Two Minute Papers explores the paper “Animating Pictures with Eulerian Motion Fields” in this video.
Here is the inside story of the DeepMind team of scientists and engineers who created AlphaFold, an AI system that is recognized as a solution to “protein folding”, a grand scientific challenge for more than 50 years.
Join Henk Boelman. Amy Boyd and Seth Juarez to learn what is possible with AI on Azure.
Two Minute Papers examines the paper “Multimodal Neurons in Artificial Neural Networks.”
This video by Simplilearn on Artificial Intelligence is a full course that will help us understand the basics of artificial intelligence, top 10 applications of AI in 2021, and more.
NVIDIA CEO Jensen Huang delivers the #GTC21 keynote, where he introduced a number of amazing breakthroughs.
Noelle talks about how to avoid invoice fraud in the latest “This Week in Applied AI.”
Bhagvan Kommadi shows us the journey forward that Quantum Computing can take us.
Bhagvan Kommadi is also the Founder of Architect Corner – AI startup and has around 20 years’ experience in the industry, ranging from large scale enterprise development to helping incubate software product start-ups. Bhagvan Kommadi founded Quantica Computacao, the first quantum computing startup in India.
He discusses Quantum algorithms of the future that will have its dominance in every utility and application field while he also traces the evolution of Quantum Computing.
If you are looking to improve your skill set or steer business/research strategy in 2021, you most certainly have come across articles decrying a skills shortage in deep learning. Not that long ago, you would have read the same about a shortage of professionals with machine learning skills. In the earlier years of the 2010s, the emphasis would have been on a shortage of data scientists skilled in “big data.”
Andrew Ng telling us for years that “AI is the new electricity”, and the advent of AI in business and society is constantly suggested to have an impact similar to that of the industrial revolution. While warnings of skills shortages are arguably overblown, why do we seem to change our ideas about what skills are needed?
While job listings are notoriously whimsical, they can, in aggregate, tell a story.
If deep learning is a part of AI, why are there ~20% fewer jobs open for the latter? The answer is that the terms we use for these fields often have as much to do with trends and marketability as they do with any substantive differences. That’s not to say that we can’t differentiate the different categories based on technical characteristics, we’ll do that too!
Why do the “hot buzzords” change every few years and how do they relate to one another?
Kevin Powell answers a question that’s been on my mind lately: with the rise of low-code/no-code systems (along with AI), what will happen to UI designer jobs?