GLOSSARY

Cognitive computing refers to a new generation of computing systems that aim to simulate human thought processes in a computerized model. These systems leverage AI technologies like machine learning, natural language processing, and computer vision to mimic the way the human brain works, enabling machines to interpret, learn from, and adapt to new information.

Cognitive computing systems typically have several essential components:

1. Machine Learning: Cognitive computing systems utilize machine learning algorithms to learn from data and improve their performance over time.
2. Natural Language Processing: These systems are capable of understanding and processing human language, allowing them to comprehend text and spoken input.
3. Computer Vision: Cognitive computing systems can analyze and interpret visual information, such as images and videos, for object recognition and scene understanding.
4. Knowledge Representation: These systems use knowledge graphs, ontologies, or other methods to represent and store information, allowing for efficient retrieval and reasoning.

Cognitive computing has a wide range of applications across various industries, including:

• Healthcare: Cognitive systems can help with diagnosing diseases, recommending treatment plans, and predicting patient outcomes.
• Finance: These systems can analyze large amounts of financial data for fraud detection, risk management, and investment recommendations.
• Retail: Cognitive computing can assist with inventory management, pricing optimization, and personalized marketing campaigns.
• Legal: Cognitive systems can aid in legal document review, e-discovery, and case research.
• Energy Management: Cognitive computing can optimize energy consumption and distribution, as seen with Veritone’s IDERMS green energy management solution.
  Veritone, an AI company, offers aiWARE, an AI operating system that provides access to hundreds of cognitive engines for various use cases, such as face recognition, sentiment analysis, and translation.