship research paper: Compute-Optimal Scaling Laws for Human Motion Generation. (link: https://t.co/QvxrWtZoma)

We are building the world's largest, high-quality human-motion dataset. We trained hundreds of models across varying scales. They match the Chinchilla scaling found in language.

This places motion as the fifth data modality we understand how to scale. Text, images, audio, and video all have scaling laws. None of them really reflect the physical world. 3D human motion, across time, does.

Both autoregressive and flow matching motion models scale predictably. We can now predict, before training a model, how good it will be.

Motion is no longer data constrained. It is now a predictable and scalable frontier for physical and digital intelligence. Our largest models are training now, and the gap between generated motion and the real physical world is closing fast.

paper: https://t.co/QvxrWtZoma
blog: https://t.co/6f991xgWid

[Tyler @tsmatses]

So basically dreamsythe

[Chubby♨️ @kimmonismus]

Someone on Reddit built a WoW private server with 1,800 bots and AI chat via the DeepSeek API.

Dead Internet Theory, but playable.

An MMORPG with no real players, yet somehow it still feels human.

[Tyler @tsmatses]

@hthieblot mIRC - gamesurge!

[FOAD @FoadZone]

🚨 MANDO EVENT WEEKEND in Droid Tycoon 🚨

Saturday
🇺🇸 ET: 10AM–4PM | PT: 7AM–1PM
🇧🇷 BRT: 11AM–5PM
🇬🇧 GMT: 3PM–9PM | 🇪🇺 CET: 4PM–10PM
🇯🇵 JST: 11PM–5AM

Sunday 🇯🇵 PRIMETIME
🇯🇵 JST: 3PM–9PM
🇬🇧 GMT: 7AM–1PM | 🇪🇺 CET: 8AM–2PM
🇧🇷 BRT: 3AM–9AM
🇺🇸 ET: 2AM–8AM | PT: 11PM–5AM (Sat)

Sunday
🇺🇸 ET: 4PM–10PM | PT: 1PM–7PM
🇧🇷 BRT: 5PM–11PM
🇬🇧 GMT: 9PM–3AM | 🇪🇺 CET: 10PM–4AM
🇯🇵 JST: 5AM–11AM