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Bots: What you need to know
The call for proposals for the O'Reilly Artificial Intelligence Conference, September 17-20, 2017, in San Francisco, is now open. "Bots are the new apps"--Satya Nadella, CEO of Microsoft Bots are a new, AI-driven way to interact with users in a variety of environments. As AI improves and users turn away from single-purpose apps and toward messaging interfaces, they could revolutionize customer service, productivity, and communication. Getting started with bots is as simple as using any of a handful of new bot platforms that aim to make bot creation easy; sophisticated bots require an understanding of natural language processing (NLP) and other areas of artificial intelligence. Since late 2015, bots have been the subject of immense excitement in the belief that they might replace mobile apps for many tasks and provide a flexible and natural interface for sophisticated AI technology.
Artificial Intelligence and Additive Manufacturing to Transform the Supply Chain Process, Reports SpendEdge
LONDON--(BUSINESS WIRE)--Artificial intelligence and additive manufacturing or 3D printing are emerging technologies that have a huge potential in a variety of industries and applications. Despite both technologies being fairly new, particularly 3D printing, procurement market intelligence experts at SpendEdge state that these technologies have several applications in the supply chain for addressing procurement challenges, and will very soon become an integral part due to its improved and sophisticated functionalities. Rapid prototyping is one of the most common uses of additive manufacturing. Since designing a successful product can be very expensive and time-consuming, 3D printed prototyping makes it quite simple at the same time shortens the manufacturing cycle. The impact of AM on supply chain is massive, some of which include increased manufacturing flexibility, reduced material waste, and the ability to employ decentralized manufacturing strategies.
Google uses AI to help diagnose breast cancer
Google announced Friday that it has achieved state-of-the-art results in using artificial intelligence to identify breast cancer. The findings are a reminder of the rapid advances in artificial intelligence, and its potential to improve global health. Google used a flavor of artificial intelligence called deep learning to analyze thousands of slides of cancer cells provided by a Dutch university. Deep learning is where computers are taught to recognize patterns in huge data sets. With 230,000 new cases of breast cancer every year in the United States, Google (GOOGL, Tech30) hopes its technology will help pathologists better treat patients.
The Era of Machine Learning (ML), Artificial Intelligence (AI), Robotics and Internet of Things (IoT) is Here.
Machine Learning (ML) has revolutionized the world of computers by allowing them to learn as they progress forward with large datasets, thus mitigating many previous programming pitfalls and impasses. Machine Learning builds algorithms, which when exposed to high volumes of data, can self-teach and evolve. When this unique technology powers Artificial Intelligence (AI) applications, the combination can be powerful. We can soon expect to see smart robots around us doing all our jobs โ much quicker, much more accurately, and even improving themselves at every step. Will this world need intelligent humans anymore or shall we soon be outclassed by self-thinking robots? What are the most visible 2017 Machine Learning trends?
Google and IBM: We Want Artificial Intelligence to Help You, Not Replace You
In an era of maturing artificial intelligence technology, what does the future of the corporation look like? Will the rise of robots help us do our jobs better, or harm them? This dynamic has become a mainstay of the dialogue around AI, with voices from technology visionaries such as Bill Gates and Stephen Hawking weighing in. But at Fortune's Most Powerful Women International Summit in Hong Kong on Tuesday, leaders at two of the world's most powerful tech giants pushed back on those concerns. AI is intended to help--not hinder--the human workforce, they said.
IBM Watson Created a Modern Sculpture Inspired by the Work of One of Spain's Most Famous Architects
BARCELONA, Spain--IBM has come up with a way to show off the more artistic side of its artificial intelligence capabilities while honoring one of Spain's most famous architects. For this year's Mobile World Congress in Barcelona, IBM tasked its Watson super computer with the understanding Antoni Gaudรญ's greatest works such as La Pedrera and la Sagrada Famรญlia to help create a unique sculpture for the annual trade show. Using its visual-recognition technology, Watson reviewed hundreds of images of Gaudรญ's buildings, along with additional examples of local architecture to understand trends in composition and inspirations. IBM then tapped Watson's AlchemyLanguage software to read documents about Gaudรญ and other architects, along with song lyrics and other documents about the city's history and culture. "What we were really trying to do at the essence was figure out if we can programmatically start to understand what the features of a particular style or architect are," said Jeff Arn, a Watson manager at IBM. Watson identified key elements of Gaudรญ's Catalan modernist style--known for its dream-like colors and shapes and odes to the natural world.
Why no job is safe from the rise of the robots
The highly intelligent machines that will be unleashed in the near future won't be coming for our lives. They'll be coming for our jobs. Being rendered obsolete by technology has been a concern among the flesh-and-blood set for hundreds of years -- cars put many in the horse industry out of work, for example -- but the speed and types of recent advances are about to give the issue an exceptional urgency. Previously, it was repetitive blue-collar jobs that were at risk, such as those in manufacturing. In the near future, however, the leaps in artificial intelligence will soon make it possible for machines to do all sorts of jobs, including those that require thinking skills we once believed beyond the reach of machines.
First Autonomous Test Vehicle Developed Entirely By Toyota Research Institute Displayed At Prius Challenge Event At Sonoma Raceway
The all- new test vehicle will be used to explore a full range of autonomous driving capabilities. Toyota's work on autonomous vehicles in the United States began in 2005 at its technical center in Ann Arbor, Mich.-- The company secured its first U.S. patents in the field in 2006.-- According to a report last year by the Intellectual Property and Science division of Thomson Reuters, Toyota holds more patents in the field than any other company. "This new advanced safety research vehicle is the first autonomous testing platform developed entirely by TRI, and reflects the rapid progress of our autonomous driving program," said TRI CEO Gill Pratt.
Why Nissan's CEO says the human brain still trumps artificial intelligence
The leader of one of the world's largest automobile producers expects that cars will soon drive themselves and sync to the world around them -- but don't count out the human behind the wheel just yet. Carlos Ghosn, the chief executive and chairman of an alliance that includes Nissan, Renault and Mitsubishi, said Thursday that humans will remain involved in the operation of vehicles for the foreseeable future, even as cars with self-driving technology enter the market in the next five years. You will push a button to activate the car's autonomous driving feature, he said, but it will encounter everyday scenarios it cannot compute and that require human assistance. "Artificial intelligence is still way below the creativity of the human brain," Ghosn said. Imagine a self-driving car coming upon a broken-down vehicle in the road, but there is a solid line to either side of it, Ghosn said.
The ability to predict earthquakes in the lab raises the possibility that the same thing will be possible for real earthquakes, too
Geologists have long been able to work out the approximate risk of an earthquake. Their approach is to work out when the fault moved in the past and use any periodicity to predict the future. The most famous example involves the Parkfield segment of the San Andreas Fault in California, one of the most carefully studied faults on the planet. Earthquakes occurred here in 1857, 1881, 1901, 1922, 1934, and 1966, suggesting a pattern in which quakes occur every 22 years give or take a few years. Geologists therefore predicted that a quake would occur between 1988 and 1993, but they had to wait until 2004 for their temblor.