Avinash C. Pillai

  Generative AI Overview and Use Cases, after going through this, you will be able to: Define Generative AI and describe its significance and explain different use cases of Generative AI.  Artificial Intelligence (AI) is defined as Augmented Intelligence that enables experts to scale their capabilities while machines handle time-consuming tasks like recognizing speech, playing games, and making decisions. On the other hand,  Generative Artificial Intelligence, or GenAI, is an AI technique capable of creating new and unique data, ranging from images and music to text and entire virtual worlds. Unlike conventional AI models that rely on pre-defined rules and patterns, Generative AI models use deep learning techniques and rely on vast datasets to generate entirely new data with various applications.  A Generative AI model can also use LLM, Large Language Model, a type of artificial intelligence based on deep learning techniques designed to process and generate natural language. For inst

    What is AI     We define AI as anything that makes machines act more intelligently, we like to think of AI as augmented intelligence. We believe that AI should not attempt to replace human experts, but rather extend human capabilities and accomplish tasks that neither humans nor machines could do on their own.    The internet has given us access to more information, faster. Distributed computing and IoT have led to massive amounts of data, and social networking has encouraged most of that data to be unstructured. With Augmented Intelligence, we are putting information that subject matter experts need at their fingertips and backing it with evidence so they can make informed decisions. We want experts to scale their capabilities and let the machines do the time-consuming work.    How do we define intelligence?    Human beings have innate intelligence, defined as the intelligence that governs every activity in our body. This intelligence is what causes an oak tree to grow out of a li