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Machine learning

Start developing a more efficient AI assistant by first understanding and replicating the unpredictable actions of humans.

Artificial Intelligence (AI) researchers at MIT and the University of Washington have created a model that can predict a human's decision-making behaviour by learning from their past actions. The model incorporates the understanding that humans can behave sub-optimally due to computational constraints — essentially the idea that humans can't spend indefinitely long periods considering the…

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KAUST researchers alongside Sony AI have put forward FedP3, a machine learning solution developed to address variations in both data and model while emphasizing the importance of privacy.

Researchers from Sony AI and the King Abdullah University of Science and Technology (KAUST) have developed FedP3, a solution aimed at addressing the challenges of model heterogeneity in federated learning (FL). Model heterogeneity arises when devices used in FL have different capabilities and data distributions. FedP3, which stands for Federated Personalized and Privacy-friendly network Pruning,…

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This AI research presents the innovative Pipeline Forward-Forward Algorithm (PFF), a new technique in machine learning for tutoring dispersed neural networks through the use of the Forward-Forward Algorithm.

Training deep neural networks with hundreds of layers can be a painstaking process, often taking weeks due to the sequential nature of the backpropagation learning method. While this process works on a single computer unit, it is challenging to parallelize across multiple systems, leading to long waiting times. This issue escalates further when dealing with enormous…

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The computational model accurately captures the hard-to-detect transition stages of chemical reactions.

Researchers from MIT have used machine learning to expedite the calculation of transient molecular states that occur during chemical reactions. The team's innovative new model streamlines the process, from a previously time-consuming task, performed using quantum chemistry techniques, to a few seconds. Applied, it could assist chemists to design new reactions and catalysts to create…

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MIT scientists utilize AI to discover a fresh category of potential antibiotics.

Using artificial intelligence (AI) technology called deep learning, MIT researchers have identified compounds capable of defeating methicillin-resistant Staphylococcus aureus (MRSA), a drug-resistant bacterium causing over 10,000 deaths annually in the US. The compounds, which exhibit low toxicity to human cells, were found to effectively kill MRSA in lab and mouse models, making them potential drug…

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Employing deep learning for imaging the Earth’s atmospheric boundary layer.

The planetary boundary layer (PBL), the lowest layer of the troposphere, significantly influences weather near the Earth's surface and holds the potential to enhance storm forecasting and improve climate projections. A research team from Lincoln Laboratory's Applied Space Systems Group has been studying the PBL with a focus on deploying machine learning for creating 3-D…

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This AI Article Investigates the Core Elements of Reinforcement Learning through Human Feedback (RLHF): Endeavoring to Elucidate its Processes and Constraints.

Large language models (LLMs) are used across different sectors such as technology, healthcare, finance, and education, and are instrumental in transforming stable workflows in these areas. An approach called Reinforcement Learning from Human Feedback (RLHF) is often applied to fine-tune these models. RLHF uses human feedback to tackle Reinforcement Learning (RL) issues such as simulated…

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