Tuesday, 10th October 2023
Bottleneck T5 Text Autoencoder (via) Colab notebook by Linus Lee demonstrating his Contra Bottleneck T5 embedding model, which can take up to 512 tokens of text, convert that into a 1024 floating point number embedding vector... and then then reconstruct the original text (or a close imitation) from the embedding again.
This allows for some fascinating tricks, where you can do things like generate embeddings for two completely different sentences and then reconstruct a new sentence that combines the weights from both.
Wikimedia Commons: Photographs by Gage Skidmore (via) Gage Skidmore is a Wikipedia legend: this category holds 93,458 photographs taken by Gage and released under a Creative Commons license, including a vast number of celebrities taken at events like San Diego Comic-Con. CC licensed photos of celebrities are generally pretty hard to come by so if you see a photo of any celebrity on Wikipedia there’s a good chance it’s credited to Gage.