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GPUs Role in Enhancing AI and Machine Learning Techniques

Specialized graphics processing units were originally designed for the efficient performance of processing of images and video. The computing efficiency of GPU computing does more than streamline the analytical process; It can be utilized in expert testimony or discovery. ....

Mike Decesaris , Cornerstone Research , Data Science Center , Cornerstone Research Data Science Center , Graphics Processing Units , I And Litigation , Artificial Intelligence , Achine Learning And Law , Atrix Arithmetic , Language Models , Deep Neural Networks , Boosted Trees , Ow To Be More Efficient In Analyzing Data ,

Researchers at Georgia Tech Propose 'LABOR' (LAyer-neighBOR sampling), A New Sampling Algorithm-Based on Machine Learning

Researchers at Georgia Tech Propose 'LABOR' (LAyer-neighBOR sampling), A New Sampling Algorithm-Based on Machine Learning ....

Graph Neural Networks , Research Goes To Researchers On This , Graph Library On Github , Neural Networks , Deep Neural Networks , Neighborhood Explosion Phenomenon , Poisson Sampling , Deep Graph Library , Marktechpost Staff ,

Do AI models process things the same way as the human brain?

Do AI models process things the same way as the human brain?
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Philippe Schyns , University Of Glasgow School Psychology , Trends In Cognitive Sciences , University Of Glasgow , Neural Network , Neural Networks , Deep Neural Networks , Cognitive Sciences , Deep Neural Network , Algorithmic Equivalence ,

"DeepVIP: Deep Learning-Based Vehicle Indoor Positioning Using Smartpho" by Baoding Zhou, Zhining Gu et al.

The advent of sensor-rich smart devices (e.g., smartphones) has enabled a lot of applications and services. One of these applications and services is smartphone-based vehicle indoor positioning, which is a key technology for smart car parking and driverless cars. So far, most vehicle indoor positioning solutions either use infrastructures (e.g., WiFi access points) or inertial sensors, which suffer from low positioning accuracy, limited coverage, or high cost to deploy new equipment. To tackle these challenges, in this work we propose a novel Deep Learning-based Vehicle Indoor Positioning (DeepVIP) approach using smartphone built-in sensors, including accelerometer, gyroscope, magnetometer, and gravity sensor. Experiments are conducted in indoor parking areas. Experimental results show that the proposed method outperforms the state-of-the-art methods. ....

Deep Learning Based Vehicle Indoor Positioning , Ata Driven Inertial Navigation , Deep Neural Networks , Indoor Localization , Inertial Navigation , Location Awareness , Smart Phones , Smartphone Sensors , Wireless Fidelity ,

Researchers propose a roadmap to understand whether AI models and the human brain process things the same way

Deep Neural Networks – part of the broader family of machine learning – have become increasingly powerful in everyday real-world applications such as automated face recognition systems and self-driving cars. Researchers use Deep Neural Networks, or DNNs, to model the processing of information, and to investigate how this information processing matches that of humans. While… ....

Philippe Schyns , University Of Glasgow , Sciences Research Council , University Of Glasgow School Psychology , Trends In Cognitive Sciences , Neural Network , Dean Of Research Technology , Neural Networks , Deep Neural Networks , Cognitive Sciences , Deep Neural Network , Research Technology , Algorithmic Equivalence , Physical Sciences Research ,