Adaptive Weight Decay

UC Berkeley and Stanford researchers have developed a parameter-efficient fine-tuning method called Low-Rank Adaptation (LoRA) for deploying language models. The method, S-LoRA, allows thousands of adapters to run efficiently on a single GPU or across multiple…

Understanding Edge Devices and AI Integration Edge devices such as smartphones, IoT devices, and embedded systems process data right where it is generated. This practice enhances privacy, lowers latency, and improves responsiveness. However, implementing large language…

Introduction to Long-Form Video Understanding Understanding long-form videos, which can last from several minutes to hours, poses significant challenges in the field of computer vision. As the demand for video analysis grows, especially beyond short clips,…

Practical Solutions and Value of RxEnvironments.jl for AI-driven Simulations Introduction to Free Energy Principle and Active Inference The Free Energy Principle (FEP) and Active Inference (AIF) offer insights into self-organization in natural systems. Agents use generative…

IBM researchers have introduced LAB (Large-scale Alignment for chatbots) to address scalability challenges in instruction-tuning for large language models (LLMs). LAB leverages a taxonomy-guided synthetic data generation process and a multi-phase training framework to enhance LLM…

Researchers have introduced the Listwise Preference Optimization (LiPO) framework, reshaping language model alignment as a listwise ranking challenge. LiPO-λ emerges as a powerful tool leveraging listwise data to enhance alignment, bridging LM preference optimization and Learning-to-Rank,…

Understanding Retrieve and Rank in Document Search What is Retrieve and Rank? The “retrieve and rank” method is gaining popularity in document search systems. It works by first retrieving documents and then re-ordering them based on…

Magika is an AI-powered file type detection tool that uses deep learning to accurately identify file types, achieving remarkable precision and recall rates of 99% or more. It offers Python command line, Python API, and TFJS…

Practical AI Solutions for Advanced AI Deployment Introduction to AI Deployment Challenges In the world of artificial intelligence (AI), the use of large language models (LLMs) like GPT-4 has greatly advanced generative AI applications. However, the…

Importance of Sampling from Complex Probability Distributions Sampling from complex probability distributions is crucial in fields like statistical modeling, machine learning, and physics. It helps generate representative data points to solve problems such as: Bayesian inference…

In 2024, deepsense.ai experts predict major advancements in AI: 1. Edge AI: Closer AI capabilities enable real-time decision-making, enhance privacy, and improve scalability in language communication, the metaverse, and various industries. 2. Large Language Models (LLMs):…

The year 2023 saw significant developments in the Generative AI landscape, marked by the release of multiple LLMs and the emergence of LLMOps. While there were challenges in production, it was a year of experimentation and…

In recent years, artificial intelligence (AI) has emerged as a game-changer for businesses across various sectors. With rapid advancements in AI technologies—such as natural language processing, machine learning, and neural networks—companies are increasingly harnessing these tools…

RealFill is a novel framework introduced by researchers to address the challenge of Authentic Image Completion. It aims to generate content that fills in missing parts of a photograph while remaining faithful to the original scene.…

L0.5, L3, and L4 regularizations are uncommon due to their non-convex nature and lack of unique benefits over L1/L2 regularizations. Non-convex L0.5 is complex, while higher norms like L3 and L4 don’t offer significant advantages and…