Generative AI Examples (2024)

FAQs

What is generative AI and examples? ›

Generative AI or generative artificial intelligence refers to the use of AI to create new content, like text, images, music, audio, and videos. Generative AI is powered by foundation models (large AI models) that can multi-task and perform out-of-the-box tasks, including summarization, Q&A, classification, and more.

Some of the applications of generative AI in the financial services industry include artificial intelligence investment strategies, drafting documentation and monitoring regulatory changes, and using generative AI as an interpreter to facilitate communications between clients and investors.

ChatGPT is a form of generative AI that helps with content creation and information retrieval.

Unlike Traditional AI, Generative AI does not rely on explicit rules but rather learns patterns and structures from vast amounts of data. One of the most significant advancements in Generative AI is the use of neural networks, specifically deep learning models.

Generative AI Writing Assistance at Your Fingertips

Grammarly is the AI communication assistant that's up to speed on your context and preferred writing style. Use Grammarly's generative AI to unblock your ideas and enable accelerated productivity for teams and individuals.

Lack of trust and authenticity

Gen AI can generate information that appears factual but is often inaccurate. This is often called AI hallucinations. We must remember that: although Gen AI models appear to understand the content that they use and generate, they do not understand it.

Which of the following is NOT a type of Generative AI? Explanation: Decision trees are a type of discriminative AI, which means that they are used to classify existing content. Neural networks, genetic algorithms, and rule-based systems are all types of Generative AI.

Use our Gen AI Navigator to assess your organization's fastest path to adopting and benefiting from generative AI. Learn how generative AI can transform customer service, enhance employee productivity, automate business processes, and more.

Amazon has made many AI-related enhancements to Alexa in recent months, including a new generative AI model to give the virtual assistant a more opinionated personality and the ability to adjust its tone and response to express human emotions like excitement or surprise.

What is the first generative AI? ›

Generative AI was introduced in the 1960s in chatbots. But it was not until 2014, with the introduction of generative adversarial networks, or GANs -- a type of machine learning algorithm -- that generative AI could create convincingly authentic images, videos and audio of real people.

Generative AI creates fresh content while predictive AI uses algorithms to spot forward-looking correlations.

Some of these types of AI aren't even scientifically possible right now. According to the current system of classification, there are four primary AI types: reactive, limited memory, theory of mind, and self-aware. Let's take a look at each type in a little more depth.

Some examples include using flashcards, past papers, and quick-fire quizzes. This approach is generative because actively recalling information from memory helps to strengthen connections between new information and learned material.

A generative model could generate new photos of animals that look like real animals, while a discriminative model could tell a dog from a cat. GANs are just one kind of generative model.

Conversational agents: Generative AI can be used to create chatbots and other conversational agents that can interact with users in natural language. For example, Google's Duplex AI can make phone calls to book appointments and reservations, and can even carry on a natural-sounding conversation with a human.