Chances are, you're already hip-deep in machine-learning applications. It's how Google Photo organizes those pictures from your vacation in Spain. It's how Facebook suggests tags for the pictures you took at last week's soccer match. It's how the cars of nearly every major automaker can help you avoid unsafe lane changes. Machine learning – which enables a computer to learn without new programming – is exploding in its ability to handle highly complex tasks.

Preeti Rathi is a Principal at Ignition Partners.

Classification Learner lets you perform common supervised learning tasks such as interactively exploring your data, selecting features, specifying validation schemes, training models, and assessing results. You can export classification models to the MATLAB workspace, or generate MATLAB code to integrate models into applications.

MACHINE-LEARNING is beginning to shake up finance. A subset of artificial intelligence (AI) that excels at finding patterns and making predictions, it used to be the preserve of technology firms. The financial industry has jumped on the bandwagon. To cite just a few examples, "heads of machine-learning" can be found at PwC, a consultancy and auditing firm, at JP Morgan Chase, a large bank, and at Man GLG, a hedge-fund manager. From 2019, anyone seeking to become a "chartered financial analyst", a sought-after distinction in the industry, will need AI expertise to pass his exams.

The biggest hardware and software arrival since the iPad in 2010 has been Amazon's Echo voice-controlled intelligent speaker, powered by its Alexa software assistant. But just because you're not seeing amazing new consumer tech products on Amazon, in the app stores, or at the Apple Store or Best Buy, that doesn't mean the tech revolution is stuck or stopped. They are: Artificial intelligence / machine learning, augmented reality, virtual reality, robotics and drones, smart homes, self-driving cars, and digital health / wearables. Google has changed its entire corporate mission to be "AI first" and, with Google Home and Google Assistant, to perform tasks via voice commands and eventually hold real, unstructured conversations.

Leaders of two South Dade cities have a warning for Miami-Dade Mayor Carlos Gimenez: Don't try to convince us to wait for driverless cars when we've been promised a new rail line. The mayors of Cutler Bay and Palmetto Bay wrote Gimenez this week to protest what they claim was a major reversal during a private May 15 meeting on the county's multi-billion-dollar plan to expand rail countywide. Instead of extending Metrorail south to Florida City, Gimenez reportedly floated the idea of using high-tech buses as a transition to a transportation revolution: the arrival of autonomous cars and their ability to revolutionize highway travel. "If the county's plan is to abandon what has been promised by way of the SMART plan, then it is only fair that we let the residents know now," read the May 22 letter from Peggy Bell, the mayor of Cutler Bay, and Eugene Flinn, Palmetto Bay's mayor. "However, we want to make it clear that our position has not changed and that we feel that the County is breaking another promise made to the residents which will undoubtedly shake the trust of its constituency."

Let's apply some natural intelligence to the concept of artificial intelligence. AI has been conflated with big data, machine learning and neural networks. AI is also second only to blockchain technology as the most overused and overhyped term referring to technologies that are taking over banking and finance, particularly in credit decisions. Three years ago, it was fashionable to just nod your head when a company founder or a conference panelist stated that AI and fintech will disrupt the banks; some entrepreneurs even went so far as to state that banks were already obsolete. The founders believed then as they do now that AI is the main component of the disruption.

Addressing thousands of developers at the annual Google I/O conference on Wednesday, Google CEO Sundar Pichai outlined the company's new strategy to transition from mobile first to artificial intelligence and machine learning. The goal is to equip the company's line of digital assistant products and services to anticipate the needs of users, and comprehend sights and sounds in ways never before possible on a massive scale. Google's deep learning and computer vision capabilities have advanced dramatically, according to Pichai, and now impact everything from cloud computing to Gmail, search and mobile devices. "We spoke last year about this important shift in computing from mobile first to AI first," Pichai recalled. "Similarly, in the AI-first world, we're rethinking all our products and applying AI and machine learning to solve human problems."

Datavail just released a white paper on the Top 10 Trends in Database Administration for the coming decade. The white paper is based on global surveys of hundreds of IT managers and input from Datavail's hundreds of DBAs. The paper predicts a new kind of IT arising from cloud computing, artificial intelligence, and mobile devices -- an IT that is "instant, invisible, and intelligent." This post looks at some of the findings from the Datavail white paper related to machine intelligence. With the Internet of Things (IoT) creating billions of information trails as data is exchanged between devices, Big Data is going to get much, much bigger.

In this video, students learn how we make robot joints move to the angles or positions that are required to achieve the desired end-effector motion. This is the job of the robot's joint controller. In the lecture, we will take discuss the realms of control theory.