AI

by Rockwell Anyoha Can Machines Think? In the first half of the 20th century, science fiction familiarized the world with the concept of artificially intelligent robots. It began with the “heartless” Tin man from the Wizard of Oz and continued with the humanoid robot that impersonated Maria in Metropolis. By the 1950s, we had a generation of scientists, mathematicians, and philosophers with the concept of …

Translations: Vietnamese. (V2 Nov 2022: Updated images for more precise description of forward diffusion. A few more images in this version) AI image generation is the most recent AI capability blowing people’s minds (mine included). The ability to create striking visuals from text descriptions has a magical quality to it and points clearly to a shift in how humans create art. The release of Stable Diffusion is a clear milestone in this development because it made a high-performance model available to the masses (performance in terms of image quality, as well as speed and relatively low resource/memory requirements). After experimenting with AI image generation, you may start to wonder how it works. This is a gentle introduction to how Stable Diffusion works. Stable Diffusion is versatile in that it can be used in a number of different ways. Let’s focus at first on image generation from text only (text2img). The image above shows an example text input and the resulting generated image (The actual complete prompt is here). Aside from text to image, another main way of using it is by making it alter images (so inputs are text + image).

From bullshit generation to culture wars and the end of ad revenue.

Do you like AI tools but have trouble getting the desired results? Then it's time to meet the concept of

Amid AI platitudes, mankind's input will still be prized

Or 10 tweets about ChatGPT

Two weeks ago, the Stable Diffusion image generation model was released to the public. I wrote about this last week, in Stable Diffusion is a really big deal—a post which …

Using CLIP and LAION5B to collect thousands of captioned images.

When large language models fall short, the consequences can be serious. Why is it so hard to acknowledge that?

“The computer has long been a solution looking for problems—the ultimate technological fix which insulates us from having to look at problems.” – Joseph Weizenbaum (1983)   Trying to kee…

A group of artists has filed a class action complaint against a trio of A.I. image generators, claiming copyright violations.

The Historical Figures app's factual errors are egregious, but some experts are more worried about its implications on knowledge authority.

OpenAI's new AI conversational bot, ChatGPT, has quickly gained popularity. The language model, which is based on GPT-3, has the ability to generate text and engage in conversations. In this text, the authors discuss potential implications such technology can have for media research.

At least four articles credit the AI tool as a co-author, as publishers scramble to regulate its use.