Metropolis The Housing Market Is Already Terrible. A.I. Is Making It Even Worse. While digital staging is nothing new to real estate, bot-made listings are forcing homebuyers and professionals to ask themselves if this is a straight-up deceptive practice. DeAnn Wiley was on the hunt for a new rental in Detroit earlier this month when she had the displeasure of arriving at a property that looked nothing like what was advertised online. "The photos made the home look brand new, only to get there and see the usual wear and tear and the old'landlord special,' " she told Slate.

No-one likes blurry images, whether they are found in personal or professional situations. If a photo lacks sharpness, don't expect anyone to want to play through your slideshows. So, is it possible to enhance a blurry photo? With HitPaw FotorPea, which uses an AI-powered algorithm to automate editing, eliminating the blur and generally sprucing up your images is effortless. Read our guide to learn how to fix blurry photos with HitPaw FotorPea.

The rapid advance of artificial intelligence technology has raised concerns about eliminating jobs held by humans. Professional photography is now coming into focus as one such potential casualty. "The rapid advancements in AI and image processing are transforming photography from a skill-based art to one that is increasingly technology-driven. This evolution is making high-quality photography accessible to a broader audience, challenging the traditional notion of professional photography as a skill," according to a report published Tuesday by Medium. "As we move further into this AI-driven era, it becomes evident that the role and relevance of professional photography skills, as we have known them, are becoming obsolete."

We are living in an exciting time, where software and machine learning are rapidly changing the way we approach work. For some industries, artificial intelligence will destroy job opportunities, but for other industries, it will revolutionize productivity. How will photography and the retouching world fare as editing software begins using this exciting technology? Here at Fstoppers, we are constantly testing and exploring the latest and greatest photo-editing software for photographers. Last week, Skylum released a new software suite called Luminar 4, which helps photographers automate their post-production workflow.

Since their introduction more than a decade ago, smartphones have been equipped with cameras, allowing users to capture images and video without carrying a separate device. Thanks to the use of computational photographic technologies, which utilize algorithms to adjust photographic parameters in order to optimize them for specific situations, users with little or no photographic training can often achieve excellent results. The boundaries of what constitutes computational photography are not clearly defined, though there is some agreement that the term refers to the use of hardware such as lenses and image sensors to capture image data, and then applying software algorithms to automatically adjust the image parameters to yield an image. Examples of computational photography technology can be found in most recent smartphones and some standalone cameras, including high dynamic range imaging (HDR), auto-focus (AF), image stabilization, shot bracketing, and the ability to deploy various filters, among many other features. These features allow amateur photographers to produce pictures that can, at times, rival photographs taken by professionals using significantly more expensive equipment.

How did Google get Clips, its AI-powered camera, to learn to automatically take the best shots of users and their families? Well, as the company explains in a new blog post, its engineers went to the professionals -- hiring "a documentary filmmaker, a photojournalist, and a fine arts photographer" to produce visual data to train the neural network powering the camera. The blog post explains this process in a little more detail, but it's basically what you'd expect for this sort of AI. In order for the software to recognize what makes a good or a bad photo, it had to be fed lots of examples. The programmers thought about not only obvious markers (eg, it's a bad photo if there is blurring or if something's covering the lens) but also more abstract criteria, such as "time" -- training Clips with the rule, "Don't go too long without capturing something."

This is thanks to computational photography that will make each snap shot look like it was taken using a professional camera. There is no denying that one of the most sought after features of any smartphone today is its camera. Ever since image sharing sites and social media platforms rose to popularity, sharing pictures of just about anything has taken over the lives of many people around the world. Smartphone manufacturers started developing camera phones that can capture high-quality images to satisfy the needs of photo-savvy individuals. If that is not enough, some of these mobile phone giants partnered with famous camera makers to create the best camera phones of today.

Imagery taken by Google's Street View team is being turned into amazing artistic landscape photography, using an experimental piece of AI software. Experts from the firm have used machine learning to train its Creatism software to scour pictures of impressive views from around the world, which it then alters using visual effects. Many of the breathtaking panoramas that result from the process appear as if they have been captured by professional photographers. But can you spot the difference between the machine generated snaps and the pictures taken by people? Take a look at the images below and visit the bottom of the page to find out which is which.

An "art" landscape photograph from Interlaken, Switzerland, produced from a Google Earth image by Creatism -- Google's new experimental "deep-learning system for artistic content creation." There are many professions where human workers are being replaced by intelligent machines. Cashiers at stores and restaurants, factory workers, even farm laborers are all being swapped out for robots at a dizzying pace. Until now, however, those in the artistic professions felt pretty safe from the threat. After all, how could an algorithm ever replicate the inenarrable process of human creativity?

Google's latest artificial intelligence experiment is taking in Street View imagery from Google Maps and transforming it into professional-grade photography through post-processing -- all without a human touch. Hui Fang, a software engineer on Google's Machine Perception team, says the project uses machine learning techniques to train a deep neural network to scan thousands of Street View images in California for shots with impressive landscape potential. The software then "mimics the workflow of a professional photographer" to turn that imagery into an aesthetically pleasing panorama. The research, posted to the pre-print server arXiv earlier this week, is a great example of how AI systems can be trained to perform tasks that aren't binary, with a right or wrong answer, and more subjective, like in the fields of art and photography. Doing this kind of aesthetic training with software can be labor-intensive and time-consuming, as it has traditionally required labeled data sets.