A useful panorama on the 7 artificial intelligence research organizations which prones regulation around AI.
Among which the Ethical AI: Partnership on AI to benefit People and Society created by Google, Amazon, Facebook, IBM, Microsoft and many others.
Here are a few glimpses about how people imagine Portfolio Project Management with Artificial Intelligence:
Presentation by Raman Sharma, Senior Product Manager at Microsoft (
Can Project Manager maintain really complex projects schedule in his head?
Project Management requires more collaboration these days, but not everyone has the same level of knowledge or specialized skill in Project Management.
Presentation by Khaled Hamdy:
Algorithms are as good and performant as the data they were fed. And data fed are reflective of the reasoning of the engineering teams. Here is a testimonial of how this discovery was shocking and how Joy intends to makes algorithms less biased. Good watch!
Amazon Web Services, the company’s cloud-computing division, will offer affordable tools so clients can incorporate artificial intelligence and machine learning into their own operations. Such tools have already been used by to detect diseases and increase crop yields, Bezos wrote.
How Amazon uses AI to drive its growth?
“But much of what we do with machine learning happens beneath the surface,” he wrote. “Machine learning drives our algorithms for demand forecasting, product search ranking, product and deals recommendations, merchandising placements, fraud detection, translations, and much more. Though less visible, much of the impact of machine learning will be of this type — quietly but meaningfully improving core operations.”
“Watch this space,” Bezos said. “Much more to come.”
This is a great serie of lecture about NLP which is given by Stanford.
Natural Language Processing with Deep Learning
– Chris Manning
– Richard Socher
Natural language processing (NLP) deals with the key artificial intelligence technology of understanding complex human language communication. This lecture series provides a thorough introduction to the cutting-edge research in deep learning applied to NLP, an approach that has recently obtained very high performance across many different NLP tasks including question answering and machine translation. It emphasizes how to implement, train, debug, visualize, and design neural network models, covering the main technologies of word vectors, feed-forward models, recurrent neural networks, recursive neural networks, convolutional neural networks, and recent models involving a memory component.