Cognitive AI, also known as cognitive artificial intelligence, refers to a type of artificial intelligence that is capable of performing tasks that require human-like cognitive abilities. Traditional AI models often focus on narrow, specific tasks, whereas cognitive AI aims to mimic human cognition to perform a wider range of complex tasks.

Cognitive AI applications are used in a broad range of functions, including: virtual assistants, customer service automation, healthcare diagnostics, fraud detection, autonomous vehicles, recommendation systems, and more. They utilize natural language processing, machine learning, computer vision, and knowledge representation to process and interpret vast amounts of data, extract meaningful insights, and provide intelligent responses.

Cognitive AI systems can handle unstructured data, including text, images, and speech, allowing them to perform tasks such as natural language understanding, sentiment analysis, image recognition, and speech recognition. They can also perform complex tasks such as problem-solving, decision-making, or more creative tasks like generating art, music, or writing.

Snowflake and AI

Snowflake is bringing the power of generative AI and LLMs to data. With generative AI, teams can discover precisely the right data point, data asset, or data insight, making it possible to maximize the value of their data.

That’s why Snowflake has recently acquired three companies that are helping bring advanced AI and deep learning to the Data Cloud:

• Neeva, a search company founded to make search even more intelligent at scale. Neeva created a unique and transformative search experience that leverages generative AI and other innovations to allow users to query and discover data in new ways.
• Streamlit, which developers use as their go-to platform to experiment and build LLM-powered, generative AI apps.
• Applica, which uses deep learning to sort information, regardless of data type.

Learn more: Using Snowflake and Generative AI to Rapidly Build Features