AI News, Open Thread Non artificial intelligence

Amazon broke the high street, but artificial intelligence could save it

To fight back against online retail giants, more boutique operators are turning to artificial intelligence.

Instead of expecting you to trek to the shops, the company combines the results of a series of algorithms with the insights of a human stylist to deliver a tidy box of new clothes straight to your doorstep.

The companies aren’t identical: Stitch Fix uses the “surprise box” approach – you don’t know what you’re getting until you open the package – while Thread lets you select the items that get delivered.

And in a move that echoes Netflix’s decision to start creating their own films and series, Stitch Fix has launched its very own range of AI-informed clothing – shirts, blazers, trousers and belts that fill gaps identified by the company’s algorithms.

“Who is this guy, and who does he want to be?” Operating across eight European countries, Outifittery has learned, example, that men in Sweden tend to stick to grey and dark blue, while Dutch men are more inclined to bright colours.

What the company ultimately wants to do, says Bösch, is to recreate the feeling of walking into an ancient boutique: the owner greets you by name, sits down with you over a coffee, then tells you about some of the latest items they have in stock that might fit your taste.

“But they will change.” “The interesting thing we are seeing is the phenomenon known as ‘clicks to bricks’ – online retailers that are also opening physical stores,” he says, noting that players like Trunk Club and Bonobos are leading the way on that front in the US.

5 Important Artificial Intelligence Predictions (For 2019) Everyone Should Read

Artificial Intelligence – specifically machine learning and deep learning – was everywhere in 2018 and don’t expect the hype to die down over the next 12 months.

The jury’s still out on whether this will lead to a glorious utopia, with humans free to spend their lives following more meaningful pursuits, rather than on those which economic necessity dictates they dedicate their time, or to widespread unemployment and social unrest.

In the meantime, here are five things that we can expect to happen: 2018 has seen major world powers increasingly putting up fences to protect their national interests when it comes to trade and defense.

At the same time, Google has faced public criticism for its apparent willingness to do business with Chinese tech companies (many with links to the Chinese government) while withdrawing (after pressure from its employees) from arrangements to work with US government agencies due to concerns its tech may be militarised.

This framework of open collaboration has been instrumental to the rapid development and deployment of AI technology we see taking place today and putting up borders around a nation’s AI development is likely to slow that progress.

Reports have even found that companies are sometimes holding back from deploying AI due to fears they may face liabilities in the future if current technology is later judged to be unfair or unethical.

After spending the previous few years getting their data in order and identifying areas where AI could bring quick rewards, or fail fast, big business is as a whole ready to move ahead with proven initiatives, moving from piloting and soft-launching to global deployment.

As I mentioned in my introduction to this post, in the long-term its uncertain if the rise of the machines will lead to human unemployment and social strife, a utopian workless future, or (probably more realistically) something in between.

But when it comes to doctors and lawyers, AI service providers have made concerted effort to present their technology as something which can work alongside human professionals, assisting them with repetitive tasks while leaving the 'final say' to them.

This means those industries benefit from the growth in human jobs on the technical side – those needed to deploy the technology and train the workforce on using it – while retaining the professionals who carry out the actual work.

AI is genuinely interwoven into our lives now, to the point that most people don't give a second thought to the fact that when they search Google, shop at Amazon or watch Netflix, highly precise, AI-driven predictions are at work to make the experience flow.

slightly more apparent sense of engagement with robotic intelligence comes about when we interact with AI assistants – Siri, Alexa, or Google Assistant, for example – to help us make sense of the myriad of data sources available to us in the modern world.

Data gathered from users allows application designers to understand exactly which features are providing value, and which are underused, perhaps consuming valuable resources (through bandwidth or reporting) which could be better used elsewhere.

On top of this, AI assistants are designed to become increasingly efficient at understanding their human users, as the natural language algorithms used to encode speech into computer-readable data, and vice versa is exposed to more and more information about how we communicate.

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