In this work, we particularly focus on the complex relationship between land-use and transport offering an innovative approach to the problem by using land-use features at two differing levels of granularity (the more general land-use sector types and the more granular amenity structures) to evaluate their impact on public transit ridership in both time and space. To quantify the interdependencies, we explored three machine learning models and demonstrate that the decision tree model performs best in terms of overall performance--good predictive accuracy, generality, computational efficiency, and "interpretability". We then demonstrate how the developed framework can be applied to urban planning for transit-oriented development by exploring practicable scenarios based on Singapore's urban plan toward 2030, which includes the development of "regional centers" (RCs) across the city-state. This trend, on the other hand, eventually reverses (particularly during peak hours) with continued strategic increase in amenities; a tipping point at 55% increase is identified where ridership begins to decline and at 110%, the predicted ridership begins to fall below current levels.

But with the rollout of iOS 10, Apple will begin using differential privacy to collect and analyze user data from its keyboard, Spotlight, and Notes. Roth is a computer science professor who has quite literally written the book on differential privacy (it's titled Algorithmic Foundations of Differential Privacy) and Federighi said Roth described Apple's work on differential privacy as "groundbreaking." Differential privacy builds on the introduction of deep linking in iOS 9 to improve Spotlight search. Although iOS 10 will only use differential privacy to improve the keyboard, deep linking, and Notes, Smith points out that Apple may use the strategy in maps, voice recognition, and other features if it proves successful.

"AI is a magnitude more complex than machine learning," states Pamela Pecs Cytron, CEO of Pendo Systems. MS Excel spreadsheets are generally referred to as "Unstructured Data," with "Structured Data" being traditional databases. This breakthrough solution liberates both structured and unstructured data and enables business users to quickly get the insights needed to make business decisions and take action. Pendo Systems is a financial technology company providing an important technology solution to a major problem in today's financial services industry: lack of transparency and disparate data.

Retailers and technology firms are experimenting with chatbots, powered by a combination of machine learning, natural language processing, and live operators, to provide customer service, sales support, and other commerce-related functions. The company first integrated peer-to-peer payments into Messenger in 2015 and then launched a full chatbot API so businesses can create interactions for customers to occur within the Facebook Messenger app. While the most common uses of the device include playing music, making informational queries, and controlling home devices, Alexa (the device's default addressable name) can also tap into Amazon's full product catalog as well as your order history and intelligently carry out commands to buy stuff. Through Amazon's developer platform for the Echo (called Alexa Skills), developers can develop "skills" for Alexa that enable her to carry out new types of tasks.

That is exactly what Forrester wants to find out - is there something behind the artificial intelligence and cognitive computing hype? AI and cognitive computing have captured the imagination and interest of organization large and small but does anyone really know how to bring this new capability in and get value from it? It is time to roll-up the sleeves and look beyond conversations, vendor pitches and media coverage to really define what AI and cognitive computing mean for businesses, are businesses ready, where they will invest, and who they will turn to to build these innovated solutions, and what benefits will result. As such, Forrester launched its Global Artificial Intelligence Survey and is reaching out to you - executives, data scientists, data analysts, developers, architects and researchers - to put a finger on the pulse.

The company this morning unveiled Tetration Analytics, which it said is designed to gather "telemetry from hardware and software sensors, and then analyse the information using advanced machine learning techniques". However, it is being heavily promoted as a kind of "time machine" for the data centre. "This is a good sign for Cisco Tetration," Warrilow said. Gartner sees Tetration occupying a space in a broader market Gartner calls IT operations analytics (ITOA).

Aerial drones get all the attention, but a new terrestrial drone named the Pegasus:Multiscope is an autonomous treaded vehicle that its makers call "the first unmanned ground vehicle (UGV) for off-road use." Use cases for the Pegasus:Multiscope include surveying challenging terrain for civil engineering projects or agriculture, or in hazardous areas such as near nuclear power stations or in conflict zones. The UGV's treads reduce ground pressure at any one point, allowing the vehicle, which weighs just under 2000 pounds, to traverse any type of terrain, including mud, sand or snow. Contractor Oshkosh Defense designs solutions to turn existing military vehicles into UGV.

Giving up control and selling the sales team represent some of the biggest challenges to implementing machine learning into email marketing. Or so say Jennifer Muse, Senior Director, Email Product Marketing, Lifescript Jon Weiss, Director, Email Marketing Operations, Sirius XM Radio Inc.to moderator Chris Marriott, Senior Vice President of Strategic Partnerships, CertainSource at last week's Email Insider Summit. For the complete video of this and other sessions from MediaPost's Email Insider Summit, go to the event agenda.

Now, researchers from Google DeepMind and Stanford University have updated a theory originally developed to explain how humans and other animals learn. "The evidence seems compelling that the brain has these two kinds of learning systems, and the complementary learning systems theory explains how they complement each other to provide a powerful solution to a key learning problem that faces the brain," explained James McClelland, lead author of the 1995 paper from Stanford University. Components of the neural network architecture that succeeded in achieving human-level performance in a variety of computer games like Space Invaders and Breakout were inspired by complementary learning systems theory. According to DeepMind co-founder Demis Hassabis, "the extended version of the complementary learning systems theory is likely to continue to provide a framework for future research not only in neuroscience but also in the quest to develop Artificial General Intelligence -- our goal at Google DeepMind."

In my opinion, the marriage of the leading professional social network and the world's largest software company demonstrates that we are decidedly at the start of a new era in software, where proprietary data is king, and will start to come bundled together with software. We've seen this rise in the consumer realm, where technology companies are fundamentally aggregating and analyzing user behavior, and providing value back to users (and, of course, advertisers.) There are countless other examples that also demonstrate that consumer technology puts behavioral and user data front and center, in a way that I expect we will start to see from the enterprise as the divide between these two segments starts to collapse. Taken together, this demonstrates that proven machine learning algorithms have both the horsepower and access to granular datasets that are unprecedented.