Computer Sciences

When it comes to AI, can we ditch the datasets?

Huge amounts of data are needed to train machine-learning models to perform image classification tasks, such as identifying damage in satellite photos following a natural disaster. However, these data are not always easy ...

Computer Sciences

A model that can realistically insert humans into images

The recent advent of generative models, computational tools that can generate new texts or images based on the data they are trained on, opened interesting new possibilities for the creative industries. For example, they ...

Computer Sciences

New tool finds bias in state-of-the-art generative AI model

Text-to-image (T2I) generative artificial intelligence tools are increasingly powerful and widespread tools that can create nearly any image based on just a few inputted words. T2I generative AI can create convincingly realistic ...

Computer Sciences

Synthetic imagery sets new bar in AI training efficiency

Data is the new soil, and in this fertile new ground, MIT researchers are planting more than just pixels. By using synthetic images to train machine learning models, a team of scientists recently surpassed results obtained ...

Computer Sciences

PizzaGAN gets the picture on how to make a pizza

Is nothing sacred? Who would dare to even attempt to talk about a machine-learning experiment that results in the perfect (gasp) pizza? It is difficult to contemplate, but a research quintet did not shy away from trying, ...

Machine learning & AI

Researchers measure reliability, confidence for next-gen AI

A team of Army and industry researchers have developed a metric for neural networks—computing systems modeled loosely after the human brain—that could assess the reliability and confidence of the next generation of artificial ...

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