Revised Chinchilla scaling laws – LLM compute and token requirementseducatingsilicon.com·1 pts·panabee·0
Illuminate: Turn academic papers into AI-generated audio discussionsilluminate.withgoogle.com·3 pts·panabee·1
CatLIP: Clip Vision Accuracy with 2.7x Faster Pre-Training on Web-Scale Dataarxiv.org·48 pts·panabee·4
Patchscopes: A framework for viewing hidden representations of language modelsresearch.google·12 pts·panabee·0
Fast-forward – comparing a 1980s supercomputer to the modern smartphoneblog.adobe.com·2 pts·panabee·0
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient LMsarxiv.org·1 pts·panabee·0
Stanford researchers: 45% of GPT4 responses to medical queries hallucinatetwitter.com·3 pts·panabee·4
Shallow Feed-Forward Neural Networks as Alternative to Attention in Transformershuggingface.co·11 pts·panabee·0
FlashFFTConv: Efficient Convolutions for Long Sequences with Tensor Coreshazyresearch.stanford.edu·3 pts·panabee·0
The core contribution of "Attention is All You Need" is logistic regressionstwitter.com·1 pts·panabee·1
'Anti-hunger' molecule forms after exercise, scientists discover (2022)med.stanford.edu·1 pts·panabee·0