Using five million real online purchases, researchers trained an AI that can create fake e-commerce orders.
How it works: A generative adversarial network (GAN) consists of two dueling neural networks that create realistic synthetic media, likethese fake photos of celebrities or made-up articles of clothing. Researchers with Amazon’s machine-learning team in India published a paper documenting eCommerceGAN, a system that can come up with any number of “plausible” orders. They also documented a second system called ec2GAN, built to create possible orders involving a specific product.
What it means: Real orders make up only a tiny fraction of all possible orders. Artificial-intelligence systems work better with more data, and parsing synthetic data like this could help Amazon improve its business by learning even more about how factors like customer preferences, price estimation, and seasonal variance affect product choices. It could also get better at predicting which items might be of interest to what type of customer.
This artist is dominating AI-generated art. And he’s not happy about it.
Greg Rutkowski is a more popular prompt than Picasso.
What does GPT-3 “know” about me?
Large language models are trained on troves of personal data hoovered from the internet. So I wanted to know: What does it have on me?
DeepMind has predicted the structure of almost every protein known to science
And it’s giving the data away for free, which could spur new scientific discoveries.
An AI that can design new proteins could help unlock new cures and materials
The machine-learning tool could help researchers discover entirely new proteins not yet known to science.
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