Well, you can add "captioning photos" to the list of jobs robots will soon be able to do just as well as humans. After some training, the latest version of Google's "Show and Tell" algorithm can describe the contents of a photo with staggering 94% accuracy. Show and Tell is in the news today because Google actually made the model open source yesterday. You'll have to train it yourself, but the source code is there for anybody who would like to try. It's amazing how far machine learning, especially in the field of photography, has come in the past several years.

Artificial Intelligence is starting to play a big role in our daily life, and judging by recent developments in the field, it looks like the importance of AI will only increase in time. While some people worry that advancements in AI could replace jobs in the long run, it's difficult to argue with the idea that artificial intelligence can bring countless benefits in numerous fields, ranging from production to automotive and healthcare. Needless to say, companies have different takes on machine learning, and artificial intelligence is used in more than one way. In Facebook's case, AI will start playing a role in making social media interaction more meaningful to blind and visually impaired Facebook users who, starting today, can use a new feature called "automatic alternative text" in order to get a more detailed description of Facebook photos. One of the main reasons why Facebook enjoys as much popularity as it does today is because of photo sharing.

Facebook is using AI to help describe images posted by users. Facebook's iOS app is using object recognition technology to give blind people an audio breakdown of what's going on in photos posted on the social network. The new accessibility feature, rolling out today, could be a major improvement on existing screen readers, which largely focus on text. Until now, when blind users were checking their Facebook newsfeed and came across an image, they would only hear the word "photo" and the name of the person who shared it, which left the user still dependent on friends and family to interpret an image. To improve the experience for blind people, Facebook has used its vast trove of user images to train a deep neural network that drives a computer vision system built to recognise objects in images.

Ask a member of Facebook's growth team what feature played the biggest role in getting the company to a billion daily users, and they'll likely tell you it was photos.

Browse through your Facebook News Feed and you'll see photos play a prominent part, meaning visually impaired users are missing out on a lot of updates from their friends. Now Facebook's engineers have harnessed the power of an artificial intelligence network to describe these pictures to blind or partially blind users. Facebook is calling the system "automatic alternative text" and it's based on a neural network primed with billions of parameters and millions of examples. Such neural networks – vast, complex databases designed to mimic the human brain as closely as possible – are playing an increasingly important role in modern computing. The AI software doesn't actually "see" the picture, but it can compare the objects in it with its vast internal database of similar photos and make an educated guess about what's being shown.

Artificial intelligence is meant to be taking over the world, but along the way, it seems to be helping out humans from time to time. Today's example: Facebook is using its artificial intelligence network to describe photos to the blind. If your Facebook feed is anything like mine, the vast majority of my friends' posts are either photos or links. Without being able to see photos, blind users are being left out of a huge chunk of the social interaction happening on Facebook. The company's answer is automatic alternative text: a neural network analyses photos, and if it's at least 80 percent confident it understands what's going on, the AI will describe the photo.