AI-powered spectral sensor performs machine learning during light capture, identifying materials and chemicals in real time ...
In a study published in Robot Learning journal, researchers propose a new learning-based path planning framework that allows mobile robots to navigate safely and efficiently using a Transformer model.
A Cornell University fellow develops strategies to extract more than correlations from algorithms’ predictions.
Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...
Quantum computing is an emerging paradigm that leverages the principles of quantum mechanics to solve computational problems beyond the reach of classical computers. This article provides an overview ...
Abstract: Real-time multi-agent internet data transmission enhances the service capabilities of diverse applications, however, it poses a risk of sensitive location information being compromised. This ...
The amino acid sequence of the transmembrane protein and its corresponding positions on the cell membrane are transformed into a hidden Markov process. After evaluating the parameters, the Viterbi ...
Google has demonstrated a 13,000 times speedup for the Quantum Echoes algorithm using its Willow quantum chip. The feat is repeatable, according to the company, and it paves the way toward real-world ...
In this video, we explore why Spotify's shuffle feature isn't truly random and operates based on an algorithm. We discuss the reasons behind our preferences for non-random shuffle, the results of an ...
Amsterdam’s struggles with its welfare fraud algorithm show us the stakes of deploying AI in situations that directly affect human lives. What Amsterdam’s welfare fraud algorithm taught me about fair ...
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