Neuro-Symbolic AI: Combining symbolic reasoning with deep learning for more interpretable and reliable AI models.
Neuro-Symbolic AI: Combining symbolic reasoning with deep learning for more interpretable and reliable AI models.
RAG - Retrieval Augmented Generation: Where language models enhance their responses by accessing and incorporating information from external data sources, such as the web, for more accurate and up-to-date outputs. (Thanks Jeremiah Owyang)
RAG - Retrieval Augmented Generation: Where language models enhance their responses by accessing and incorporating information from external data sources, such as the web, for more accurate and up-to-date outputs. (Thanks Jeremiah Owyang)
Reinforcement Learning: Training AI systems through trial and error, using rewards to guide them towards desired outcomes. Applied in robotics, game playing, and dynamic decision-making.
Reinforcement Learning: Training AI systems through trial and error, using rewards to guide them towards desired outcomes. Applied in robotics, game playing, and dynamic decision-making.
Responsible AI: Designing, developing, deploying, and using AI in a way that is ethical, transparent, accountable, and aligned with human values.
Responsible AI: Designing, developing, deploying, and using AI in a way that is ethical, transparent, accountable, and aligned with human values.
Robustness & Adversarial AI: Strengthening AI systems against attacks designed to produce incorrect outputs.
Robustness & Adversarial AI: Strengthening AI systems against attacks designed to produce incorrect outputs.