Recently, there has been a lot of hullabaloo about the idea that large reasoning models (LRM) are unable to think. This is ...

I created a kicker score to summarize both the season’s actual and predicted values into a single number. Each field goal made is worth one, and attempts are negatively weighted based on distance and ...

The rapid rise of AI data centers is testing the limits of the power grid, driving utilities to boost capital spending, overhaul tariffs, and build new flexibility into their systems to keep pace with ...

It seems like everyone wants to get an AI tool developed and deployed for their organization quickly—like yesterday. Several customers I’m working with are rapidly designing, building and testing ...

Google released a Model Context Protocol (MCP) server for Data Commons, exposing the project’s interconnected public datasets—census, health, climate, economics—through a standards-based interface ...

Large Language Models (LLMs) are recasting the relationship between humans & technology. There’s a complete transition in how we search, consume, and execute information on the web. LLMs are no longer ...

Abstract: Despite the remarkable success of end-to-end intelligent diagnosis methods, the shortage of available training data remains one of the most challenging issues in real industrial scenarios.

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator.

Want smarter insights in your inbox? Sign up for our weekly newsletters to get only what matters to enterprise AI, data, and security leaders. Subscribe Now Singapore-based AI startup Sapient ...

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...