Before going to the world of integration, machine learning, etc., I would like to discuss with all of you about a scenario many of you might experience when you live in a mega city. I lived in the London suburbs for almost 2 years (and it's a city quite close to my heart too), so let me use London as this story's background. When I moved to London, one question which came to my mind was whether I should buy a car or not. The public transport system in London is quite dense and amazing (Oh!!! I just love the amazing London Underground and I miss it in Toronto).

Artificial Intelligence is rewriting the rules of economics, but is also bounded by that same economics. This is a long article, even by my standards. It represents my thinking about the implications of artificial intelligence on the economy, beyond the normal cheerleading that seems to so frequently accompany discussion of topic. Feel free to respond to me at kurt.cagle@gmail.com Artificial intelligence, the use of computer processes to infer and make decisions on information about the world that is not necessarily explicitly given, has been a hallmark of much of this decade. From word processors that went from simple spell check to office suites that now have a significant hand in the production process, from cruise control to self-driving vehicles, from halting speech recognition software to fully integrated video/audio concept recognition, AI and its related technologies have quietly but perhaps irrevocably changed our relationship with computers far more than most people realize. Yet as the information revolution continues, the impacts that it is having upon our economy are now reaching an extent where most of the models that economists have formulated about how that economy works are being thrown out. We're in terra incognita at this stage, and this, in turn, is forcing politicians, policy makers, economists, business leaders and everyday people to rethink many of the fundamental assumptions on which we base our notions of work, value and utility. Almost everything that deals with intellectual property has gone digital in the last three decades, as we move from an environment where not only are the physical products that used to convey that IP - from novels to newspapers to movies to music no longer require the physical media to transport content, but increasingly IP being produced today cannot be transcribed back to physical media.

But attempting to model an intelligence after either the ephemeral human mind or the exact physical structure of the brain (rather than iterating increasingly capable Roombas) is no small task -- and with no small amount of competing hypotheses and models to boot. In fact, a 2010 survey of the field found more than two dozen such cognitive architectures actively being studied. The current state of AGI research is "a very complex question without a clear answer," Paul S. Rosenbloom, professor of computer science at USC and developer of the Sigma architecture, told Engadget. "There's the field that calls itself AGI which is a fairly recent field that's trying to define itself in contrast to traditional AI." That is, "traditional AI" in this sense is the narrow, single process AI we see around us in our digital assistants and floor-scrubbing maid-bots.

AdMobilize, headquartered in Miami, FL with offices in London, UK, Bogota, Colombia, Sao Paulo, Brazil is a venture-backed AI company with seamless solutions for implementing advanced computer vision technologies in the brick and mortar world. The company has one clear mission; connecting the physical world to the online grid. Our "drop in" solutions yield to each customer's hardware/software needs. AdMobilize's suite of analytics and engagement products are designed to be "Plug and Measure", enabling real-time audience analytics and intelligence to be instantly activated at scale on any software/hardware platform. AdMobilize offers the industry's most complete and accurate analytics/engagement solution for digital signage, OOH, DOOH, retail, live events, small business, malls, restaurants, and beyond.

Artificial Intelligence and Machine Learning are two of some of the most commonly uttered buzzwords in tech circles; while the former is familiar to a layman, thanks to the deluge of science fiction movies and books that have become a part of our pop-culture, the latter is something of a jargon. Although, both Artificial Intelligence (AI) and Machine Learning (ML) are closely associated terms and are often used interchangeably, there exist distinct differences. For a quick overview of its history, the idea of a machine doing human's work has existed for millennia, beginning from mythologies (Talos of Crete). The earliest European computers were modelled as logical machines that mimicked a human brain. Since then, technology and computers have come a long way.

A conquering army wants to take a major city but doesn't want troops to get bogged down in door-to-door fighting as they fan out across the urban area. Instead, it sends in a flock of thousands of small drones, with simple instructions: Shoot everyone holding a weapon. A few hours later, the city is safe for the invaders to enter. This sounds like something out of a science fiction movie. But the technology to make it happen is mostly available today -- and militaries worldwide seem interested in developing it. Experts in machine learning and military technology say it would be technologically straightforward to build robots that make decisions about whom to target and kill without a "human in the loop" -- that is, with no person involved at any point between identifying a target and killing them.

A team of researchers from Carnegie Mellon University, in collaboration with the University of Minnesota, has made a breakthrough that could benefit paralyzed patients and those with movement disorders. Using a noninvasive brain-computer interface (BCI), scientists have developed the first successful mind-controlled robotic arm exhibiting the ability to continuously track and follow a computer cursor. BCIs have been shown to achieve good performance for controlling robotic devices using only the signals sensed from brain implants. When robotic devices can be controlled with high precision, they can be used to complete a variety of daily tasks. Until now, however, BCIs successful in continuously controlling robotic arms have used invasive brain implants.

We already knew an artificial intelligence could reflect the racial bias of its creator. But San Francisco thinks the tech could potentially do the opposite as well, by identifying and counteracting racial prejudice -- and it plans to put the theory to the test in a way that could change the legal system forever. On Wednesday, San Francisco District Attorney George Gascon announced that city prosecutors will begin using an AI-powered "bias-mitigation tool" created by Stanford University researchers on July 1. This could include their last name, eye color, hair color, or location. It also removes any information that might identify the law enforcement involved in the case, such as their badge number, a DA spokesperson told The Verge. Prosecutors will look at these redacted reports, record their decision on whether to charge a suspect, and then see the unredacted report before making their final charging decision.

Judging a book by its cover is not the way to go.. but I guess a summary should do just fine. In a world where internet is getting exploded with a hulking amount of data every day, being able to automatically summarize is an important challenge. Summaries of long documents, news articles, or even conversations can help us consume content faster and more efficiently. Automatic Text Summarization is a growing field in NLP and has been getting a lot of attention in the last few years. I will not be discussing specific details of any algorithm or implementation.

Fintech startup Active.ai, that delivers conversational banking through artificial intelligence (AI), has raised $3 million from Innocell, the venture capital arm of Spanish banking group Banco Sabadell, in an extension of its Series A funding round. With this, its total funding from the current round has touched over $11 million. Headquartered in Singapore, Active.ai raised $8.25 million in Series A back in November 2017, which was led by Vertex Ventures, with contributions from CreditEase, Dream Incubator, Kalaari Capital and IDG Ventures. The existing investors have contributed in this round too in order to retain their stakes. With this round of funding and partnership, Active.ai