AI image generators can create realistic-seeming photographs. They can also edit preexisting images. Like other types of generative AI, AI image generation models can interpret natural-language prompts and create images in response. "Make an image of an elephant" is a valid prompt — although su...
What is generative AI? ChatGPT, Bing Chat, and Bard - we explain how artificial intelligence works, with the most relevant examples of today.
What is the best AI art generator? The best AI art generator is Midjourney. We can be confident in such a matter-of-fact statement because the results speak for themselves. With 16,000,000+ users, Midjourney is the most popular paid AI image generator. Very impressive monthly user figures...
Machine learning, a subset of artificial intelligence, is where the foundations for Generative AI were laid. With the development of thefirst machine learning model in the 1950's, as time progressed and algorithms became more sophisticated, deep learning took these computing system capabilities further...
Image created with Midjourney The next type of AI, general or strong AI, is also known as artificial general intelligence (AGI). These systems are not limited to a specific area of expertise and can perform various tasks beyond those of weak AI programs. While we have yet to achieve this...
Generative AI is artificial intelligence (AI) that can create original content in response to a user’s prompt or request.
while the discriminator evaluates them against a set of real data. The generator’s goal is to produce data that is indistinguishable from real data, while the discriminator’s goal is to correctly distinguish between the two. Over time, the generator improves, creating increasingly realistic data...
These machine learning systems use two neural networks — a system of algorithms mimicking the human brain’s function — one responsible for generating new data and the another for evaluating how realistic it is. Next are Variational Autoencoders (VAEs), another type of machine learning systems...
At a very high level, the reason for this is that some amount of randomness is key to making the responses from generative AI realistic. If a tool always picks the most likely prediction at every turn, it will often end up with an output that doesn’t make sense. ...
Image by Pro_Vector / shutterstock.com Generative AI made significant strides with the advent of Generative Adversarial Networks, or GANs. A GAN is made up of two competing parts: ageneratorand adiscriminator. These two parts work together to create very realistic “synthetic data.” ...