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Recent advancements in (self) supervised learning models have been driven by empirical scaling laws, where a model's performance scales with its size. However, such scaling laws have been challenging to establish in reinforcement learning (RL). Unlike...
Large Language Models (LLMs) have significantly evolved in recent times, especially in the areas of text understanding and generation. However, there have been certain difficulties in optimizing LLMs for more effective human instruction delivery. While LLMs...

Meet Rodin: A Novel Artificial Intelligence (AI) Framework To Generate 3D Digital Avatars From Various Input Sources

Generative models are becoming the de-facto solution for many challenging tasks in computer science. They represent one of the most promising ways to analyze...

This Python Library ‘Imitation,’ Provides Open-Source Implementations of Imitation and Reward Learning Algorithms in PyTorch

In areas with clearly defined reward functions, like games, reinforcement learning (RL) has outperformed human performance. Unfortunately, it is difficult or impossible for many...

AI Research At The French CNRS Proposes A Noise-Adaptive Intelligent Programmable Meta-Imager: A Timely Approach To Task-Specific, Noise-Adaptive Sensing

Researchers from the French CNRS have come up with a Noise-Adaptive Intelligent Programmable Meta-Imager. Sensing systems are increasingly used in many aspects of our...

New AI Research from the University of Maryland Investigates Cramming Challenge for Training a Language Model on a Single GPU in One Day

In many areas of natural language processing, including language interpretation and natural language synthesis, large-scale training of machine learning models utilizing transformer topologies has...

This Artificial Intelligence Paper Presents an Advanced Method for Differential Privacy in Image Recognition with Better Accuracy

Machine learning has increased considerably in several areas due to its performance in recent years. Thanks to modern computers' computing capacity and graphics cards,...

Meet Powderworld: A Lightweight Simulation Environment For Understanding AI Generalization

Despite recent advances in RL research, the ability to generalize to new tasks remains one of the major issues in both reinforcement learning (RL)...

Meet DiffusionDet: An Artificial Intelligence (AI) Model That Uses Diffusion for Object Detection

Object detection is a powerful technique for identifying objects in images and videos. Thanks to deep learning and computer vision advances, it has come...

Artificial Intelligence (AI) Researchers from Cornell University Propose a Novel Neural Network Framework to Address the Video Matting Problem

Image and video editing are two of the most popular applications for computer users. With the advent of Machine Learning (ML) and Deep Learning...

What Does it Mean to Deploy a Machine Learning Model?

Data Science, a promising field that continues to attract more and more companies, is struggling to be integrated into industrialization processes. In most cases,...

Meet FathomNet: An Open-Source Image Database That Uses Artificial Intelligence and Machine Learning Algorithms To Help Process The Backlog Of Visual Data For Understanding...

The ocean is changing at an unprecedented rate, making it challenging to maintain responsible stewardship while visually monitoring vast amounts of marine data. The...

Researchers at Michigan State University Developed ‘DANCE,’ a Python Library to Support Deep Learning Models for Analyzing Single-Cell Gene Expression at Scale

From single-modality profiling (RNA, protein, and open chromatin) to multimodal profiling and spatial transcriptomics, the technology for analyzing single cells has advanced rapidly in...

Researchers From China Proposed A Novel μXRD Image Screening Method Based On Federated Learning (FL) To Improve The Screening While Protecting Data Privacy

Federated learning provides a mechanism to unleash data to fuel new AI applications by training AI models without letting anyone see or access your...

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