Robots will help a national news agency to create up to 30,000 local news stories a month, with the help of human journalists and funded by a Google grant. The Press Association has won a €706,000 (£621,000) grant to run a news service with computers writing localised news stories. The national news agency, which supplies copy to news outlets in the UK and Ireland, has teamed up with data-driven news start-up Urbs Media for the project, which aims to create "a stream of compelling local stories for hundreds of media outlets". It won one of the largest grants to date from Google's Digital News Initiative (DNI), which is aimed at supporting innovation in European digital journalism. PA and Urbs Media will set up Radar – Reporters And Data And Robots – to produce thousands of stories each month.

If you make a purchase by clicking one of our links, we may earn a small share of the revenue. However, our picks and opinions are independent from USA TODAY's newsroom and any business incentives. With Amazon Prime Day coming up, there will be lots of deals Prime members can only get by ordering through an Amazon Alexa device. If you don't already have an Echo or Fire device, now is the perfect chance to get one for a great low price. The Amazon Tap, Amazon's portable bluetooth speaker, gives you a great way to listen to your music anywhere you are.

Is bingeing a good thing? The mobile network Three would like to persuade you it is. Its latest, just-announced phone tariff is called Go Binge and it encourages you to make the most of your 4G connection with streaming that doesn't impact on your monthly data total. Not for just any streaming, you understand, but for four carefully picked apps. They're pretty good apps to choose, though: Netflix, TVPlayer, Deezer and SoundCloud.

I am one of the authors of ShuffleNet. We've designed a new convolutional neural network structure for mobile platforms which utilizes pointwise group convolution and channel shuffle. Under the budget of 40MFLOPS, we've achieved 6.7% absolute top-1 error reduction on ImageNet classification compared to MobileNets. Empirically, our network with approximately the same error runs 13x faster than AlexNet on an ARM platform.

Alexa, Amazon's digital assistant that powers, among other things, its popular Echo smart speaker, has grown its third-party-created skillset from 10,000 to 15,000 in under six months, as developers race to get their software on what has become an increasingly popular platform. The figures come from Voicebot, which analysed skills available in the US, and shows a massive acceleration in the volume of third-party software available through Alexa. At the start of the year, there were around 7,000 skills available on the platform, according to Voicebot, and Amazon's official figures suggest that in September 2016, there were only around 3,500. 'Flash Briefings', which provide audio updates on news, weather and other topics, are the most popular skills, making up 20 per cent of the US skills store. With both a clear use case and a simple development process, publishers have flocked to this format, with The Wall Street Journal, NPR and The Washington Post all launching Alexa Skills that saw significant downloads.

Spotify's music recommendation engine – Spotify have built their own AI and machine learning engine, whose sole purpose is monitor a user's listening preferences and tailor the whole product around it. In the first 2-3 weeks Spotify's AI engine would have understood what you like, which artists are your favorite, what are the genre's you are most interested in, to minute details like, when do you listen most often, your average listening period, etc. Using all these data, the AI engine will recommend music that you are most likely to favorite or save to your own collection. Apart from that, it will automatically send you communication about new releases from your favorite artists, how your favorite music charts are shaping up, etc. Streaming industry experts, credit Spotify's AI engine for their massive growth in last 6 years and also how easily they have fended off bigger companies like Apple, Google, etc in the same industry to keep the top player title for themselves.

Welcome to "What Is," a new column on dedicated to giving simple answers to complex things that affect the products around you. Submit yours to [email protected] and we'll do our best to get them answered. Every day we hear buzzwords like artificial intelligence and machine learning at some point or another in the news cycle, typically associated with smartphones, smart speakers, drones, and so on. It's easy to take for granted that these are technologies that make our lives easier and more convenient, undergirding everything from facial recognition to autocomplete on Google. Even Spotify uses machine learning for music recommendations.

Thomson Reuters has launched a start-up incubator in Switzerland to host early-stage entrepreneurs working on big data, advanced analytics, distributed ledgers, artificial intelligence, machine learning and other transformational technologies. Thomson Reuters Labs – The Incubator, as its called, will furnish its cohort with access to Thomson Reuters data and content sets, as well as mentoring from executives and networking opportunities for investment and commercialisation. The Incubator is the next horizon of the company's investment in the Thomson Reuters Labs network, said a statement. TR's Innovation Labs collaborate with customers, universities and startups around the world. Mona Vernon, chief technology officer for Thomson Reuters Labs, said: "Technology is evolving at an unprecedented rate and corporations need to keep pace. Partnering with startups and other market disruptors is essential for us to be agile and responsive to our customers. The Incubator will become an essential part of our corporate strategy to drive organic growth through innovation."

Among the multitude of new technologies entering banking's sphere, machine learning likely will quickly come to the fore. Imagine some poor bank employee sitting at a desk, peering at multiple computer screens. On those screens come waves and waves of charts, transaction lists, voice recordings, geographical data points, and social media posts, all constantly changing--and all focused on a single bank customer. The bank employee's job, at the moment: Decide whether that customer actually used his own credit card to buy a big screen television, or if that transaction, which just occurred, is fraudulent. And he only has a moment to decide.

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