Ryan Little

[Tim Butterly @timbutterly]

It has been brought to my attention that in my state of grief I never even tweeted the link to the special. Here it is for posterity. RIP Andy.

30 Minutes with Tim Butterly | Presented by GaS Digital | Full Special
https://t.co/bQGOEH54uT

[Ryan Little @TacticSiege]

@Kotaku pot, kettle.

[Sam Altman @sama]

people love MCP and we are excited to add support across our products.

available today in the agents SDK and support for chatgpt desktop app + responses api coming soon!

[Ryan Little @TacticSiege]

@BoneJail https://t.co/WplJbNIXyv

[Ryan Little @TacticSiege]

@lunivore I had no problem with your post, chat isn’t stateless and I was trying to help improve the example.

[Jim Fan @DrJimFan]

This is an ape ("Kanzi") playing Minecraft! A fascinating experiment on non-human biological neural networks 🙉

I've been teaching AI to play Minecraft for too long. There're so many similar techniques that the ape trainers used:

- In-context reinforcement learning: Kanzi gets a fruit or peanut whenever he hits a marked milestone in the game, incentivizing him to follow the in-game guides.
- RLHF: Kanzi doesn't understand much language, but he can see the trainers cheering him on, and he occasionally cheers them back! That gives him a strong signal that he's on the right track.
- Imitation learning: the trainers show Kanzi just 1 demonstration of how to do a task, and he immediately grasps the concepts. It's much more efficient than using rewards alone.
- Curriculum learning: they start with very simple environments to gradually teach Kanzi the controls. At the end, Kanzi is able to navigate complex caves, mazes, and the Nether.

It also amazes me how strong the ape's vision system is. Kanzi never saw Minecraft in his life, and for sure his ancestors didn't either. Yet he rapidly adapts to Minecraft's texture and physics, which are dramatically different from the natural world.

This level of generalization is far beyond what our most powerful vision models can do today. We are right in the thick of Moravec's paradox again: our best AIs are approaching human level on understanding language, but far behind animals on parsing pixels.

From YouTube channel "ChrisDaCow": https://t.co/AREU1q1QVm
Researchers are from the Ape Initiative, a non-profit org.

[Ammaar Reshi @ammaar]

The folks @CorridorDigital combine Stable Diffusion, Dreambooth, and Davinci Resolve for their AI powered anime and the results are incredible!

[reversecowgirl69 @botticellibimbo]

calling out ticketmaster’s monopoly bc tickets are 8k like wait til u hear about insulin

[Christopher Figueroa ☕️ @kinifi]

Dice that generate a dungeon

[Faustman Lab @FaustmanLab]

This vaccine is a century old—but it might be a secret weapon against diabetes https://t.co/RL5J1meQWG

[Ryan Little @TacticSiege]

*excited noises*
https://t.co/n6xe6s28Te

[Steve Noah @Steve_OS]

No idea what this game is called, but whoever made it, is the devil. https://t.co/Ec98aGXSDD

[Ryan Little @TacticSiege]

These Jaw-Dropping Computer Graphics, Modeling & Design Advances Will be on Display at SIGGRAPH 2017 https://t.co/AhQzNuWAT9

[David Li @daviddotli]

Fluid Paint - https://t.co/71qGexuSzp #webgl

[Ryan Little @TacticSiege]

Who will clean the cleaners?

[Jeremy Kahn is @[email protected] @trochee]

"it was just a side effect of the algorithm" is going to be the 21st century version of "I was just following orders".

[Ryan Little @TacticSiege]

“Tensorflow: How to freeze a model and serve it with a python API” by @morgangiraud https://t.co/OqjajTjYcB

[Ryan Little @TacticSiege]

“GitHub for Chimpanzees (and a short rant against scientists)” by @mngrwl https://t.co/Zfp7FfeWAg