News (Page 5) | Liquid AI

Articles

  1. MIT Startup Takes On Big AI Names Using Radically New Tech (10.02.2024)
  2. Liquid AI Announces Generative AI Liquid Foundation Models With Smaller Memory Footprint (10.01.2024)
  3. Liquid AI launches non-transformer genAI models: Can it ease the power crunch? (10.01.2024)
  4. Liquid AI's LFMs challenge ChatGPT with innovative architecture and specs (10.01.2024)
  5. MIT startup Liquid AI releases its first series of generative AI models (10.01.2024)
  6. Liquid AI, an MIT spinoff, this week announced its first series of generative AI models: Liquid Foundation Models, or LFMs for short. (10.01.2024)
  7. Liquid AI debuted its non-transformer models, which it says perform on par with other leading generative AI models while requiring less memory (10.01.2024)
  8. Liquid Foundation Models: Our First Series of Generative AI Models (09.30.2024)
  9. In AI arms race, Boston’s LiquidAI claims to have a cheaper, more efficient app (09.30.2024)
  10. Liquid AI Announces First Generation of Language Liquid Foundation Models (09.30.2024)
  11. Liquid AI debuts new LFM-based models that seem to outperform most traditional large language models (09.30.2024)
  12. Liquid AI Introduces New Class of Foundational Models, Advancing AI Performance and Efficiency (09.30.2024)
  13. Liquid AI Launches Liquid Foundation Models: A Game-Changer in Generative AI (09.30.2024)
  14. MIT spinoff Liquid AI debuts its non-transformer AI models LFM-1B, LFM-3B, and LFM-40B MoE (09.30.2024)
  15. MIT spinoff Liquid debuts non-transformer AI models and they’re already state-of-the-art (09.30.2024)
  16. From Liquid Neural Networks to Liquid Foundation Models (09.29.2024)
  17. Towards a theory of learning dynamics in deep state space models (07.26.2024)
  18. Liquid at ICML 2024 (07.09.2024)
  19. The Empirical Impact of Neural Parameter Symmetries, or Lack Thereof (06.16.2024)
  20. Large Scale Dataset Distillation with Domain Shift (05.01.2024)
  21. LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery (05.01.2024)
  22. Mechanistic Design and Scaling of Hybrid Architectures (05.01.2024)
  23. Position: Future Directions in the Theory of Graph Machine Learning (05.01.2024)
  24. RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation (05.01.2024)
  25. State-Free Inference of State-Space Models: The Transfer Function Approach (05.01.2024)
  26. Liquid at ICLR 2024 (04.22.2024)
  27. Growing Q-Networks: Solving Continuous Control Tasks with Adaptive Control Resolution (04.05.2024)
  28. Launch of Collaboration with Liquid AI to Develop Edge AI Solution (02.27.2024)
  29. COCO-Periph: Bridging the Gap Between Human and Machine Perception in the Periphery (01.16.2024)
  30. Graph Metanetworks for Processing Diverse Neural Architectures (01.16.2024)