@third eye dog πŸ‘οΈ (@thirdeyedog001) 's Twitter Profile
@third eye dog πŸ‘οΈ

@thirdeyedog001

Digital-humanist, techno-hermeticist. Synthesizing concepts to better understand linguistics and symbolisms. Micro-Model maker. Hacker and word-crafter.

ID: 1664044677203476480

linkhttps://github.com/ThirdEyeDog calendar_today31-05-2023 23:02:35

3,3K Tweet

132 Followers

619 Following

@third eye dog πŸ‘οΈ (@thirdeyedog001) 's Twitter Profile Photo

Large language models use computational power to predict the next token, I think this will eventually lead to a machine that can predict the future.

anton (@abacaj) 's Twitter Profile Photo

This is really impressive, CPU inference is becoming more viable and faster, this would drop costs significantly and even allow small devices to run fast inference

This is really impressive, CPU inference is becoming more viable and faster, this would drop costs significantly and even allow small devices to run fast inference
@third eye dog πŸ‘οΈ (@thirdeyedog001) 's Twitter Profile Photo

using mistral for about 2h and already feel how much better it is in speech alone, it talks like a real person and don't use any odd RLHF dick-fuckery

using mistral for about 2h and already feel how much better it is in speech alone, it talks like a real person and don't use any odd RLHF dick-fuckery
caio temer (@canalccore2) 's Twitter Profile Photo

Approach to Language Modeling Using Numeric Tokenization Concept Overview:This approach involves a unique method of tokenizing input text. Instead of traditional methods, I employ a numeric tokenization scheme with four distinct parts: Relative Position Encoding: The first part

@third eye dog πŸ‘οΈ (@thirdeyedog001) 's Twitter Profile Photo

Things to figure out: * How do humans synthesize information * How does language evolve and is created * How to pragmatically access information * Why is the math working in the first place

caio temer (@canalccore2) 's Twitter Profile Photo

nice to hear that your team has already explored this, I don't have much knowledge in physics, just my undergraduate engineering background. What I was thinking is that if we could create an optical network parallel to a conventionally trained neural networkβ€”essentially