If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
A "high-tech robot" praised on Russian TV was actually a man in wearing a costume. No one said the "most modern robot" at a Russian technology event was a real robot, but it appears no one said it wasn't either. So, some journalists covering the state-sponsored event for children had a lot of questions when Robot Boris appeared on stage talking and dancing. He also could answer math equations. Coverage on Russian state TV praised the "hi-tech robot" at the annual Proyektoria technology forum, The Guardian reports, even praising its intelligent dance moves.
For all the talk about data fueling digital transformation, it would seem the world remains in a strange limbo where a few companies embrace this concept. Many continue to be slow followers, while others are not yet familiar with the idea. A new report from Gartner, titled Applied Infonomics: Seven Steps to Monetize Available Information Assets (Nov 2018) shows top performers are more than twice as likely as typical performers to have monetized information assets, and eight times more likely to have done so than trailing organizations. From my experience over the past 20 years in analytics and data management, the main challenge for those companies in the middle and those that are laggards is that they generally lack the vision of what could be done differently from their traditional information processes. They are waiting for vendors to bring their best practices, use cases and ideas.
The Azure Machine Learning service speeds up the process of identifying useful algorithms and machine learning pipelines, which automates model selection and tuning. This can cut development time from days to hours, said Bharat Sandhu, director of product marketing, big data and analytics at Microsoft. It also provides DevOps capabilities, via integrated CI/CD tooling, to enable experiment tracking and manage machine learning models deployed in the cloud and on the edge, said Venky Veeraraghavan, group program manager for Microsoft Azure, in a blog post. The Azure Machine Learning service supports popular open source frameworks, including PyTorch, TensorFlow and scikit-learn, so developers and data scientists can use familiar tools. Developers can use Visual Studio Code, Visual Studio, PyCharm, Azure Databricks notebooks or Jupyter notebooks to build apps that use the service.