Transformers.js allows users to run the following Transformers in their browsers: BERT, ALBERT, DistilBERT, T5, T5v1.1, FLAN-T5, GPT2, BART, CodeGen, Whisper, CLIP, Vision Transformer, and VisionEncoderDecoder.

2023.03.17

github.comGitHub repositoryTLDR

$24K A YEAR

2023.03.17

arstechnica.com8 min readTLDR

HUNDREDS OF GOOGLE WORKERS IN ZURICH WALKED OUT AFTER 200 OF THEIR COLLEAGUES GOT LAID OFF

Google rejected a proposal from thousands of staff who offered to have their wages and hours reduced to avoid job losses.

2023.03.17

archive.ph5 min readTLDR

2023.03.17

blogs.microsoft.com7 min readTLDR AI

STRIPE AND OPENAI

2023.03.17

stripe.com2 min readTLDR AI

PWC USING GENERATIVE AI FOR LEGAL

2023.03.17

pwc.com3 min readTLDR AI

S4 TAKES ON RL

S4 models are a great new long range architecture. This work modifies them so they can initialize and update their internal state in parallel and then explores the modifications on a meta learning task. They found some promising results that point to S4 and other state space models potentially being used as the default RL architecture over LSTMS.

2023.03.17

arxiv.org12 min readTLDR AI

INVESTIGATING GANSFORMER: A VARIATION OF GANS FOR IMAGE GENERATION

The article discusses the authors' reproduction and evaluation of the GANformer, a variation of the Generative Adversarial Networks (GANs) used for image generation. They successfully recreated both variations of the model and found differences between their results and those of the authors, as well as two undisclosed variations of the presented procedures.

2023.03.17

arxiv.org18 min readTLDR AI

RE-REND: REAL-TIME RENDERING OF NERFS ACROSS DEVICES

This paper proposes Re-ReND, a method designed to achieve real-time performance of Neural Radiance Field (NeRF) rendering on resource-constrained devices by converting the NeRF into a representation that can be efficiently processed by standard graphics pipelines, distilling the NeRF by extracting the learned density into a mesh, and factorizing the learned color information into a set of matrices that represent the scene’s light field.

2023.03.17

arxiv.org15 min readTLDR AI

NANOT5

The repository contains code for reproducing a pre-trained T5 language model with limited resources in PyTorch. The model is pre-trained on the C4 dataset and fine-tuned on Super-Natural Instructions (SNI). Despite using only one GPU and limited resources, the model achieves ~40 RougeL on the SNI test set, compared to ~42 RougeL of the original HuggingFace model. The contribution is a user-friendly template for NLP research.

2023.03.17

github.comGitHub repositoryTLDR AI

LLAMA SUPPORT IN HUGGINGFACE

2023.03.17

github.comGitHub repositoryTLDR AI

BIFORMER: VISION TRANSFORMER WITH BI-LEVEL ROUTING ATTENTION

The article discusses the use of attention as a powerful tool for capturing long-range dependencies in vision transformers but highlights the challenge of its high computational burden and memory footprint. To address this issue, the authors propose a dynamic sparse attention via bi-level routing that allows for flexible allocation of computations with content awareness. The proposed BiFormer model, which utilizes the bi-level routing attention, shows good performance and high computational efficiency across various computer vision tasks.

2023.03.17

github.comGitHub repositoryTLDR AI

MOZILLA RESPONSIBLE AI CHALLENGE

2023.03.17

axios.com3 min readTLDR AI

CHALLENGE: READ ANCIENT SCROLLS WITH ML

The Vesuvius Challenge aims to read an unopened Herculaneum scroll for the first time and is offering $250,000 in prizes, including a $150,000 Grand Prize and $100,000 in Progress Prizes. Contestants receive 3D X-ray scans, papyrus fragments, tutorials, and tools to virtually unwrap the scrolls. They also have access to a Discord server to connect with other contestants and the Vesuvius Challenge team. The competition is open, and the organizers believe that it will help achieve the goal by 2023.

2023.03.17

scrollprize.org3 min readTLDR AI