Categories: AI/ML News

Reinforcement learning allows underwater robots to locate and track objects underwater

A research team has shown for the first time that reinforcement learning—i.e., a neural network that learns the best action to perform at each moment based on a series of rewards—allows autonomous vehicles and underwater robots to locate and carefully track marine objects and animals.
AI Generated Robotic Content

Share
Published by
AI Generated Robotic Content

Recent Posts

Let’s Destroy the E-THOT Industry Together!

I created a completely local Ethot online as an experiment. I dream of a world…

10 hours ago

Vector Databases Explained in 3 Levels of Difficulty

Traditional databases answer a well-defined question: does the record matching these criteria exist?

10 hours ago

Drop-In Perceptual Optimization for 3D Gaussian Splatting

Despite their output being ultimately consumed by human viewers, 3D Gaussian Splatting (3DGS) methods often…

10 hours ago

Frontend Engineering at Palantir: Redefining Real-Time Map Collaboration

How we built lightweight, real-time map collaboration for teams operating at the edge.About This SeriesFrontend engineering at…

10 hours ago

Run Generative AI inference with Amazon Bedrock in Asia Pacific (New Zealand)

Kia ora! Customers in New Zealand have been asking for access to foundation models (FMs)…

10 hours ago

The new AI literacy: Insights from student developers

AI has made it easier than ever for student developers to work efficiently, tackle harder…

10 hours ago