Analytics Insight

Avoid These 10 Machine Learning Project Mistakes

Overview: Clear problem definitions prevent wasted effort and keep machine learning work focused.Clean, well-understood data ...
The Diplomat

Japan’s Long Return to Artificial Intelligence

Once a pioneer that helped the world lay the foundations of machine learning, Japan’s renewed push into artificial ...
Morning Overview on MSN

Scientists built a working brain, and the stakes just exploded

Researchers have crossed a threshold that once belonged squarely to science fiction: they have built working models of brains, both in silicon and in living tissue, that can learn, adapt, and even ...
IEEE

Data-Driven Motion Planning: A Survey on Deep Neural Networks, Reinforcement Learning, and Large Language Model Approaches

Abstract: Motion planning is a fundamental challenge in robotics, involving the creation of trajectories from start to goal states while meeting constraints like collision avoidance and joint limits.
Tech Xplore

Machine learning helps robots see clearly in total darkness using infrared

From disaster zones to underground tunnels, robots are increasingly being sent where humans cannot safely go. But many of ...
Semiconductor Engineering

Accelerating Semiconductor Innovation Through Machine Learning-Driven Modeling

Using AI and machine learning as transformative solutions for semiconductor device modeling and parameter extraction.

Kolmogorov-Arnold networks bridge AI and scientific discovery by increasing interpretability

AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...
TMCnet

WiMi Releases Next-Generation Hybrid Quantum Neural Network Structure Technology, Breaking Through the Bottleneck of Image Multi-Classification

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, launched a hybrid quantum neural network structure (H-QNN) ...
IEEE

Deep Reinforcement Learning with Graph Neural Networks: An Indepth Analysis of Algorithms and Applications

Abstract: Deep Reinforcement Learning (DRL) enable several areas of artificial intelligence, including perception recognition, expert system, recommender program and game. Also, graph neural networks ...
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
AlphaGalileo

Real-Time, Machine Learning-Enhanced Position Recognition for Sub-Half-Wavelength Precision Laser Nanofabrication

Imagine a camera that keeps a laser pencil sharp down to a hair’s width—257 nm! New AI trick watches the tiny bright dot and nudges the stage so ...
European Medical Journal

Machine Learning Shows Promise in Predicting RA Treatment Response

A scoping review shows machine learning models may help predict response to biologic and targeted synthetic DMARDs in ...