⚡️ Test-Time Training RNN (TTT) is a fundamentally new method of machine learning.

TTT is a technique that allows artificial intelligence models to adapt and learn while in use, rather than just during pre-training.
The main advantage of TTT is that it can efficiently process long contexts (large amounts of input data) without significantly increasing the computational cost.

The researchers conducted experiments on various datasets, including books, and found that TTT often outperformed traditional methods.
In comparative benchmarks with other popular machine learning methods such as transformers and recurrent neural networks, TTT was found to perform better on some tasks.

This revolutionary method will bring us closer to creating more flexible and efficient artificial intelligence models that can better adapt to new data in real time.

Adaptations of the method have been published on Github:

- adaptation for Pytorch
- adaptation to JAX

🟡 Arxiv
🖥 GitHub for Pytorch [Stars: 277 | Issues: 3 | Forks: 12 ]
🖥 GitHub for Jax [ Stars: 129 | Issues: 1 | Forks: 6 ]


#Pytorch #Jax #TTT #LLM #Training

https://t.iss.one/DataScienceT ⚫️