Meta FAIR Lab
Fundamental AI Research laboratory at meta, led by yann-lecun. The lab focuses on developing artificial-general-intelligence (AGI) through world-models and Self-Supervised Learning.
Core Research Paradigms
- JEPA (Joint-Embedding Predictive Architecture): Moving away from generative pixel/token prediction toward predicting in latent space.
- Self-Supervised Learning: Training models on raw data without manual labeling.
- Development of non-generative architectures for reasoning and predictive modeling.
Recent Developments
- vl-jepa (2026-04-14): A new vision-based approach to AGI that departs from the current llm-centric paradigm.
- Core Thesis: “Language is not Intelligence.”
- Represents a strategic shift away from generative-ai-driven approaches.
- Emphasizes vision-based predictive modeling as a foundation for true intelligence, rather than relying on text-only generative processes.
Backlinks
- 2026 04 14 New paper for a vision approach to AGI not LLM