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) …
Do we really need an Alexa-powered toilet? Kitchen and bath products-maker Kohler thinks so, as well as a faucet and bathroom mirror and the list of Alexa-activated devices is even longer and weirder than that. Amazon was expected to get its voice-activated digital assistant into all manner of Internet-connected gadgets at CES 2018, the big annual technology trade show that wrapped up in Las Vegas last week. The list of new devices powered by Alexa rose to 4,000, from over 1,000 brands. Not to be outdone, Google made an unusual splash, showing off deals that put its Alexa rival, Google Assistant, in touchscreen displays and voice-activated commands in cars.
Intel recently released its BigDL project for distributed deep learning on Apache Spark. BigDL has native Spark integration, allowing it to leverage Spark during model training, prediction, and tuning. This blog post gives highlights of BigDL and a tutorial showing how to get started with BigDL on Databricks.
I once posted about making use of narrative objects. In this blog, I will be discussing an algorithm that supports the creation of these objects. I call it my "Infereferencing Algorithm": this term is most easily pronounced with a slight pause between "infer" and "referencing." I consider this a useful and widely applicable algorithm although I don't believe it operates well in a relational database environment. Instead, I use "mass data files": these contain unstructured lumps of symbols or tags.
We just open-sourced a project to create labeled datasets for ML on satellite imagery. There are only a handful of high quality satellite datasets out there, so our team built something to quickly/easily generate new ones. It pulls label information from OpenStreetMap and saves both the imagery and labels into numpy arrays for incorporation into ML workflows. You can filter by common tags in OSM like roads, buildings, railroads, etc., and it's able to package data for classification, object detection, or segmentation.
While you've been sleeping, artificial intelligence has been evolving. It isn't something to be afraid of -- yet. In actuality, AI has been present in numerous industries for a long time. As development improves and transforms, both with AI-based analytics, also referred to asdeep learning, and user feedback, AI is evolving from being the villain in a bad action movie to helping people live a better life through sleep and Health and wellness tracking.