AI Image Generation Prompt Examples and Tutorial

AI Image Generation Prompt Examples and Tutorial

Background: What is a Generative Model? Machine Learning

GT4SD is an open-source library to accelerate hypothesis generation in the scientific discovery process that eases the adoption of state-of-the-art generative models. Generative AI systems trained on sets of images with text captions include Imagen, DALL-E, Midjourney, Adobe Firefly, Stable Diffusion and others (see Artificial intelligence art, Generative art, and Synthetic media). They are commonly used for text-to-image generation and neural style transfer.[31] Datasets include LAION-5B and others (See Datasets in computer vision). Transformer-based models, such as OpenAI’s GPT (Generative Pre-trained Transformer) series, have revolutionized natural language processing. These models utilize attention mechanisms to capture long-range dependencies in text, enabling them to generate coherent and contextually appropriate language. GPT models have demonstrated remarkable capabilities in text generation, including story writing, code completion, language translation, and even composing poetry.

generative ai models

There are artifacts like PAC-MAN and GTA that resemble real gameplay and are completely generated by artificial intelligence. Pioneering generative AI advances, NVIDIA presented DLSS (Deep Learning Super Sampling). The 3rd generation of DLSS increases performance for all GeForce RTX GPUs using AI to create entirely new frames and display higher resolution through image reconstruction. Video is a set of moving visual images, so logically, videos can also be generated and converted similar to the way images can. If we take a particular video frame from a video game, GANs can be used to predict what the next frame in the sequence will look like and generate it. In 2022, Apple acquired the British startup AI Music to enhance Apple’s audio capabilities.

Image-to-image translation

A transformer is made up of multiple transformer blocks, also known as layers. GANs offer an effective way to train such rich models to resemble a real
distribution. To understand how they work we’ll need to understand the basic
structure of a GAN.

Such algorithms can learn to recreate images of cats and guinea pigs, even those that were not in the training set. Say, we have training data that contains multiple images of cats and guinea pigs. And we also have a neural net to look at the image and tell whether it’s a guinea pig or a cat, paying attention to the features that distinguish them. The more neural networks intrude on our lives, the more the areas of discriminative and generative modeling grow.

Adobe Releases New Firefly Generative AI Models and Web App; Integrates Firefly Into Creative Cloud and Adobe Express

And overall, just 23 percent of respondents say at least 5 percent of their organizations’ EBIT last year was attributable to their use of AI—essentially flat with the previous survey—suggesting there is much more room to capture value. Respondents at AI high performers most often point to models and tools, such as monitoring model performance in production and retraining models as needed over time, as their top challenge. By comparison, other respondents cite strategy issues, such as setting a clearly defined AI vision that is linked with business value or finding sufficient resources.

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.

The next two recent projects are in a reinforcement learning (RL) setting (another area of focus at OpenAI), but they both involve a generative model component. Building a generative AI model has for the most part been a major undertaking, to the extent that only a few well-resourced tech heavyweights Yakov Livshits have made an attempt. OpenAI, the company behind ChatGPT, former GPT models, and DALL-E, has billions in funding from boldface-name donors. DeepMind is a subsidiary of Alphabet, the parent company of Google, and Meta has released its Make-A-Video product based on generative AI.

But a much smaller share of respondents report hiring AI-related-software engineers—the most-hired role last year—than in the previous survey (28 percent in the latest survey, down from 39 percent). Roles in prompt engineering have recently emerged, as the need for that skill set rises alongside gen AI adoption, with 7 percent of respondents whose organizations have adopted AI reporting those hires in the past year. Today, there are already systems that can ingest large volumes data, sift through it, and help find patterns in the noise.

Indonesia’s nascent generative AI sector faces challenges in scaling up – The Jakarta Post – The Jakarta Post

Indonesia’s nascent generative AI sector faces challenges in scaling up – The Jakarta Post.

Posted: Mon, 18 Sep 2023 01:11:16 GMT [source]

This can be useful for creating content without any cost, and you don’t need to pay anyone for their photo. DeOldify is an open-source tool used to colorize black and white images. With the following examples, the first is a picture I took of my room in sepia, and the other is a photo of fresh tomatoes and basil. To all who may be interested, did you know that you can generate images using AI? Read our article on Stability AI to learn more about an ongoing discussion regarding the challenges generative AI faces. The online survey was in the field April 11 to 21, 2023, and garnered responses from 1,684 participants representing the full range of regions, industries, company sizes, functional specialties, and tenures.

This is the basis for tools like Dall-E that automatically create images from a text description or generate text captions from images. Deep Reinforcement Learning (DRL) models combine reinforcement learning algorithms with deep neural networks to generate intelligent and adaptive behaviors. These models learn through trial and error, exploring different actions in an environment and receiving feedback in the form of rewards. DRL models have been applied in game playing, robotics, recommendation systems, and autonomous driving, among other areas, generating sophisticated and goal-oriented actions. Kris Ruby, the owner of public relations and social media agency Ruby Media Group, is now using both text and image generation from generative models.

  • In the short term, work will focus on improving the user experience and workflows using generative AI tools.
  • Google has since unveiled a new version of Bard built on its most advanced LLM, PaLM 2, which allows Bard to be more efficient and visual in its response to user queries.
  • Check out the latest GTC sessions to demystify generative AI, learn about the latest technologies, and see how it’s affecting the world today.

In healthcare, one example can be the transformation of an MRI image into a CT scan because some therapies require images of both modalities. But CT, especially when Yakov Livshits high resolution is needed, requires a fairly high dose of radiation to the patient. Some of the most well-known examples of transformers are GPT-3 and LaMDA.

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