- Thu. Nov 28th, 2024
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Advancements in Protein Sequence Design: Leveraging Reinforcement Learning and Language Models
Protein sequence design is crucial in protein engineering for drug discovery. Traditional methods like evolutionary strategies and Monte-Carlo simulations often need help to efficiently explore the vast combinatorial space of…
DRLQ: A Novel Deep Reinforcement Learning (DRL)-based Technique for Task Placement in Quantum Cloud Computing Environments
The ever-evolving nature of quantum computing renders managing tasks with the traditional heuristic approach very tricky. These models often struggle with adapting to the changes and complexities of quantum computing…
Syntiant Named 2024 ‘Best Places to Work’ for Fifth Consecutive Year
Syntiant Corp., the recognized leader in low power edge AI deployment, today announced it has been listed as one of 2024’s “Best Places to Work in Orange County” by the Orange…
Solomon to advance Robotics with NVIDIA Isaac Robotics Platform
Solomon, a leader in advanced vision and robotics solutions, is excited to announce a collaboration with NVIDIA at COMPUTEX 2024. This collaboration focuses on integrating Solomon’s product offerings with the NVIDIA Isaac robotics…
Top Free Artificial Intelligence AI Courses from Ivy League Colleges
Ivy League Colleges such as Harvard, Stanford, and MIT offer a range of free online courses that make high-quality education accessible to a global audience. These courses span various fields,…
Researchers at the University College London Unravel the Universal Dynamics of Representation Learning in Deep Neural Networks
Deep neural networks (DNNs) come in various sizes and structures. The specific architecture selected along with the dataset and learning algorithm used, is known to influence the neural patterns learned.…
Google Researchers Propose a Formal Boosting Machine Learning Algorithm for Any Loss Function Whose Set of Discontinuities has Zero Lebesgue Measure
As a very effective machine learning ML-born optimization setting, boosting requires one to efficiently learn arbitrarily good models using a weak learner oracle, which provides classifiers that perform marginally better…
Researchers at IT University of Copenhagen Propose Self-Organizing Neural Networks for Enhanced Adaptability
Artificial neural networks (ANNs) traditionally lack the adaptability and plasticity seen in biological neural networks. This limitation poses a significant challenge for their application in dynamic and unpredictable environments. The…
Tsinghua University Open Sources CodeGeeX4-ALL-9B: A Groundbreaking Multilingual Code Generation Model Outperforming Major Competitors and Elevating Code Assistance
In a significant leap forward for the field of code generation, the Knowledge Engineering Group (KEG) and Data Mining team at Tsinghua University have unveiled their latest innovation: CodeGeeX4-ALL-9B. This…
T-FREE: A Tokenizer-Free Approach for Efficient and Scalable Text Encoding in Large Language Models
Natural language processing (NLP) drives researchers to develop algorithms that enable computers to understand, interpret, and generate human languages. These efforts cover various applications, such as machine translation, sentiment analysis,…