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Major advances in artificial intelligence (AI) have opened the door to many new ideas that were just impossible a few years ago

When creating a new AI-based app, there are many generic problems that are already being solved by other companies, for example face and gesture detection.

Unless this is the main business and focus of the company, they will prefer to look for an out-of-the-box AI-as-a-service solution which will save them time, expertise and money.

This type of solutions are called AI platforms and give their users many out-of-the-box services, such as computer vision (feature/face and gesture detection), natural language processing (NLP), speech to text, and translations between different language.

Many companies including Google and Amazon sell this kind of AI services. During 2017, we will continue to see many improvements in those platforms mainly in the ease of use, accuracy and performance.

Businesses whose goals can’t be achieved using AI-as-a-service will create customised modules on top of those platforms or completely start from scratch to create their own image recognition algorithm.

Companies in the medical field such as Zebra medical will continue to improve their AI algorithm, which can now detect under-diagnosed medical conditions in MRI scans.

Other companies such as Tesla will use similar technologies to improve their fully autonomous level five self-driving vehicles.

2017 will continue to see many businesses taking advantage of existing platforms and others creating their own customised AI algorithms.

Another major trend that will grow dramatically next year is apps being built on top of existing AI-ecosystems such as Siri by Apple, Alexa by Amazon and Assistant by Google.

Joining one or more of these closed AI-ecosystems brings tremendous benefits to the business, including huge ecosystem and distribution channels.

For the developers, it instantly harnesses the great power of AI, without the need to build and understand artificial intelligence.

All this is worth a lot of money, which can be saved by taking advantage of the existing AI-ecosystems.

As an example, let’s take Amazon’s AI-ecosystem with its ‘Alexa’ brain. One of the ways to interact with Alexa is to buy Amazon Echo, a hands-free speaker that you can control with your voice.

Domino’s pizza created an app for the Echo that allows hands-free pizza ordering with voice-control. This type of AI technology combined with a strong community of third-party developers will dramatically change the way we interact with technology around the house, office or on the go.

Similar to Allo, an instant messaging app developed by Google that includes a virtual assistant which provides a ‘smart reply’ function that allows users to reply without typing, we’ll see AI services further weave into everyday interactions in a conversational manner.

In terms of customer service, we’re seeing bots becoming a go-to tool. These bots are built into current platforms such as Facebook to allow people to check their account, make reservations or be redirected to the right department.

By not needing to wait for a physical body, customers are able to lessen the time they need to spend finding help, without draining companies resources.

Moreover, texting a bot feels more natural than conversing with one over the phone where they may only understand simple phrases.

Beyond customer servicing, bots on Facebook have been built by news sites to keep users up to date in a conversational manner.

Quartz introduced a conversational style app that updates throughout the day while CNN has built a bot directly for Facebook messenger that can reply with news depending on the input. So if a user wishes to read news about a certain topic, they can send a text message to CNN to request it.

Author:  Ben Rossi

Source:  http://www.information-age.com/2017-hold-digital-economy-123463767

Published in Business Research

When I started in TV journalism three decades ago, pictures were still gathered on film. By the time I left the BBC in 2015, smartphones were being used to beam pictures live to the audience. Following the digital revolution and the rise of online giants such as Facebook and Google, we have witnessed what Joseph Schumpeter described as the “creative destruction” of the old order and its replacement by the innovative practices of new media.

There has been a great deal of furious – and often hyperbolic – discussion in the wake of the US election, blaming the “echo-chamber” of the internet – and Facebook in particular – for distorting political discourse and drowning the online public in “fake news”. Antidotes are now sought to ensure that “truth filters” guard the likes of Facebook – and its users – from abuse at the hands of con artists wielding algorithms.

Students in the town of Veles, Macedonia where reports say hundreds of websites are churning out ‘fake news’ designed to appeal to Donald Trump supporters on social media. EPA/Georgi Licovski

Facebook and Google are now the big beasts of the internet when it comes to distributing news – and as they have sought to secure advertising revenue, what has slowly but surely emerged is a kind of “click-mania”. This is how it works: the social media platforms and search engines advertise around news stories, which means that the more clicks a story gets the more eyeballs see the social media sites’ advertising, which generates revenue for them. In this media environment, more clicks mean more revenue – so the content they prioritise is inevitably skewed towards “clickbait” – stories chosen for their probability of getting lots and lots of readers to click on them. Quality and veracity are low on the list of requirements for these stories.

It is difficult to argue that this did not impact on online editorial priorities with hyperbolic headlines becoming ever more tuned to this end. At times, on some platforms, it resulted in what Nick Davies dubbed“churnalism”, whereby stories were not properly fact-checked or researched.

Erosion of trust

Consumption patterns are inevitably affected by all this creative destruction and social media sites have quickly replaced “the press” as leading sources of news. And yet there is the danger that the resulting information overload is eroding trust in information providers.

The outgoing US president, Barack Obama, captured the dilemma the public faces on his recent trip to Germany:

If we are not serious about facts and what’s true and what’s not, if we can’t discriminate between serious arguments and propaganda, then we have problems.

There is a renewed recognition that the traditional “gatekeepers” – journalists working in newsrooms – do provide a useful filter mechanism for the overabundance of information that confronts the consumer. But their once-steady advertising revenues are fast being rerouted to Facebook and Google. As a result, traditional news companies are bleeding to death – and the currently popular strategy of introducing paywalls and subscriptions are not making up the losses. Worse still, many newspapers continue to suffer double-digit falls in circulation, so the gatekeepers are “rationalised” and the public is the poorer for it.

Rise of the algorithm

One of the answers lies in repurposing modern newsrooms, which is what the likes of the Washington Post are doing under its new owner Jeff Bezos. Certainly, journalists have to find ways of encouraging people to rely less on, or become more sceptical of, using social media as their primary source for news. Even Facebook has recognised it needs to do more to avoid fakery being laundered and normalised on its platform.

So how to avoid falling for fakery? One option involves the use of intelligent machines. We live in a media age of algorithms and there is the potential to use Artificial Intelligence as a fundamental complement to the journalistic process – rather than simply as a tool to better direct advertising or to deliver personalised editorial priorities to readers.

Software engineers already know how to build a digital architecture with natural language programming techniques to recognise basic storylines. What is to stop them sampling a range of versions of a story from various validated sources to create a data set and then use algorithms to strip out bias and reconstruct the core, corroborated facts of any given event.

Aggregation and summation techniques are beginning to deliver results. I know of at least one British tech start-up that, although in the research and development phase, has built an engine that uses a natural language processing approach to digest data from multiple sources, identify a storyline and provide an artificially intelligent summary that is credible. It’s a question of interpretation. It is, if you will, a prototype “bullshit detector” – where an algorithmic solution mimics the old-fashioned journalistic value of searching for the truth.

If we look at the mess our democracies have fallen into because of the new age of free-for-all information, it is clear that we need to urgently harness artificial intelligence to protect open debate – not stifle it. This is one anchor of our democracies that we cannot afford to abandon.

Source : http://theconversation.com

Author : Kurt Barling

Published in Social

YOU KNOW YOU shouldn’t click on that article. There’s no way the headline is going to live up to the promise. But the draw of finding out what happens next—crossing that curiosity gap—is just too much to resist. So you take the bait. And, sure enough, you’re disappointed.

Facebook wants to stop this from happening, and it’s turning to artificial intelligence to help. Earlier this month the company announced that it was tweaking its algorithms to cut down on “clickbait”—the ubiquitous plague of Internet content that over-promises and under-delivers. But it’s a big Internet out there, and plenty of other companies and sites that could benefit from tools that can separate quality news stories from fluff. Now Facebook is open sourcing software to help filter out all that Internet noise.

Facebook’s AI-driven text classification system, bag-of-tricks” approach that helps machines efficiently glean information from the order in which words appear. Another FastText tactic breaks down words into “subwords“—such as prefixes, suffixes and root words—to help computers more easily learn their meanings.

Beyond clickbait, Facebook suggests software developers could use FastText to help filter out spam. It could power search engines and autocomplete fields. Recommendation engines like the ones used by the likes of Amazon or Netflix could also benefit from a little artificial smarts that can get a better read on what you’re writing.

FastText is just the latest of several open source AI projects to come out of Facebook in recent years. The company has released AI algorithms, a tool for spotting bugs (in code), and designs for AI-optimized hardware. And it’s not the only tech giant doing this. Google released its AI framework TensorFlow, and companies from Microsoft and Baidu to Amazon and Yahoo have all given away the code for some of their own AI tech.

That may seem like an odd trend, given that each of these companies hopes to best the other with better tech, including AI. But artificial intelligence is still a budding field. The researchers creating these technologies within companies like Facebook and Google benefit from having their counterparts on the outside review their work and suggest changes. In a sense, open sourcing code offers the same potential benefit that publishing research in peer-reviewed journals does for scientists. In other words, Facebook is betting that giving away its AI tech will make for better software, because it too can benefit from the new ways others use it. And besides, more developers and researchers learning to use the software means more coders better prepared to work for Facebook in the future.

Source : http://www.wired.com/2016/08/wont-believe-facebook-giving-away-free-now/ 

Published in Others
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