Vector Institute

4 Posts

Goodbye Prompt Engineering, Hello Prompt Generation: Automatic Prompt Engineer (APE) research summary.
Vector Institute

Goodbye Prompt Engineering, Hello Prompt Generation: Automatic Prompt Engineer (APE) research summary.

When you’re looking for answers from a large language model, some prompts are better than others. So how can you come up with the best one? A new model automates the process.
Few-shot Learning with a Universal Template (FLUTE)
Vector Institute

Pattern for Efficient Learning: A training method for few-shot learning in computer vision.

Getting high accuracy out of a classifier trained on a small number of examples is tricky. You might train the model on several large-scale datasets prior to few-shot training, but what if the few-shot dataset includes novel classes? A new method performs well even in that case.
Data related to a system that purportedly identified breast cancer
Vector Institute

Pushing for Reproducible Research: Experts criticize Google Health over AI transparency.

Controversy erupted over the need for transparency in research into AI for medicine. Google Health introduced a system that purportedly identified breast cancer more accurately than human radiologists.
Replica of the video game Pac-Man generated by a GAN
Vector Institute

Playing With GANs: GameGAN generated a fully functional Pac-Man.

Generative adversarial networks don’t just produce pretty pictures. They can build world models, too. A GAN generated a fully functional replica of the classic video game Pac-Man.

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