As major powers accelerate the military use of artificial intelligence, the consequences for countries that fail to adapt are ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

Artificial intelligence can be a beautiful thing for business, with a lot of promise. But this promise has yet to deliver tangible results. Many AI projects fail in various stages of experimentation ...

A University of Hawaiʻi at Mānoa student-led team has developed a new algorithm to help scientists determine direction in ...

AI’s biggest constraint isn’t algorithms anymore. It’s data…specifically, high-quality, forward-looking data. It is the “Rare ...

Extracting and analyzing relevant medical information from large-scale databases such as biobanks poses considerable challenges. To exploit such "big data," attempts have focused on large sampling ...

As computing power has increased and data science has expanded into nearly every area of our lives, we have entered the age of the algorithm. While our personal and professional data is being compiled ...

Building fast and highly performant data science applications requires an intimate knowledge of how data can be organized in a computer and how to efficiently perform operations such as sorting, ...

It is critical for manufacturers such as food processors to recognize that while AI has the potential to become the turbocharger of operations, that transformation rarely happens by simply bolting on ...

Through data, algorithms communicate with their environments and get to “know about” and “learn from” what is happening around them. Algorithms without living data are no more than sheer mathematical ...