Natural language processing (NLP): Becoming increasingly sophisticated, NLP technology has been demonstrating continuous improvements in language translation, text-to-speech, and speech-to-text applications.
Computer vision: The ability of AI systems to process and understand visual information is improving at a rapid pace in areas such as autonomous vehicles, security, and medical imaging
Robotics: AI-powered robots are becoming more advanced and autonomous, and are expected to play a larger role in areas such as manufacturing, agriculture, and healthcare in the future.
Generative models: Generative models can be used to create new, synthetic data that is similar to real-world data in areas such as art, design, and content creation
Reinforcement learning: A type of machine learning that allows AI systems to learn from experience and improve their decision-making over time. This technology has applications in areas such as gaming, autonomous systems, financial trading, etc.