Google announced today that it has acquired Paris-based Moodstocks, a startup that has developed machine learning technology to bolster the image recognition features on smartphones. "We continue to pursue our machine learning and research efforts," wrote Vincent Simonet, head of the research and development team for France Google, "and Moodstocks is the latest proof of our commitment to this area." Today, we're thrilled to announce that we've reached an agreement to join forces with Google in order to deploy our work at scale. We expect the acquisition to be completed in the next few weeks. Our focus will be to build great image recognition tools within Google, but rest assured that current paying Moodstocks customers will be able to use it until the end of their subscription.

DeepMind, Google's London-based artificial intelligence company, has started training neural networks to recognise the signs of eye disease in medical images. A partnership with Moorfields Eye Hospital in London has given the company access to about a million anonymised retinal scans, which DeepMind will feed into its artificial intelligence software. The project will target two of the most common eye diseases – age related macular degeneration and diabetic retinopathy. More than 100 million people around the world have these conditions. The information that Moorfields is providing includes scans of the back of people's eyes, as well as more detailed scans known as optical coherence tomography (OCT). The idea is that the images will let DeepMind's neural networks learn to recognise subtle signs of degenerating eye conditions that even trained clinicians have trouble spotting.

It's odd holding a minute's silence for a dead person who you never knew anything about, especially at a tech show where you can see messages from their AI reincarnation flashing up on a massive screen behind the very-much-alive man who has made this whole strange scene possible. Is this what a 21st-century Dr Frankenstein looks like? Except now, instead of stitching body parts together to recreate life, what we're seeing is found fragments of the deceased's personality put through a form of machine learning to create a semblance of their life after death. Very recently however, Luka was adapted in a brand new way, to include a chatbot based on a real human being--one who just so happens to be dead. It's this ghost-in-the-machine that has the audience spellbound, as Luka's cofounder Eugenia Kuyda explains how text messages, social media conversations, and other sources of information on the deceased were grafted onto an existing AI platform.

Your job may end up being done by a computer in the not-so-distant future, according to participants in a White House-hosted discussion on Tuesday. The discussion addressed how the future of automation can provide many social and economic advantages, but could also be a major disadvantage for those who would lose their jobs to robots. "There are fantastic things to be very excited about," said Martin Ford, author of two books on the future of automation. He cautioned that increased automation could have major detriments for the labor market. "Almost any kind of work that is on some level routine and predictable is very highly susceptible to [automation]."

The robots are coming, and they're bringing dinner. Food delivery company Just Eat will begin testing a mostly self-driving robot from Starship Technologies this month, using it to carry orders to customers within a few kilometers of participating restaurants in the U.K. Despite the high-flying name, Starship Technologies has a down-to-earth ambition: Automating local logistics over the "last mile" between retailer and customer, for a cost of around 1 per delivery. It plans to do that with a six-wheeled robot that looks like a cross between a Roomba and an icebox. The robot trundles along at a brisk walking pace, monitoring its environment using an array of cameras. Most of the time, it chooses its own route, avoiding obstacles and people.

In a recent op-ed for The New York Times, Microsoft Principal Researcher Kate Crawford discusses what she sees as the a very real problem with artificial intelligence today: "Sexism, racism and other forms of discrimination are being built into the machine-learning algorithms that underlie the technology behind many "intelligent" systems that shape how we are categorized and advertised to." Below are a few excerpts from "Artificial Intelligence's White Guy Problem." Police departments across the United States are also deploying data-driven risk-assessment tools in "predictive policing" crime prevention efforts. In many cities, including New York, Los Angeles, Chicago and Miami, software analyses of large sets of historical crime data are used to forecast where crime hot spots are most likely to emerge; the police are then directed to those areas. At the very least, this software risks perpetuating an already vicious cycle, in which the police increase their presence in the same places they are already policing (or overpolicing), thus ensuring that more arrests come from those areas.

The next time you order food using the delivery app Just Eat in London, don't be surprised if it's brought to your door by a small, six-wheeled robot. London-listed Just Eat Plc. will join German retail chain Metro AG, logistics company Hermes Group, and U.K. food delivery startup Pronto Technology Ltd., in trialing delivery using self-driving robots. Starship Technologies, the company that makes the droids, said Wednesday that Just Eat and Pronto will be using the robots in London, while Metro and Hermes will deploy them in Dusseldorf, Germany, and Bern, Switzerland, as well as another undisclosed German city. Created by two Skype co-founders, Starship, which is headquartered in London and has its engineering research and development office in Tallinn, Estonia, has been testing its robots in 12 countries over the past nine months. This will be the first time businesses will be using the technology to deliver real orders to paying customers.

The White House and New York University's Information Law Institute, with support from Google Open Research, Microsoft Research and the MacArthur Foundation will host a major public symposium to address the near-term impacts of AI technologies across social and economic systems. The focus will be the challenges of the next 5-10 years, specifically addressing four themes: social inequality, labor, healthcare, and ethics. Leaders from industry, academia, and civil society will share ideas for technical design, research and policy directions. This event will be live-streamed. Check back on July 7th for a live feed.

Google DeepMind, the British artificial intelligence research arm of Google, will collaborate with Britain's National Health Service (NHS) to tackle sight loss in humans. A retina-scanning system that will be able to detect the early signs of eye disease will be developed in partnership with with Moorfields Eye Hospital in London. About a million anonymized scans taken from patients who attended Moorfields between January 1, 2007 and February 29 this year will be used for analysis by Google's Artifical Intelligence (Al) computer. Scientists are hopeful that they will be able to recognize conditions such as macular degeneration, a gradual deterioration of the light-sensitive tissue lining at the back of the eye, and diabetic retinopathy, when high blood sugar levels damage the retina over time. Early treatment can be critical in both conditions.

Last year, Amazon kicked off its inaugural Picking Challenge to encourage teams to create robots able to perform the task of an Amazon stock picker. This year the competition was expanded to include not only picking items from a shelf and placing them in a container, but the reverse as well – and a team from the Netherlands has claimed victories in both. This year's pick task, which carries over from last year but has been made more difficult, requires robots to grab target items from a shelf and place them in a container. Conversely, the stow task involves the robot removing items from a box and placing them back on the shelf. They sound like very simple tasks for a human, but for robot competitors it requires a sophisticated array of sensors, moving parts and artificial intelligence.