[RB] Is studying AI in academia a waste of ti...

The brutal truth about why Silicon Valley is blowing billions on glorified autocomplete while pretending it's the next iPhone. We're diving deep into the AI investment circus where VCs who can't code are funding companies that barely understand their own technology. From blockcha ...  Show more

VortexNet uses actual whirlpools to build neural networks. Seriously. By borrowing equations from fluid dynamics, this new architecture might solve deep learning's toughest problems—from vanishing gradients to long-range dependencies. Today we explain how vortex shedding, the Str ...  Show more

The data science field is expanding because so many businesses and other institutions require skilled workers who can manage data as well as provide insights. Companies and students are clamoring for more academic programs. There is great need, but academic institutions are st ...

A 2021 EdScoop survey underwritten by Dell Technologies and Intel found that higher education officials believe the demand for AI training is outpacing both supply and the current ability of higher education institutions to meet that demand. Fifty-three percent of survey respo ...

About 10 years ago, Thomas Davenport & DJ Patil published the article "Data Scientist: The Sexiest Job of the 21st Century" in the Harvard Business Review. In this piece, they described the bourgeoning role of the data scientist and what it will mean for organizations and individ ...  Show more

Huiming Qu didn’t plan to work in data science, a nascent field at the time she was pursuing a Ph.D. in computer science, but one course in data mining changed all of that. She started her career in the research department at IBM, transitioned to a 50-person startup, spent some t ...  Show more