Artificial Intelligence focuses on creating intelligent machines that can perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and natural language processing. It involves the development of algorithms and systems that can reason, learn, and make decisions based on input data.

Machine Learning (ML) is a subfield of AI that involves teaching machines to learn from data without being explicitly programmed. ML algorithms can identify patterns and trends in data and use them to make predictions and decisions.

Enterprise AI are solutions that apply artificial intelligence and machine learning to solve problems faced by large-scale companies and organizations.

Common applications include but are not limited to Process Automation, Compliance and Risk Management, ESG, Supply Chain, Product Development, Healthcare, and Customer Service.

Major Categories in AI and ML

• Computer Vision: Creating new ways for computers to gain a higher level of understanding of the visual world around us.
• Core Machine Learning: Building algorithms inspired by, and compatible with human cognition.
• Embodied AI/Robotics: Developing embodied agents that assist and collaborate with people in virtual and physical spaces.
• Generative AI: Creating AI systems that empower anyone to bring their imagination to life.
• Natural Language Processing: Advancing the state-of-the-art in natural language understanding and generation.
• Society & Responsible AI: Delivering AI research innovations and guidelines designed to help everyone benefit from AI.
• Speech & Audio: Creating spoken language technology to help people build community and connect with others.