Tech Xplore

Compression technique makes AI models leaner and faster while they're still learning

Training a large artificial intelligence model is expensive, not just in dollars, but in time, energy, and computational ...
CNET

Meta Unveils New AI Model Developed by Costly, New Superintelligence Labs

The new model, known as Muse Spark, was created by Meta Superintelligence Labs, a team of expensive AI leaders and developers ...

New framework lets AI agents rewrite their own skills without retraining the underlying model

Memento-Skills lets AI agents rewrite their own skills using reinforcement learning, hitting 80% task success vs. 50% for ...
EurekAlert!

AI model boosts accuracy and reliability in predicting biochar production

Researchers have developed a powerful new artificial intelligence model that can accurately predict biochar yield and composition, helping scientists and industry optimize production while reducing ...
IEEE

An Adaptive deep reinforcement learning Routing Decision Algorithm – Based on ResNet-BiLSTM-ProbSparseAttention and Imitation Learning

Abstract: Wireless Sensor Networks (WSNs) have become an indispensable part of the Internet of Things (IoT). How to balance energy consumption and data transmission to further extend the overall ...
AOL

Exposed: How Bill Gates' Connections to Pedophile Jeffrey Epstein Landed Tech Billionaire at the Center of a Deep State Cover-up Conspiracy Theory Involving Sick Pedo

Gates, who turned 70 on October 28, has previously denied any connections to Epstein's vile sex trafficking ring and confessed he "foolish to spend any time with him" at all. The tech billionaire said ...
SciELO

LEAF NITROGEN CLASSIFICATION OF COMMON BEAN (PHASEOLUS VULGARIS L.) USING DEEP LEARNING MODELS AND IMAGES

Beans are a legume that is widely grown and consumed globally, being the staple food for humans in developing countries. Nitrogen (N) is the most limiting nutrient for yield and foliar analysis is ...
IEEE

A Hybrid Wavelet-Resnet Diffusion Based Deep Learning Model for Ocular Disease Classification

Deep learning models have become indispensable in medical image analysis, particularly for detecting and classifying ocular diseases. Automated diagnostic systems are promising to improve accuracy and ...
Frontiers

Development and validation of a deep learning model using MR imaging for predicting brain metastases: an accuracy-focused study

Brain metastases (BM), originating from extracranial malignancies, significantly threaten patient health. Accurate BM identification is crucial but labor-intensive manually. This study developed and ...
C&EN

Deep Learning-Based Shape Classification for Hyperspectral-Imaged Microplastics

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. Figure 1 illustrates the overall workflow of the hyperspectral ...