Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results. In ...

Abstract: Reversible steganography enables recovery of the cover image from the stego image after extracting the hidden data, making it valuable for applications such as medical imaging, content ...

Master the art of visualizing histograms and normal distributions in Web VPython! This guide teaches you how to create dynamic, interactive 3D plots to enhance your data analysis and physics ...

Quantum communication is edging closer to reality thanks to a breakthrough in teleporting information between photons from different quantum dots—one of the biggest challenges in building a quantum ...

Artificial intelligence has developed rapidly in recent years, with tech companies investing billions of dollars in data centers to help train and run AI models. The expansion of data centers has ...

Abstract: In order to engage with large language models (LLMs) in a meaningful way, it is necessary to create prompts that are both instructive and precise. However, especially when working with ...

Leveraging Centralized Health System Data Management and Large Language Model–Based Data Preprocessing to Identify Predictors for Radiation Therapy Interruption This study presents a new method based ...

If you’d like an LLM to act more like a partner than a tool, Databot is an experimental alternative to querychat that also works in both R and Python. Databot is designed to analyze data you’ve ...

Web scraping powers pricing, SEO, security, AI, and research industries. AI scraping threatens site survival by bypassing traffic return. Companies fight back with licensing, paywalls, and crawler ...

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