Neural networks are used to help robots learn, understand, and react to their environments. They follow a software model designed to function similarly to a human brain’s biological neural pathways. Neural networks are composed of multi-layered “neurons” that take in and process data – the input layer, the hidden layers, and the output layer. Like a human brain, neural networks strive to predict accurate outcomes by weighing the data they receive over time. Neural networks are the supporting architecture of machine learning.
RIT Researchers Work to Make Mobile Robots for Warehouses Smarter
March 15, 2022
RIT faculty and researchers are developing ways for autonomous mobile robots to move more intelligently around warehouses. They have worked with The Raymond Corp. and Simcona Electronics Corp.
ENOT Debuts Technology to Optimize Deep Neural Networks for Speed, Compression, and Energy Efficiency
March 14, 2022
ENOT.ai said its framework optimizes neural network architectures for accuracy and efficiency. The company said its framework, which has a Python API, can help robotics developers.
Bowery Farming Purchases Traptic to Expand Agricultural Prowess
February 21, 2022
Indoor grower Bowery Farming has acquired fruit-picking robot provider Traptic to harvest produce such as strawberries.
Cognitive Rail Pilot Complies With Eurasian Economic Union Requirements, Starts Mass Production
January 24, 2022
Cognitive Rail Pilot is an AI-based system designed to help engine drivers avoid errors that may lead to accidents and to help locomotive fleet operators boost efficiency.
Ambarella Launches CV3 AI Domain Controller for Autonomous Vehicle Perception
January 4, 2022
Ambarella says its CV3 domain controller offers single-chip high performance for AI and sensor fusion at low power for autonomous vehicles and driver-assist systems.