What is Generative AI (GenAI)
Generative artificial intelligence (AI) is a type of AI that generates images, text, videos, and other media in response to inputted prompts.
AI generators like ChatGPT and DALL-E are gaining worldwide popularity. These programs respond to prompts input by users. Submit a text prompt, and the generator will produce an output, whether it is a story or outline from ChatGPT or a monkey painted in a Victorian style by DALL-E.
In this article, we’ll outline what you should know about this growing field, how it works, uses cases, and more. Afterward, if you’re interested in building foundational generative AI skills, consider enrolling in DeepLearning.AI’s Generative AI for Everyone course.
What is generative AI vs AI?
Generative AI is a type of machine learning focused on building generative models that are capable of producing a wide range of AI-generated content, including human-like text, images, and audio. As a result, it’s a subset of AI in general, which is essentially defined as the pursuit of creating machines capable of exhibiting (or exceeding) human intelligence.
Generative models, also known as “large language models (LLMs),” are a type of deep learning neural network designed to mimic the human brain. They are produced by training complex algorithms on massive datasets. While traditional AI is typically designed to perform a narrow range of tasks repetitively, GenAI is capable of producing original content in response to a wide variety of user inputs, allowing it to respond dynamically to users’ needs in real-time.
Read more: AI vs. Generative AI: The Differences Explained
How does generative AI work?
Generative AI models use neural networks to identify patterns in existing data to generate new content. Trained on unsupervised and semi-supervised learning approaches, organizations can create foundation models from large, unlabeled data sets, essentially forming a base for AI systems to perform tasks [1].
Some examples of foundation models include LLMs, GANs, VAEs, and Multimodal, which power tools like ChatGPT, DALL-E, and more. ChatGPT draws data from GPT-3.5 or 4 and enables users to generate text based on a prompt. Another foundation model Stable Diffusion enables users to generate realistic images based on text input [2].
Popular AI generators
There are several generative AI platforms you can become familiar with. You may find them helpful for automating certain processes in your workflow:
- ChatGPT: This language model has a foundation of GPT architecture that generates text that resembles something a human would produce. It’s a helpful companion for research, strategy, and content creation.
- DALL-E3: This model generates images from text prompts, so creatives can create vibrant illustrations and concept art that’s a useful accompaniment to content marketing.
- Microsoft Copilot: This model, based on ChatGPT, is integrated into Microsoft’s popular productivity suite of applications and is also available as a stand-alone product offering.
- Google Gemini: Google’s answer to ChatGPT, Gemini is integrated into Google’s own suite of productivity applications but is also accessible as a stand-alone chatbot.
Generative AI use cases
Once you’ve decided which AI generator suits your needs, these use cases may help you get the creative juices flowing for ways generative AI can benefit you and your business.
- Writing or improving content by producing a draft text in a specific style or length
- Adding subtitles or dubbing educational content, films, and other content in different languages
- Outlining briefs, resumes, term papers, and more
- Receiving a generic code to edit or improve upon
- Summarizing articles, emails, and reports
- Improving demonstration or explanation videos
- Creating music in a specific tone or style
Generative AI has many use cases that can benefit the way we work, by speeding up the content creation process or reducing the effort put into crafting an initial outline for a survey or email. However, generative AI also has limitations that may cause concern if it remains unregulated.
Conclusion
This is a very basic description of Generative AI, for more information Read here.
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