Reasoning about spatial data is a key task in many applications, including geographic information systems, meteorological and fluid-flow analysis, computer-aided design, and protein structure databases. Such applications often require the identification and manipulation of qualitative spatial representations, for example, to detect whether one object will soon occlude another in a digital image or efficiently determine relationships between a proposed road and wetland regions in a geographic data set. Qualitative spatial reasoning (QSR) provides representational primitives (a spatial "vocabulary") and inference mechanisms for these tasks. This article first reviews representative work on QSR for data-poor scenarios, where the goal is to design representations that can answer qualitative queries without much numeric information. It then turns to the data-rich case, where the goal is to derive and manipulate qualitative spatial representations that efficiently and correctly abstract important spatial aspects of the underlying data for use in subsequent tasks.

NEW YORK – Why did you splurge on that new pair of shoes? More and more advertisers are trying to tap into the unconscious to divine the invisible forces that drive those spending decisions. Using gadgets to track eye movements, computer maps of faces to capture a momentary grin (approval) or squint (anger), and sensors to measure perspiration or monitor brain activity, companies are mining consumers' raw emotions for information. Ad firms have traditionally measured the success of their campaigns through consumer surveys, but that technique has its limits. "It's not that people won't tell you, they actually can't tell you why they're making the decision they're making," said Jessica Azoulay, vice president of the market intelligence practice at Isobar, a digital marketing agency.

Before voice assistants like Apple's Siri and Amazon's Alexa gained relevancy, Will Underwood and Jarrod Wolf were researching semantic search and realized a lot could be done with natural-language search by taking the words humans use on a daily basis and making them comprehensible to a machine. By analyzing reviews and ratings, AddStructure can better help users find what they're looking for based on what they're researching or requesting at any given moment, along with what they've asked about in the past. While many agencies are beginning to build voice skills for Amazon and Google devices, building custom products provides more autonomy than they have with Alexa's parent company, Amazon. In the third quarter of this year, Strike Social will start offering a new AI service to help clients buy digital media in a way that the company's co-founder, Patrick McKenna, says will make buying across YouTube and other platforms faster, cheaper and smarter.

With Google, Microsoft and Facebook all pushing artificial intelligence, AI is becoming the next battleground for agencies, perpetually on the hunt for new service lines. AI basically gives machines the ability to think like humans. A simple example: You can have a one-on-one conversation with another person, but AI can talk to 500 people at the same time and make decisions based on real-time data to learn what's going on in each conversation, explained Dave Meeker, vp of Isobar's U.S. operations. In the context of advertising and marketing, AI theoretically means more personalized and interactive consumer experience, including targeted programmatic ad buys, identification of site visitors' decision-making patterns, conversational commerce like bots, as well as smarter search and recommendation engines on websites, according to six agency executives interviewed for this article. At the moment, with the help of AI developed by big tech companies, agencies are able to serve cognitive ads and integrate voice-activated assistants in their campaigns.

With Google, Microsoft and Facebook all pushing artificial intelligence, AI is becoming the next battleground for agencies, perpetually on the hunt for new service lines. AI basically gives machines the ability to think like humans. A simple example: You can have a one-on-one conversation with another person, but AI can talk to 500 people at the same time and make decisions based on real-time data to learn what's going on in each conversation, explained Dave Meeker, vp of Isobar's U.S. operations. In the context of advertising and marketing, AI theoretically means more personalized and interactive consumer experience, including targeted programmatic ad buys, identification of site visitors' decision-making patterns, conversational commerce like bots, as well as smarter search and recommendation engines on websites, according to six agency executives interviewed for this article. At the moment, with the help of AI developed by big tech companies, agencies are able to serve cognitive ads and integrate voice-activated assistants in their campaigns.