Rakis: Decentralized AI Network, Efficient FeedForward Networks, Multilingual Detoxification, and Performance Analysis of Vision Models

Introducing Rakis, a decentralized verifiable AI network in the browser. Cutting costs with structured FeedForward Networks in Transformer-based LLMs. Researchers explore zero-shot cross-lingual generalization of preference tuning in detoxifying LLMs. Comprehensive analysis of the performance of Vision State Space Models, Vision Transformers, and Convolutional Neural Networks.

Sources:
https://www.marktechpost.com/2024/07/01/meet-rakis-a-decentralized-verifiable-artificial-intelligence-ai-network-in-the-browser/
https://www.marktechpost.com/2024/06/30/cutting-costs-not-performance-structured-feedforward-networks-ffns-in-transformer-based-llms/
https://www.marktechpost.com/2024/06/30/researchers-at-brown-university-explore-zero-shot-cross-lingual-generalization-of-preference-tuning-in-detoxifying-llms/
https://www.marktechpost.com/2024/06/30/comprehensive-analysis-of-the-performance-of-vision-state-space-models-vssms-vision-transformers-and-convolutional-neural-networks-cnns/

Outline:
(00:00:00) Introduction
(00:00:47) Meet Rakis: A Decentralized Verifiable Artificial Intelligence AI Network in the Browser
(00:03:18) Cutting Costs, Not Performance: Structured FeedForward Networks FFNs in Transformer-Based LLMs
(00:06:40) Comprehensive Analysis of The Performance of Vision State Space Models (VSSMs), Vision Transformers, and Convolutional Neural Networks (CNNs)