บ้าน Generative AI What is generative AI? Artificial intelligence that creates

What is generative AI? Artificial intelligence that creates

Top Generative AI Tools To Check Out In 2023

AI generative models have the potential to disrupt industries like entertainment, design, advertising, and more. They can enhance creative processes, automate content creation, and enable personalized user experiences. We have already seen that these generative AI systems lead rapidly to a number of legal and ethical issues. “Deepfakes,” or images and videos that are created by AI and purport to be realistic but are not, have already arisen in media, entertainment, and politics.

what is generative ai?

Artists might start with a basic design concept and then explore variations. Architects could explore different building layouts and visualize them as a starting point for further refinement. A generative AI model starts by efficiently encoding a representation of what you want to generate. For example, a generative AI model for text might begin by finding a way to represent the words as vectors that characterize the similarity between words often used in the same sentence or that mean similar things.


This has given organizations the ability to more easily and quickly leverage a large amount of unlabeled data to create foundation models. As the name suggests, foundation models can be used as a base for AI systems that can perform multiple tasks. In addition to natural language text, large language models can be trained on programming language text, allowing them to generate source code for new computer programs.[29] Examples include OpenAI Codex.

what is generative ai?

Researchers at Stanford, for example, trained a relatively small model, PubMedGPT 2.75B, on biomedical abstracts and found that it could answer medical questions significantly better than a generalist model the same size. Their work suggests that smaller, domain-specialized models may be the right choice when domain-specific performance is important. Language transformers today are used for non-generative tasks like classification and entity extraction as well as generative tasks like translation, summarization, and question answering. More recently, transformers have stunned the world with their capacity to generate convincing dialogue, essays, and other content. As an evolving space, generative models are still considered to be in their early stages, giving them space for growth in the following areas. A transformer is made up of multiple transformer blocks, also known as layers.

Pardot Implementation Guide: Setting Up in 12 Easy Steps

In design, generative AI can help create countless prototypes in minutes, reducing the time required for the ideation process. In the entertainment industry, it can help produce new music, write scripts, or even create deepfakes. Generative AI has the potential to revolutionize any field where creation and innovation are key.

Yakov Livshits
Founder of the DevEducation project
A prolific businessman and investor, and the founder of several large companies in Israel, the USA and the UAE, Yakov’s corporation comprises over 2,000 employees all over the world. He graduated from the University of Oxford in the UK and Technion in Israel, before moving on to study complex systems science at NECSI in the USA. Yakov has a Masters in Software Development.

They work by distilling the user’s data and target task into a small number of parameters that are inserted into a frozen large model. Generative AI and large language models have been progressing at a dizzying pace, with new models, architectures, and innovations appearing almost daily. Autoencoders work by encoding unlabeled data into a compressed representation, and then decoding the data back into Yakov Livshits its original form. “Plain” autoencoders were used for a variety of purposes, including reconstructing corrupted or blurry images. Variational autoencoders added the critical ability to not just reconstruct data, but to output variations on the original data. Artificial intelligence has gone through many cycles of hype, but even to skeptics, the release of ChatGPT seems to mark a turning point.


An LLM, like ChatGPT, is a type of generative AI system that can produce natural language texts based on a given input, such as a prompt, a keyword, or a query. LLMs can also learn from their own outputs and are likely to improve over time. Generative AI technology uses machine learning to produce content like text, images, or music. It generates new outputs by learning patterns from existing data and creating novel, creative content based on those patterns. Generative AI is a type of artificial intelligence that generates various types of content, including text, imagery, audio, videos and data. Its models use neural networks to recognize patterns and structures in the existing data to generate new and original data.

  • By harnessing the power of our generative AI tools and technology, you can track customer journeys and interactions, ensuring they receive personalized attention that keeps them coming back for more.
  • From there, a generative adversarial network (GAN) algorithm constantly competes with itself within the gen AI model.
  • I think there’s huge potential for the creative field — think of it as removing some of the repetitive drudgery of mundane tasks like generating drafts, and not encroaching on their innate creativity.
  • However, it also can introduce new risks, be they legal, financial or reputational.
  • Of course, AI can be used in any industry to automate routine tasks such as minute taking, documentation, coding, or editing, or to improve existing workflows alongside or within preexisting software.

Murf.ai is an online tool that uses AI to generate high-quality voice-overs for videos, presentations, and text-to-speech needs. This tool allows users to modify a script or transform a casual voice recording into a professional-sounding studio-quality voice-over. The most commonly used tool from OpenAI to date is ChatGPT, which offers common users free access to basic AI content development. It has also announced its experimental premium subscription, ChatGPT Plus, for users who need additional processing power, and early access to new features. Traditional AI simply analyzes data to reveal patterns and glean insights that human users can apply.

Scaling laws allow AI researchers to make reasoned guesses about how large models will perform before investing in the massive computing resources it takes to train them. Another limitation of zero- and few-shot prompting for enterprises is the difficulty of incorporating proprietary data, often a key asset. If the generative model is large, fine-tuning it on enterprise data can become prohibitively expensive. They allow you to adapt the model without having to adjust its billions to trillions of parameters.

what is generative ai?


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