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Artificial Intelligence

Investigating Offline Reinforcement Learning (RL): Providing Constructive Guidance for Particular Domain Professionals and Future Algorithm Construction.

Data-driven techniques, such as imitation and offline reinforcement learning (RL), that convert offline datasets into policies are seen as solutions to control problems across many fields. However, recent research has suggested that merely increasing expert data and finetuning imitation learning can often surpass offline RL, even if RL has access to abundant data. This finding…

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Researchers at New York University suggest the use of Inter- & Intra-Modality Modeling (I2M2) for multiple mode learning, emphasizing on both cross-modality and within-modality dependencies.

Researchers from New York University, Genentech, and CIFAR are pioneering a new approach to multi-modal learning in an attempt to improve its efficacy. Multi-modal learning involves using data from various sources to inform a target label, placing boundaries between the sources to allow for differentiation. This type of learning is commonly used in fields like…

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Researchers from NYU suggest the I2M2 approach for multi-modal learning which can capture both dependencies within and between different modalities.

Researchers from New York University, Genentech, and CIFAR have proposed a new paradigm to address inconsistencies in supervised multi-modal learning referred to as Inter & Intra-Modality Modeling (I2M2). Multi-modal learning is a critical facet of machine learning, used in autonomous vehicles, healthcare, and robotics, among other fields, where data from different modalities is mapped to…

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The MIT-Takeda Program concluded with 16 research papers, a patent, and almost 24 projects successfully completed.

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Protect a generative AI travel agent with proactive engineering and safety measures for Amazon Bedrock.

In recent years, the deployment of artificial intelligence (AI) in customer-facing roles has seen a significant increase, particularly in the use of large language models (LLMs) which engage in natural language conversations. This article focuses on the usage of AI in travel companies to create and operate virtual travel agents. These AI-powered assistants can handle…

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Enhancing air purity through the application of generative artificial intelligence.

Ghana, currently ranking as the 27th most polluted country in the world, is addressing its critical air pollution problem through technological solutions. This includes the adoption of low-cost air sensor technologies evaluated and supported by the Sensor Evaluation and Training Centre for West Africa (Afri-SET). Afri-SET aids governmental and civil societies in managing air pollution.…

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This Novel AI Instrument Has the Potential to Transform the Method We Uncover New Medicines

A revolutionary AI tool created by Australian researchers may dramatically accelerate the drug discovery process, offering a cheaper and more effective method. The tool, named PSICHIC (PhySIcoCHemICal), has been designed to predict the way in which molecules and proteins interact within the human body. Its use could significantly reform the early stages of drug discovery.…

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Enhancing Clinical Confidence: Fine-Tuning DPO Reduces Imaginary Findings in Radiology Reports, Transitioning from Illusions to Facts

The field of radiology has seen a transformative impact with the advent of generative vision-language models (VLMs), automating medical image interpretation and report generation. This innovative tech has shown potential in reducing radiologists’ workload and improving diagnostic accuracy. However, a challenge to this technology is its propensity to produce hallucinated content — text that is…

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