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) …
Three MIT alumni have been awarded The Paul and Daisy Soros Fellowship for New Americans, a graduate school fellowship for outstanding immigrants and children of immigrants in the United States. Selected from 1,775 applicants, the 2017 fellows were chosen for their potential to make significant contributions to U.S. society, culture, or their academic field. Each will receive up to $90,000 in funding to support their graduate school studies. "At a time when the national conversation seems to be on what immigrants are taking away, we are putting the spotlight on what immigrants from diverse backgrounds contribute to the United States," said Craig Harwood, who directs the Soros Fellowship program. Born on the East Coast and raised in Madison, Wisconsin, Pratyusha Kalluri is the daughter of Indian immigrants.
The SETI Institute of Mountain View is inviting all citizen data scientists and technologists to join us as collaborators in our mission to find intelligent radio signals from beyond our solar system. We are issuing a worldwide, public code challenge and accompanying hackathon for the purpose of expanding our radio-telescope signal classification tools using the latest developments available in machine- and deep-learning. We are looking for signal classification algorithms and models that can accurately identify the various types of radio signals we observe each night. We have constructed a set of simulated signals (thus, they are a labeled training data set) that mimic our observations. A typical analysis approach begins with transforming these simulated data into two-dimensional images.
Smart home hubs are continuing to evolve, and Google just added a pretty important feature to its own hub, the Google Home. Previously, Home only linked up to the account of whomever set it up first. Now, the device will be able to handle multiple accounts and tell who's speaking to it, offering personalized answers to some questions. That's a feature that Amazon's Echo doesn't have. And it's important for a voice assistant that's designed to run your household.
Artificial intelligence will soon augment the number of physicians and nurses to provide health care to billions of people worldwide. Health care assistants in the form of mobile apps are now taking over some tasks of nurses and physicians. Currently, worldwide shortage of physicians and nurses has reached more than seven million. Filling the gap is difficult considering the amount of time and money needed to train physicians and nurses. The number of students taking nursing, medicine and other healthcare related courses had been dwindling in the past years.
Chances are, if you are searching for a tutorial on artificial neural networks (ANN) you already have some idea of what they are, and what they are capable of doing. But did you know that neural networks are the foundation of the new and exciting field of deep learning? Deep learning is the field of machine learning that is making many state-of-the-art advancements, from beating players at Go and Poker, to speeding up drug discovery and assisting self-driving cars. If these types of cutting edge applications excite you like they excite me, then you will be interesting in learning as much as you can about deep learning. However, that requires you to know quite a bit about how neural networks work. This tutorial article is designed to help you get up to speed in neural networks as quickly as possible. In this tutorial I'll be presenting some concepts, code and maths that will enable you to build and understand a simple neural network. Some tutorials focus only on the code and skip the maths – but this impedes understanding. I'll take things as slowly as possible, but it might help to brush up on your matrices and differentiation if you need to. The code will be in Python, so it will be beneficial if you have a basic understanding of how Python works. You'll pretty much get away with knowing about Python functions, loops and the basics of the numpy library. By the end of this neural networks tutorial you'll be able to build an ANN in Python that will correctly classify handwritten digits in images with a fair degree of accuracy. Once you're done with this tutorial, you can dive a little deeper with the following posts: All of the relevant code in this tutorial can be found here. Here's an outline of the tutorial, with links, so you can easily navigate to the parts you want: Artificial neural networks (ANNs) are software implementations of the neuronal structure of our brains. We don't need to talk about the complex biology of our brain structures, but suffice to say, the brain contains neurons which are kind of like organic switches.
This curated list comprises awesome resources, libraries, information sources about Machine Learning with the Ruby programming language. This list comes from our day to day work on ML Applications. Our main goal is to promote Ruby as a tool for NLP related tasks. Your help, suggestions and contributions are welcome! We kindly ask you to study the Contribution section.
While it's true that RPA doesn't require significant changes to technology platforms or infrastructure, some level of IT oversight is essential to ensure operational efficiency and security. For example, robotics tools need to be aligned to IT disaster recovery plans, system upgrades and password reset policies to avoid problems. In this regard, RPA presents a shadow IT threat similar to what many organizations have experienced with cloud computing. Over the longer term, by creating linkages between applications at the user interface level, RPA tools introduce changes to operational environments that, if not managed by IT, can complicate efforts to modernize existing systems, link platforms and drive digital transformation.
Tech advancements have been making life easier for years now -- especially on the road. From apps that save driving time to smart streets that track available parking, computer programs are helping streamline transit like never before. And now, thanks to ongoing developments in machine learning, artificial intelligence (AI) is taking convenient travel one step further. As I've written about recently, AI has become a major player in the auto industry. Current and in-development smart features include things like impact detection, self-driving programs, and built-in smart assistants.
NEW DELHI: Microsoft on Thursday announced several new products and services that will empower organisations to easily leverage data driven intelligence in their digital transformation journey. The next generation offerings include first relational database management system (RDBMS) with built-in Artificial Intelligence (AI), SQL Server 2017, Microsoft R Server 9.1 and neural network models, azure cognitive services and Cortana intelligence solution templates. "SQL Server 2017 will be the first version of SQL Server compatible with Windows, Linux and Docker containers. In addition to Windows Server, the new version will also run on Red Hat Enterprise Linux, SUSE Enterprise Linux Server and Ubuntu," the company said in a statement. Microsoft also announced Deep Learning and Machine Learning capabilities to support the next generation of enterprise-grade AI applications for developers and businesses, to create intelligent applications that drive new efficiencies, create better products and improve customer experiences.