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Ryff has a big idea that it says could turn the $23 billion product placement market upside down. Product placement is the advertising tactic of placing a branded object, like a bottle of Coca-Cola, in a scene in a movie or a TV show.

Los Angeles-based Ryff has figured out how to do this digitally with cloud technology. Ryff figures out the places in video content where virtual objects can be placed in a scene where they seem like they are a natural part of the environment. That means the objects have to be rendered realistically enough so they can be mistaken for being part of a real scene, as recorded in a movie or TV show or a commercial, said Roy Taylor, CEO of Ryff, at an event on Thursday evening.

“We are on a new platform that makes images intelligent,” Taylor said. “Ryff is the world’s first image technology company using AI and visual computing to change the way we experience entertainment.”

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Researchers are paving the way to total reliance on renewable energy as they study both large- and small-scale ways to replace fossil fuels. One promising avenue is converting simple chemicals into valuable ones using renewable electricity, including processes such as carbon dioxide reduction or water splitting. But to scale these processes up for widespread use, we need to discover new electrocatalysts—substances that increase the rate of an electrochemical reaction that occurs on an electrode surface. To do so, researchers at Carnegie Mellon University are looking to new methods to accelerate the discovery process: machine learning.

Zack Ulissi, an assistant professor of chemical engineering (ChemE), and his group are using machine learning to guide electrocatalyst discovery. By hand, researchers spend hours doing routine calculations on materials that may not end up working. Ulissi’s team has created a system that automates these routine calculations, explores a large search space, and suggests new alloys that have promising properties for electrocatalysis.

“This allows us to spend our time asking science questions, like, ‘How do you predict the properties of something,’ ‘What is the thermodynamic model,’ ‘What is the model of the system,’ or ‘How do you represent the system?’” said Ulissi.

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An international team of researchers led by The Australian National University (ANU) has invented a tiny camera lens, which may lead to a device that links quantum computers to an optical fibre network.

Quantum computers promise a new era in ultra-secure networks, artificial intelligence and therapeutic drugs, and will be able to solve certain problems much faster than today’s computers.

The unconventional lens, which is 100 times thinner than a human hair, could enable a fast and reliable transfer of information from the new-age computers to a network, once these technologies are fully realised.

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MIT’s Lincoln Laboratory Intelligence and Decision Technologies Group yesterday unveiled a neural network capable of explaining its reasoning. It’s the latest attack on the black box problem, and a new tool for combating biased AI.

Dubbed the Transparency by Design Network (TbD-net), MIT’s latest machine learning marvel is a neural network designed to answer complex questions about images. The network parses a query by breaking it down into subtasks that are handled by individual modules.

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For several years, civil society groups have been calling for a ban on what they call “killer robots”. Scores of technologists have lent their voice to the cause. Some two dozen governments now support a ban and several others would like to see some kind of international regulation.

Yet the latest talks on “lethal systems” wrapped up last month with no agreement on a ban. The Group of Governmental Experts meeting, convened in Geneva under the auspices of the United Nations Convention on Certain Conventional Weapons, did not even clearly proceed towards one. The outcome was a decision to continue discussions next year.

Those supporting a ban are not impressed. But the reasons for the failure to reach agreement on the way forward are complex.

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Here in beautiful Basel, Switzerland we open the section Aging and Drug Discovery, actually an intersection of AI, longevity and drug discovery in the Innovation Forums of Basel Life Conference 2018. Dr Alex Zhavoronkov (InSilico Medicine) and Dr Morten Scheibye-Knudsen (University Copenhagen) welcomed us. Dr Jay Olshansky (University of Illinois at Chicago) gave the first lecture. Some examples for age face recognition were shown, emphasising the importance of wrinkles from smoking or others and suggesting that looking younger means living longer! After the wonderful lecture I immediately went to correct my make-up!

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Since its acquisition of ITA Matrix Software eight years ago, Google has been quietly rolling out new tools for travelers. Its progress has been even more notable over the past months and weeks as it began unveiling tools to help predict flight delays, plan trips, and manage itineraries — among other things.

These changes have some wondering: Is Google making a run at total domination in the travel space? If it is, there’s a strong case to be made for its potential to disrupt the travel and hospitality sector with a similar approach to Amazon’s run at retail, and more recently grocery.

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AI is massively transforming our world, but there’s one thing it cannot do: love. In a visionary talk, computer scientist Kai-Fu Lee details how the US and China are driving a deep learning revolution — and shares a blueprint for how humans can thrive in the age of AI by harnessing compassion and creativity. “AI is serendipity,” Lee says. “It is here to liberate us from routine jobs, and it is here to remind us what it is that makes us human.”

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