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When Artificial Intelligence Becomes Commonplace

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AI and computer learning is quickly gaining use, so what happens when AI becomes commonplace? Before we dive into this it is important to understand what AI can and can't do today and what aspect of it is already common. Computer learning is a subset of AI, but the two are often discussed together or interchanged. Computer learning is a method where a computer is trained on a set of data and then uses that training to learn a task. Facial feature recognition is a common computer learning task where the computer is trained to recognize the various features (eyes, lips, nose and mouth) of anyone's face.


An Intelligent Claims Process

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Artificial intelligence, Machine Learning, and Deep Learning are more than futuristic concepts. These technologies are impacting the insurance industry in a significant way right now and this impact is likely to increase in the near future. The idea of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) may fascinate consumers who enjoy talking to their digital while admiring a Nest thermostat. But for the insurance industry, these terms are business-changers that affect products and services offered and interactions with consumers and other industry partners. The definitions of these terms may be a bit confusing to the uninitiated (see sidebar).


Robocar Startup Drive.ai Gets Backing From Uber Rival Grab, Plans Singapore Move

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After announcing plans this month to supply self-driving vehicles for Lyft's ride-hailing network, the autonomous tech developer has scored financial backing from Southeast Asian rideshare powerhouse Grab and plans to expand into Singapore. Singapore office will study that market as a potential place to deploy vehicles equipped with its software and self-driving hardware kits in government and business fleets, Tandon said. Amid the rush by auto and tech firms to perfect robotic vehicles, Tandon and his co-founders, who were all researchers from Stanford University's Artificial Intelligence Lab, founded Drive.ai to specialize in deep learning-based driving software for business, government and shared vehicle fleets. Small relative to well-funded programs at Waymo, General Motors' Cruise, Uber's Advanced Technology Vehicle Group and Ford's Argo AI, Mountain View, California-based Drive.ai has made quick progress.


Machine learning and data are fueling a new kind of car, brought to you by Intel

@machinelearnbot

The automobile is being dismantled, reimagined, and rebuilt in Silicon Valley. Intel's proposed $15.3 billion acquisition of Mobileye, an Israeli company that supplies carmakers with a computer-vision technology and advanced driver assistance systems, offers a chance to measure the scale of this rebuild. In particular, it shows how valuable on-the-road data is likely to be in the evolution of automated driving. While the price tag might seem steep, especially with so many players in automated driving today, Mobileye has some key technological strengths and strategic advantages. It's also developing new technologies that could help solidify this position.


Is Facebook Building An Autonomous Car?

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Facebook seems to have a strategy of leveraging its capabilities in social marketing, AR & VR and interestingly, who would have thought of it, leveraging its advanced AI and deep learning capabilities to support the development of autonomous vehicles. Potential car buyers spend anywhere between 30 to 50 minutes every day on Facebook and that has helped the social business make significant inroads in digital prospecting and omni-channel commerce. Facebook believes that car companies are focusing more on the connected car, rather than the connected consumer. With every new customer car buying journey now beginning online, it is possible through Facebook's huge data on a customer's social behavior, to make that experience personalized and completely customized.


Machine Learning at HPC User Forum: Drilling into Specific Use Cases

@machinelearnbot

Dr. Weng-Keen Wong from the NSF echoed much the same distinction between the specific and general case algorithm during his talk "Research in Deep Learning: A Perspective From NSF" and was also mentioned by Nvidia's Dale Southard during the disruptive technology panel. Tim Barr's (Cray) "Perspectives on HPC-Enabled AI" showed how Cray's HPC technologies can be leveraged for Machine and Deep Learning for vision, speech and language. Fresh off their integration of SGI technology into their technology stack, the talk not only highlighted the newer software platforms which the learning systems leverage, but demonstrated that HPE's portfolio of systems and experience in both HPC and hyper scale environments is impressive indeed. Stand-alone image recognition is really cool, but as expounded upon above, the true benefit from deep learning is having an integrated workflow where data sources are ingested by a general purpose deep learning platform with outcomes that benefit business, industry and academia.


New NHTSA Robocar regulations are a major, but positive, reversal

Robohub

The proposed regulations preempt state regulation of vehicle design, and allow companies to apply for high volume exemptions from the standards that exist for human-driven cars. There is a new research area known as "explainable AI" which hopes to bridge this gap and make it possible to document and understand why machine learning systems operate as they do. The most interesting proposal in the prior document was a requirement for public sharing of incident and crash data so that all teams could learn from every problem any team encounters. The new document calls for a standard data format, and makes general motherhood calls for storing data in a crash, something everybody already does.


Drones and Robots Are Taking Over Industrial Inspection

MIT Technology Review

The effort shows how low-cost drones and robotic systems--combined with rapid advances in machine learning--are making it possible to automate whole sectors of low-skill work. Avitas uses drones, wheeled robots, and autonomous underwater vehicles to collect images required for inspection from oil refineries, gas pipelines, coolant towers, and other equipment. Nvidia's system employs deep learning, an approach that involves training a very large simulated neural network to recognize patterns in data, and which has proven especially good for image processing. It is possible, for example, to train a deep neural network to automatically identify faults in a power line by feeding in thousands of previous examples.


Artificial Intelligence and Deep Learning Quotes - Supply Chain Today

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We are in the crawling stages of Artificial Intelligence and Deep Learning. So everyone is aware, Deep Learning is a subset of Machine Learning, and Machine Learning is a subset of Artificial Intelligence. Companies like Tesla, Uber, and Google are using Deep Learning to make self driving vehicles a reality. We hope you like the Artificial Intelligence and Deep Learning quotes.


New Google Street View Cameras Will Fuel AI Assistants

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Wired reports that the cameras Google uses to create imagery on its Street View service have gotten their first upgrade in eight years. Those units record images of stores, road signs, and other objects at the side of the road in incredible detail--and information gleaned from the data will feed Google's ever-hungry machine-learning algorithms. New 360-degree cameras allow users to upload their own panoramas to Street View, and the company hopes cities and other organizations may do the same to keep things fresh. All of that data will be indexed by Google's algorithms--so who knows, maybe one day, a handwritten "sorry we're closed today" sign might stop a wasted journey for a sandwich.