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Machine learning

EuroCropsML: A Ready-for-Analysis Machine Learning Dataset for Time Ordered Crop-Type Identification using Remote Sensing across European Agricultural Plots

Remote sensing is a crucial and innovative technology that utilizes satellite and aerial sensor technologies for the detection and classification of objects on Earth. This technology plays a significant role in environmental monitoring, agricultural management, and natural resource conservation. It enables scientists to accumulate massive amounts of data over large geographical areas and timeframes, providing…

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To improve an AI assistant, initiate by simulating the unpredictable conduct of humans.

Researchers from MIT and the University of Washington have developed a computational model to predict human behavior while taking into account the suboptimal decisions humans often make due to computational constraints. The researchers believe such a model could help AI systems anticipate and counterbalance human-derived errors, enhancing the efficacy of AI-human collaboration. Suboptimal decision-making is characteristic…

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To create an improved AI assistant, begin by simulating the unpredictable actions of people.

Researchers at MIT and the University of Washington have successfully developed a model that can infer an agent's computational constraints from observing a few samples of their past actions. The findings could potentially enhance the ability of AI systems to collaborate more effectively with humans. The scientists found that human decision-making often deviates from optimal,…

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This miniature circuit can protect user information while facilitating effective calculations on a mobile phone.

A team of researchers from MIT and the MIT-IBM Watson AI Lab has developed a machine-learning accelerator that is resistant to the two most common types of cyberattacks. This ensures that sensitive information such as finance and health records remain private while still enabling large AI models to run efficiently on devices. The researchers targeted…

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For improving an AI assistant, begin with simulating the unpredictable tendencies of human beings.

MIT and University of Washington researchers have created a method to model both human and machine behaviours, taking into account unknown computational constraints which can limited problem-solving skills. The model infers an "inference budget" from previous actions. The inference budget can then predict the agent's future behaviour. Their technique can be used to predict navigation…

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This small microchip can protect user information while facilitating effective computation on a mobile phone.

Health-monitoring apps can help individuals manage chronic diseases and keep up with their fitness goals. However, these apps can often be slow and energy-inefficient due to the machine-learning models they use, which need a significant amount of data shuffling between the smartphone and a central memory server. Engineers typically use hardware (machine-learning accelerators) to streamline…

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This AI article from the Netherlands presents an AutoML structure engineered for effective creation of comprehensive multimodal machine learning ML pipelines.

Automated Machine Learning (AutoML) has become crucial for data-driven decision-making, enabling experts to utilize machine learning without needing extensive statistical knowledge. However, a key challenge faced by current AutoML systems is the efficient and correct handling of multimodal data, which can consume significant resources. Addressing this issue, scientists from the Eindhoven University of Technology have put…

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To construct an advanced AI assistant, initiate the process by imitating the erratic actions of humans.

Researchers at MIT and the University of Washington have developed a model that accounts for the sub-optimal decision-making processes in humans, potentially improving the way artificial intelligence can predict human behavior. Named 'inference budget,' the model infers an agent's computational constraints, whether human or machine, after observing a few traces of their past actions. It…

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This miniature microchip has the capability to protect user information while also enhancing the effectiveness of computations on a mobile device.

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Google Deepmind’s researchers have introduced BOND: An innovative RLHF method that refines the policy through online distilling of the top-N sampling distribution.

Reinforcement Learning from Human Feedback (RLHF) plays a pivotal role in ensuring the quality and safety of Large Language Models (LLMs), such as Gemini and GPT-4. However, RLHF poses significant challenges, including the risk of forgetting pre-trained knowledge and reward hacking. Existing practices to improve text quality involve choosing the best output from N-generated possibilities,…

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In order to improve an AI assistant, initiate by imitating the unpredictable actions of humans.

Researchers from MIT and the University of Washington have developed a method to model the behaviour of an agent, including its computational limitations, predicting future behaviours by examining prior actions. The method applies to both humans and AI, and has a wide range of potential applications, including predicting navigation goals from past routes and forecasting…

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