DFL Erwin

This is so wrong. Gaming, even in its original metaverse form, was shitcoin trading. ( so many game studio from 2022 were token launchpad) Now, that spirits still remain but the form factors have evolved: entertainment finance, arcade finance, tap trading, and a variety of light gambling use cases Future is serious dex as infra, and gamified experiences on top Incredible momentum ahead

JUST IN: Meta announces they'll be shutting down the Metaverse, after pouring $80,000,000,000.00 into the project.

all these useful AI tools, all these insane cracked ivy league graduates building applications funded by paradigm where the fuck is my medicine

I used Cursor to vibe code a simple fishing game prototype on the Unity Engine. Here's my learnings: - I did not use any Unity MCP for this. The game was built entirely by Cursor models (Sonnet 4.6 for execution and Opus 4.6 for planning) - The model was able to set up the game, getting the basic game mechanics working fairly quickly - I had to use the Unity Game Editor UI to attach components to the in-game objects manually, but it was quite easy to follow the instructions given by the Cursor model - Unity Editor is huge and slow! Compared to Godot, I find the UI really clunky I feel tired looking at it - Unity Assets Marketplace is amazing, there are so many amazing art assets there (like the ones I am using for this game). This is probably the biggest strength of Unity. - I had some issues with restoring checkpoints, probably because of how Unity Game Editor UI being really clunky and I had to manually adjust things in the Editor, which the model doesnt have knowledge of Overall, the results turn out pretty decent, but it was a rather frustrating experience, especially when I had to debug issues or rollback changes. I'll explore more vibe coding on Unity but for now, I think I prefer Godot as a game engine. I just wish there is a Godot Asset Marketplace!

For decades, we’ve trained AI to chase rewards. But humans don’t just optimize outcomes. We experience, reflect, then learn. Can AI do the same? Introducing 𝐄𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐭𝐢𝐚𝐥 𝐑𝐞𝐢𝐧𝐟𝐨𝐫𝐜𝐞𝐦𝐞𝐧𝐭 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, a step toward AI that truly learn from experience.

Hot take from investing in robotics companies: simulation is overrated. Billions poured into sim-to-real. The gap hasn't meaningfully closed in 2-3 years. Locomotion tolerates 10% failure rates — manipulation doesn't. The industry is quietly converging on: bulk imitation data → fine-tuning with RL → less simulation, not more.

Hot take from investing in robotics companies: simulation is overrated. Billions poured into sim-to-real. The gap hasn't meaningfully closed in 2-3 years. Locomotion tolerates 10% failure rates — manipulation doesn't. The industry is quietly converging on: bulk imitation data → fine-tuning with RL → less simulation, not more.