Byte Latent Transformer: Scaling LLMs Beyond Tokens скачать в хорошем качестве

Byte Latent Transformer: Scaling LLMs Beyond Tokens

In this episode of the AI Research Roundup, host Alex dives into a novel architecture challenging traditional large language models: Byte Latent Transformer: Patches Scale Better Than Tokens This paper introduces the Byte Latent Transformer (BLT), a byte-level model using dynamic patching instead of fixed tokenization. BLT aims for comparable performance to token-based models but with enhanced efficiency and robustness. https://paperswithcode.com/paper/byte... This work explores a fundamental shift away from tokenization, potentially overcoming issues like noise sensitivity and multilingual inequity. The BLT's approach of processing raw bytes could pave the way for more adaptable and efficient language models. #AI #MachineLearning #DeepLearning #LLM #Transformer #NLP #Research #Podcast #ByteLevel