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Text-to-image
A text-to-image model is a machine learning model which takes an input natural language prompt and produces an image matching that description. Text-to-image models began to be developed in the mid-2010s during the beginnings of the AI boom, as a result of advances in deep neural networks. In 2022, the output of state-of-the-art text-to-image models—such as OpenAI's DALL-E 2, Google Brain's Imagen, Stability AI's Stable Diffusion, and Midjourney—began to be considered to approach the quality of real photographs and human-drawn art. Text-to-image models are generally latent diffusion models, which combine a language model, which transforms the input text into a latent representation, and a generative image model, which produces an image conditioned on that representation. The most effective models have generally been trained on massive amounts of image and text data scraped from the web. History Before the rise of deep learning, attempts to build text-to-image mo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stable Diffusion
Stable Diffusion is a deep learning, text-to-image model released in 2022 based on Diffusion model, diffusion techniques. The generative artificial intelligence technology is the premier product of Stability AI and is considered to be a part of the ongoing AI boom, artificial intelligence boom. It is primarily used to generate detailed images conditioned on text descriptions, though it can also be applied to other tasks such as inpainting, outpainting, and generating image-to-image translations guided by a prompt engineering, text prompt. Its development involved researchers from the CompVis Group at Ludwig Maximilian University of Munich and Runway (company), Runway with a computational donation from Stability and training data from non-profit organizations. Stable Diffusion is a latent diffusion model, a kind of deep generative artificial neural network. Its code and model weights have been released Source-available software, publicly, and an optimized version can run on most ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
DALL-E
DALL-E, DALL-E 2, and DALL-E 3 (stylised DALL·E) are text-to-image models developed by OpenAI using deep learning methodologies to generate digital images from natural language descriptions known as Prompt engineering, ''prompts''. The first version of DALL-E was announced in January 2021. In the following year, its successor DALL-E 2 was released. DALL-E 3 was released natively into ChatGPT for ChatGPT Plus and ChatGPT Enterprise customers in October 2023, with availability via OpenAI's API and "Labs" platform provided in early November. Microsoft implemented the model in Bing's Image Creator tool and plans to implement it into their Designer app. With Bing's Image Creator tool, Microsoft Copilot runs on DALL-E 3. In March 2025, DALL-E-3 was replaced in ChatGPT by GPT-4o#GPT Image 1, GPT Image 1's native image-generation capabilities. History and background DALL-E was revealed by OpenAI in a blog post on 5 January 2021, and uses a version of GPT-3 modified to generate image ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Imagen (text-to-image Model)
Imagen is a series of text-to-image models developed by Google DeepMind. They were developed by Google Brain until the company's merger with DeepMind in April 2023. Imagen is primarily used to generate images from text prompts, similar to Stability AI's Stable Diffusion, OpenAI's DALL-E, or Midjourney. The original version of the model was first discussed in a paper from May 2022. The tool produces high-quality images and is available to all users with a Google account through services including Gemini, ImageFX, and Vertex AI. History Imagen's original version was first presented in a paper published in May 2022. It featured the ability to generate high-fidelity images from natural language. The second version, Imagen 2 was released in December 2023. The standout feature was text and logo generation. Imagen 3 was released in August 2024. Google claims that the newest version provides better detail and lighting on generated images. On 20 May 2025 at Google I/O 2025 the compan ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Midjourney
Midjourney is a generative artificial intelligence program and service created and hosted by the San Francisco-based independent research lab Midjourney, Inc. Midjourney generates images from natural language descriptions, called '' prompts'', similar to OpenAI's DALL-E and Stability AI's Stable Diffusion. It is one of the technologies of the AI boom. The tool is in open beta as of August 2024, which it entered on July 12, 2022. The Midjourney team is led by David Holz, who co-founded Leap Motion. Holz told ''The Register'' in August 2022 that the company was already profitable. Users create artwork with Midjourney using Discord bot commands or the official website. History Midjourney, Inc. was founded in San Francisco, California, by David Holz, previously a co-founder of Leap Motion. The Midjourney image generation platform entered open beta on July 12, 2022. On March 14, 2022, the Midjourney Discord server launched with a request to post high-quality photographs to Twit ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
AI Boom
The AI boom is an ongoing period of rapid Progress in artificial intelligence, progress in the field of artificial intelligence (AI) that started in the late 2010s before gaining international prominence in the early 2020s. Examples include large language models and generative AI applications developed by OpenAI as well as Protein structure prediction, protein folding prediction led by Google DeepMind. This period is sometimes referred to as an AI spring, to contrast it with previous AI winters. History In 2012, a University of Toronto research team used artificial neural networks and deep learning techniques to lower the error rate below 25% for the AlexNet, first time during the ImageNet challenge for object recognition in computer vision. The event catalyzed the AI boom later that decade, when many alumni of the ImageNet challenge became leaders in the tech industry. In March 2016, AlphaGo beat Lee Sedol in AlphaGo versus Lee Sedol, a five-game match, marking the first ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Google Brain
Google Brain was a deep learning artificial intelligence research team that served as the sole AI branch of Google before being incorporated under the newer umbrella of Google AI, a research division at Google dedicated to artificial intelligence. Formed in 2011, it combined open-ended machine learning research with information systems and large-scale computing resources. It created tools such as TensorFlow, which allow neural networks to be used by the public, and multiple internal AI research projects, and aimed to create research opportunities in machine learning and natural language processing. It was merged into former Google sister company DeepMind to form Google DeepMind in April 2023. History The Google Brain project began in 2011 as a part-time research collaboration between Google fellow Jeff Dean (computer scientist), Jeff Dean and Google Researcher Greg Corrado. Google Brain started as a Google X project and became so successful that it was graduated back to Google: As ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Natural Language Prompt
Prompt engineering is the process of structuring or crafting an instruction in order to produce the best possible output from a generative artificial intelligence (AI) model. A ''prompt'' is natural language text describing the task that an AI should perform. A prompt for a text-to-text language model can be a query, a command, or a longer statement including context, instructions, and conversation history. Prompt engineering may involve phrasing a query, specifying a style, choice of words and grammar, providing relevant context, or describing a character for the AI to mimic. When communicating with a text-to-image or a text-to-audio model, a typical prompt is a description of a desired output such as "a high-quality photo of an astronaut riding a horse" or "Lo-fi slow BPM electro chill with organic samples". Prompting a text-to-image model may involve adding, removing, or emphasizing words to achieve a desired subject, style, layout, lighting, and aesthetic. History In 2018, ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Latent Diffusion Model
The Latent Diffusion Model (LDM) is a diffusion model architecture developed by the CompVis (Computer Vision & Learning) group at LMU Munich. Introduced in 2015, diffusion models (DMs) are trained with the objective of removing successive applications of noise (commonly Gaussian) on training images. The LDM is an improvement on standard DM by performing diffusion modeling in a latent space, and by allowing self-attention and cross-attention conditioning. LDMs are widely used in practical diffusion models. For instance, Stable Diffusion versions 1.1 to 2.1 were based on the LDM architecture. Version history Diffusion models were introduced in 2015 as a method to learn a model that can sample from a highly complex probability distribution. They used techniques from non-equilibrium thermodynamics, especially diffusion. It was accompanied by a software implementation in Theano. A 2019 paper proposed the noise conditional score network (NCSN) or score-matching with Langevin d ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
OpenAI
OpenAI, Inc. is an American artificial intelligence (AI) organization founded in December 2015 and headquartered in San Francisco, California. It aims to develop "safe and beneficial" artificial general intelligence (AGI), which it defines as "highly autonomous systems that outperform humans at most economically valuable work". As a leading organization in the ongoing AI boom, OpenAI is known for the GPT family of large language models, the DALL-E series of text-to-image models, and a text-to-video model named Sora (text-to-video model), Sora. Its release of ChatGPT in November 2022 has been credited with catalyzing widespread interest in generative AI. The organization has a complex corporate structure. As of April 2025, it is led by the Nonprofit organization, non-profit OpenAI, Inc., Delaware General Corporation Law, registered in Delaware, and has multiple for-profit subsidiaries including OpenAI Holdings, LLC and OpenAI Global, LLC. Microsoft has invested US$13 billion ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
University Of Toronto
The University of Toronto (UToronto or U of T) is a public university, public research university whose main campus is located on the grounds that surround Queen's Park (Toronto), Queen's Park in Toronto, Ontario, Canada. It was founded by royal charter in 1827 as King's College, the first institution of higher learning in Upper Canada. Originally controlled by the Church of England, the university assumed its present name in 1850 upon becoming a secular institution. It has three campuses: University of Toronto Mississauga, Mississauga, #St. George campus, St. George, and University of Toronto Scarborough, Scarborough. Its main campus, St. George, is the oldest of the three and located in Downtown Toronto. U of T operates as a collegiate university, comprising 11 #Colleges, colleges, each with substantial autonomy on financial and institutional affairs and significant differences in character and history. The University of Toronto is the largest university in Canada with a t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
COCO (dataset)
These datasets are used in machine learning (ML) research and have been cited in peer-reviewed academic journals. Datasets are an integral part of the field of machine learning. Major advances in this field can result from advances in learning algorithms (such as deep learning), computer hardware, and, less-intuitively, the availability of high-quality training datasets. High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to produce because of the large amount of time needed to label the data. Although they do not need to be labeled, high-quality datasets for unsupervised learning can also be difficult and costly to produce. Many organizations, including governments, publish and share their datasets. The datasets are classified, based on the licenses, as Open data and Non-Open data. The datasets from various governmental-bodies are presented in List of open government data sites. The ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
