AI Drives Surge in Shared Cloud Infrastructure Spending in Q1 2024
According to the International Data Corporation (IDC) Worldwide Quarterly Enterprise Infrastructure Tracker: Buyer and Cloud Deployment, spending on compute and storage infrastructure products for cloud deployments, including dedicated and shared IT…
Meet Rakis: A Decentralized Verifiable Artificial Intelligence AI Network in the Browser
Traditional AI inference systems often rely on centralized servers, which pose scalability limitations, privacy risks, and require trust in centralized authorities for reliable execution. These centralized models are also at…
Cutting Costs, Not Performance: Structured FeedForward Networks FFNs in Transformer-Based LLMs
Optimizing the efficiency of Feedforward Neural Networks (FFNs) within Transformer architectures is a significant challenge in AI. Large language models (LLMs) are highly resource-intensive, requiring substantial computational power and energy,…
Researchers at Brown University Explore Zero-Shot Cross-Lingual Generalization of Preference Tuning in Detoxifying LLMs
Large language models (LLMs) have gained significant attention in recent years, but their safety in multilingual contexts remains a critical concern. Researchers are grappling with the challenge of mitigating toxicity…
How Valuable is Interpretability and Analysis Work for NLP Research? This Paper Investigate the Impact of Interpretability and Analysis Research on NLP
Natural language processing (NLP) has experienced significant growth, largely due to the recent surge in the size and strength of large language models. These models, with their exceptional performance and…
Comprehensive Analysis of The Performance of Vision State Space Models (VSSMs), Vision Transformers, and Convolutional Neural Networks (CNNs)
Deep learning models like Convolutional Neural Networks (CNNs) and Vision Transformers achieved great success in many visual tasks, such as image classification, object detection, and semantic segmentation. However, their ability…