Generative AI System

Context:
- It can have applications in numerous fields, such as creative writing, image synthesis, music composition, and drug discovery.
- It can be based on advanced algorithms and models, such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformer models.
- It can (often) surprise and generate outputs that human creators might not think of.
- …
Example(s):
- a Text-to-Text Generative AI System (that uses a text-to-text model), such as OpenAI ChatGPT.
- DeepArt: An AI system that generates unique pieces of art by combining one image's style with another's content.
- Jukin Media: A music-generating AI that creates original compositions based on input parameters like genre and mood.
- Insilico Medicine: A biotech company that uses generative AI for drug discovery.
- …
Counter-Example(s):
- Rule-Based System: These systems don't generate new outputs but work based on pre-defined rules.
- Supervised Learning System: While these systems learn from data, they don't generate new content but make predictions based on input.
- Search Engine: They retrieve and rank existing information instead of generating new content.
See: Artificial Intelligence, Machine Learning, Generative Adversarial Network, Transformer (model).

References

(Wikipedia, 2023) ⇒ https://en.wikipedia.org/wiki/generative_artificial_intelligence Retrieved:2023-6-6.
- Generative artificial intelligence or generative AI is a type of artificial intelligence (AI) system capable of generating text, images, or other media in response to prompts.^[1] ^[2] Generative AI models learn the patterns and structure of their input training data, and then generate new data that has similar characteristics.
  Notable generative AI systems include ChatGPT (and its variant Bing Chat), a chatbot built by OpenAI using their GPT-3 and GPT-4 foundational large language models,^[3] and Bard, a chatbot built by Google using their LaMDA foundation model. Other generative AI models include artificial intelligence art systems such as Stable Diffusion, Midjourney, and DALL-E.
  Generative AI has potential applications across a wide range of industries, including art, writing, software development, healthcare, finance, gaming, marketing, and fashion.^[4] ^[5] Investment in generative AI surged during the early 2020s, with large companies such as Microsoft, Google, and Baidu as well as numerous smaller firms developing generative AI models.^[1]^[6] However, there are also concerns about the potential misuse of generative AI, such as in creating fake news or deepfakes, which can be used to deceive or manipulate people.