The current machine learning training and testing process is not rigorous enough to ensure that the models being trained will work in the real world.
Artificial intelligence is getting more expensive to develop , and the cost is growing faster than the energy efficiency of the models.
lal is a lightweight Service composition and execution language that is tailored towards the requirements of mobile infrastructures.
A team of researchers from Intel, MIT and Georgia Tech has published a tool that has the potential of helping developers to write code automatically.
It has become very expensive to train modern networks; in fact it has become so expensive, that some companies are choosing not to use AI methods at all.
If you want to take a deep dive into AI and ethics, go to AI Ethics Reading | AI Truth.org for an overview of critical surveys, papers, books from AI experts. It’s definitely worth checking out :-). Photo by h heyerlein on Unsplash
Humans are almost hardwired to recognize faces. It’s important for us to tell people apart and we barely think about it.
If you look at AI from a purely business point of view, Alphabet’s DeepMind last year’s loss of $572 million should make you worry.
The Activity Centric Computing paradigm adresses information management challenges that at the core of the application centric computing paradigm. Activity-Centric Computing Systems from CACM on Vimeo. Photo by Steve Johnson from Pexels Source: Activity-Centric Computing Systems | August 2019 | Communications of the ACM
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