Last year, the Defense Advanced Research Projects Agency (DARPA), which funds a range of blue-sky research efforts relevant to the US military, launched a $1.5 billion, five-year program known as the Electronics Resurgence Initiative (ERI) to support work on advances in chip technology. The agency has just unveiled the first set of research teams selected to explore unproven but potentially powerful approaches that could revolutionize US chip development and manufacturing. Hardware innovation has taken something of a back seat to software advances in recent years, and that bothers the US military for several reasons. At the top of the list is that Moore's Law, which holds that the number of transistors fitted on a chip doubles roughly every two years, is reaching its limits (see "Moore's Law is dead. That could stymie future advances in electronics that the military relies on, unless new architectures and designs can allow progress in chip performance to continue.

Zero Touch & Carrier Automation Congress -- The 3GPP standards group is developing a machine learning function that could allow 5G operators to monitor the status of a network slice or third-party application performance. The network data analytics function (NWDAF) forms a part of the 3GPP's 5G standardization efforts and could become a central point for analytics in the 5G core network, said Serge Manning, a senior technology strategist at Sprint Corp. (NYSE: S). Speaking here in Madrid, Manning said the NWDAF was still in the "early stages" of standardization but could become "an interesting place for innovation." The 3rd Generation Partnership Project (3GPP) froze the specifications for a 5G new radio standard at the end of 2017 and is due to freeze another set of 5G specifications, covering some of the core network and non-radio features, in June this year as part of its "Release 15" update. Manning says that Release 15 considers the network slice selection function (NSSF) and the policy control function (PCF) as potential "consumers" of the NWDAF.

Thanks to the likes of Google, Amazon, and Facebook, the terms artificial intelligence (AI) and machine learning have become much more widespread than ever before. They are often used interchangeably and promise all sorts from smarter home appliances to robots taking our jobs. But while AI and machine learning are very much related, they are not quite the same thing. AI is a branch of computer science attempting to build machines capable of intelligent behaviour, while Stanford University defines machine learning as "the science of getting computers to act without being explicitly programmed". You need AI researchers to build the smart machines, but you need machine learning experts to make them truly intelligent.

From picking our favorite restaurants to predicting weather and correcting global food shortages, artificial intelligence is already augmenting everyday life. Firmly rooted in the realm of science fiction, artificial intelligence (AI) has often felt external – something happening out there. In reality, AI is a huge part of our everyday lives. We just don't recognize it. Bank alerts of suspected fraudulent charges, smartphone notifications to exercise, Siri or Cortana's ability to recognize voices – are all examples of AI. "Artificial intelligence is basically where machines make sense, learn, interface with the external world, without human beings having to specifically program it," said Nidhi Chappell, director of machine learning at Intel. AI improves lives in many other areas too.

Firmly rooted in the realm of science fiction, artificial intelligence (AI) has often felt external – something happening out there. In reality, AI is a huge part of our everyday lives. We just don't recognize it.Bank alerts of suspected fraudulent charges, smartphone notifications to exercise, Siri or Cortana's ability to recognize voices – are all examples of AI. "Artificial intelligence is basically where machines make sense, learn, interface with the external world, without human beings having to specifically program it," said Nidhi Chappell, director of machine learning at Intel. AI improves lives in many other areas too. By measuring biometrics in sports, data can help measure how an athlete's playing time impacts injury likelihood.

Artificial Intelligence (AI) is much more than the thinking, feeling robots often portrayed in pop culture. "Artificial intelligence is basically trying to have machines make sense, learn, and interface with the external world, without requiring programming by human beings," said Nidhi Chappell, Director of Machine Learning at Intel, and the applications for the tech are seemingly endless. From autonomous cars taking over our commutes to artificially intelligent robots teaching in our classrooms, AI technology is a major talking point right now in terms of how it is impacting the world of people. Less discussed are the ways in which AI is being used in relation to animals, but several companies and creators are merging artificial intelligence with the animal kingdom in unique ways. Every day, an estimated 96 African elephants are killed by poachers eager to strip the animals of their valuable ivory tusks.

Thanks to the likes of Google, Amazon, and Facebook, the terms artificial intelligence (AI) and machine learning have become much more widespread than ever before. They are often used interchangeably and promise all sorts from smarter home appliances to robots taking our jobs. But while AI and machine learning are very much related, they are not quite the same thing. You can now play a Pictionary-style game called Quick Draw against Google's AI You can now play a Pictionary-style game called Quick Draw against Google's AI You can now play a Pictionary-style game called Quick Draw against Google's AI You can now play a Pictionary-style game called Quick Draw against Google's AI You can now play a Pictionary-style game called Quick Draw against Google's AI AI is a branch of computer science attempting to build machines capable of intelligent behaviour, while Stanford University defines machine learning as "the science of getting computers to act without being explicitly programmed". You need AI researchers to build the smart machines, but you need machine learning experts to make them truly intelligent.

Firmly rooted in the realm of science fiction, artificial intelligence (AI) has often felt external – something happening out there. In reality, AI is a huge part of our everyday lives. We just don't recognize it. Bank alerts of suspected fraudulent charges, smartphone notifications to exercise, Siri or Cortana's ability to recognize voices – are all examples of AI. "Artificial intelligence is basically where machines make sense, learn, interface with the external world, without human beings having to specifically program it," said Nidhi Chappell, director of machine learning at Intel. AI improves lives in many other areas too. By measuring biometrics in sports, data can help measure how an athlete's playing time impacts injury likelihood.

Thanks to the likes of Google, Amazon, and Facebook, the terms artificial intelligence (AI) and machine learning have become much more widespread than ever before. They are often used interchangeably and promise all sorts from smarter home appliances to robots taking our jobs. But while AI and machine learning are very much related, they are not quite the same thing. Google's Digital Justice League: how its Jigsaw projects are hunting down online trolls AI is a branch of computer science attempting to build machines capable of intelligent behaviour, while Stanford University defines machine learning as "the science of getting computers to act without being explicitly programmed". You need AI researchers to build the smart machines, but you need machine learning experts to make them truly intelligent.

Thanks to the likes of Google, Amazon, and Facebook, the terms artificial intelligence (AI) and machine learning have become much more widespread than ever before. They are often used interchangeably and promise all sorts from smarter home appliances to robots taking our jobs. But while AI and machine learning are very much related, they are not quite the same thing. AI'lawyer' correctly predicts outcomes of human rights trials AI is a branch of computer science attempting to build machines capable of intelligent behaviour, while Stanford University defines machine learning as "the science of getting computers to act without being explicitly programmed". You need AI researchers to build the smart machines, but you need machine learning experts to make them truly intelligent.