Large Concept Models (LCMs) by Meta - The Era of AI After LLMs?
AI Summary
Summary of Large Concept Models Video
- Introduction to Large Language Models (LLMs) and Tokenization
- LLMs use Transformers and tokenizers.
- Tokenizers convert prompts into tokens.
- Example: GPT-4 tokenizes ‘will tokenization eventually be dead?’ into multiple tokens.
- Large Concept Models (LCMs)
- LCMs process concepts instead of tokens.
- Concepts represent higher-level ideas, not limited to words or language.
- LCMs handle long contexts better due to shorter concept sequences.
- Hierarchical reasoning is improved with LCMs.
- Meta’s Research Paper on LCMs
- Paper titled “Large Concept Models: Language Modeling in a Sentence Representation Space.”
- LCMs work with concepts derived from sentences.
- Concepts can be language-independent and multimodal.
- LCM Architecture
- Sentences are encoded into concept embeddings using a concept encoder called SONAR.
- SONAR supports 200 languages for text and 76 for speech.
- LCM operates in the embedding space, independent of language or modality.
- Output concepts are decoded back into language or other modalities using SONAR.
- Hierarchical Structure in LCMs
- Extract concepts, reason with them, and generate output.
- The structure allows for multiple outputs without rerunning the LCM.
- Relation to Previous Work
- LCMs are similar to Meta’s Joint Embedding Predictive Architecture (JEPA).
- Base-LCM Architecture
- Predicts the next concept in the embedding space.
- Uses a Transformer decoder, PreNet, and PostNet.
- Trained with mean squared error loss.
- Diffusion-Based LCMs
- Inspired by diffusion models in image generation.
- One-Tower and Two-Tower diffusion-based LCMs are explored.
- One-Tower LCM removes noise from the concept sequence iteratively.
- Two-Tower LCM separates context encoding from concept diffusion.
- Comparison of LCM Versions
- Diffusion-based LCMs outperform other versions in ROUGE-L and coherence metrics.
- Smallama slightly outperforms diffusion-based LCMs.
Detailed Instructions and URLs
- No specific CLI commands, website URLs, or detailed instructions were provided in the transcript.