The rise of the AI gig workforce has driven an important shift from commodity task execution to first-tier crowd contribution ...

New agentic tools, medication management advances, medical device guidance and the "great tech reckoning" were among just ...

It is a great example of aphoristic intelligence at work. It makes us reconsider what we’re doing, or not doing, with our ...

AI (Artificial Intelligence) is a broad concept and its goal is to create intelligent systems whereas Machine Learning is a specific approach to reach the same goal.

In recent years, power consumption by machine learning technologies, represented by deep learning and generative artificial ...

Find out how AI will evolve in 2026 to be an even larger partner in numerous tasks, in all types of industries.

As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models ...

For years, the artificial intelligence industry has followed a simple, brutal rule: bigger is better. We trained models on ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

Taken together, these signals suggest one thing: we may be closer to AGI—and to systems capable of passing the Turing ...

Vangalapat led the development of a comprehensive MLOps infrastructure at Broadridge, building CI/CD pipelines, automated ...

AI in 2025 shifted from hype to economics, defined by compute, energy, infrastructure limits, enterprise adoption, and ...