A team of researchers has found a way to steer the output of large language models by manipulating specific concepts inside these models. The new method could lead to more reliable, more efficient, ...

A Purdue University digital forestry team has created a computational tool to obtain and analyze urban tree inventories on ...

The global economy is in the middle of a glow-up, and the fuel isn’t oil barrels or factory floors, it’s raw, restless data.

The emergence of AI and biosensors offers a chance to address inefficiencies in drug development.

Abstract: In today’s data-driven world, structuring unstructured data is crucial for efficient analysis and meaningful insights. This paper focuses on transforming unstructured text documents into a ...

Roughly 80% of enterprise data sits in emails, contracts, call transcripts, and PDFs where traditional databases can't touch it. Much of this "unstructured" data isn't ignored because it lacks value, ...

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 ...

Coastal zones face growing threats from climate change, including sea-level rise and intensified storm activity. Accurate numerical modelling is essential to predict the impacts of anthropogenic and ...

Enterprise AI has a data problem. Despite billions in investment and increasingly capable language models, most organizations still can't answer basic analytical questions about their document ...

Jesse Todd, CEO of EncompaaS, is a SaaS expert specializing in information management and risk mitigation for Fortune 500 companies. AI has the potential to transform how organizations operate, but ...

Abstract: Forecasting equity markets has traditionally relied on structured data sources, such as historical prices, fundamentals, and macroeconomic indicators. However, unstructured data, including ...