Tokens are the fundamental units that LLMs process. Instead of working with raw text (characters or whole words), LLMs convert input text into a sequence of numeric IDs called tokens using a ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

Meta open-sourced Byte Latent Transformer (BLT), an LLM architecture that uses a learned dynamic scheme for processing patches of bytes instead of a tokenizer. This allows BLT models to match the ...

Test-time scaling (TTS) has emerged as a proven method to improve the performance of large language models in real-world applications by giving them extra compute cycles at inference time. However, ...