Researchers demonstrate that misleading text in the real-world environment can hijack the decision-making of embodied AI ...

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...

We’re witnessing a collision between AI’s growing sophistication and natural intelligence’s vulnerabilities, which leads to ...

HybridLeg robots Olaf and Snogie use impact-safe design and self-recovery to enable scalable, real-world hardware ...

Class Disrupted guest Irina Jurenka on large language models in education: ‘The stakes are so much higher in learning than in other use cases.’ ...

To help professionals build these capabilities, we have curated a list of the best applied AI and data science courses.

The ability of computers to learn on their own by using data is known as machine learning. It is closely related to ...

An Ensemble Learning Tool for Land Use Land Cover Classification Using Google Alpha Earth Foundations Satellite Embeddings ...

You read the “AI-ready SOC pillars” blog, but you still see a lot of this:Bungled AI SOC transitionHow do we do better?Let’s go through all 5 pillars aka readiness dimensions and see what we can ...

Agnik, the global leader of the vehicle analytics market, announced today that it is going to offer a wide range of Deep Machine Learning-based solutions for powering its new and existing products in ...

The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...

Introduction: Why Data Quality Is Harder Than Ever Data quality has always been important, but in today’s world of ...