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 classifiers can be represented as discrimination maps, where a red color indicates that the intensity at that location contributes to the likelihood of the images belonging to the more advanced stage, and a blue color to the likelihood of belonging to the less advanced stage. Weights are shown inside the mask that resulted in the highest accuracies for each classification: A: Alzheimer's disease (AD) vs. subjective cognitive decline (SCD); B: AD vs. mild cognitive impairment (MCI); C: MCI vs. SCD. Figure 2. Discrimination maps for classifying MCI subgroups, inside the masks that resulted in the highest accuracies. A: between patients with MCI that converted to AD (MCIc) and subjects with SCD; B: between MCIc and patients with MCI that remained stable (MCIs).

Machine learning is responsible for a great deal of our tech advancements, from speech recognition to self-driving cars, smart homes and beyond. This developing field of study explores the techniques used to give computers the ability to learn without being explicitly programmed, creating a new world of technological opportunities. If breakthrough tech fascinates you, you can develop the skills required to deep-dive in an industry that's on track to change the world with the 10-course instruction provided in the Complete Machine Learning Bundle, now available at a 94 per cent off from Pocket-lint Deals. The Complete Machine Learning Bundle offers high-level learning through 10 comprehensive courses and 63 hours of training, putting you in command of an exciting field with high-value applicability everywhere from the startup world to Fortune 500 companies and beyond. Develop your skills in Python programming and Python libraries for Machine Learning, utilizing Hadoop and MapReduce to process and manage enormous amounts of data efficiently.

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 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.

Iyad Rahwan was the first person I heard use the term society-in-the-loop machine learning. He was describing his work which was just published in Science, on polling the public through an online test to find out how they felt about various decisions people would want a self-driving car to make - a modern version of what philosophers call "The Trolley Problem." The idea was that by understanding the priorities and values of the public, we could train machines to behave in ways that the society would consider ethical. We might also make a system to allow people to interact with the Artificial Intelligence (AI) and test the ethics by asking questions or watching it behave. Society-in-the-loop is a scaled up version of human-in-the-loop machine learning - something that Karthik Dinakar at the Media Lab has been working on and is emerging as an important part of AI research.

DOING THE ROBOT So, you're thinking about bringing artificial intelligence technology to your financial institution - what do you need to take into consideration? First, decide if you are betting for a chatbot or conversational UI in your app, or both. Regardless of the previous choice, the successful uptake of a natural language interface will largely depend on the culture of the market in which you operate. Messaging might become the dominant model of interacting with the world, as Uber DevEx lead Chris Messina predicts in his clarion call to #ConvComm. However, this culture isn't yet universal by any means - and there are, of course, major generational differences around messaging behaviours.

Someone at Google really likes sneakers: The company has just bought a French machine learning startup that taught a computer how to recognize 15,000 different types of them. Paris-based Moodstocks builds image and object recognition software using deep learning techniques, and offered an Android app and visual search API that could recognize certain kinds of object. By analyzing video from a smartphone camera, and correlating it with accelerometer readings to determine how the camera is moving around, the software is able to infer information about the three-dimensional shape of objects in the video, facilitating their recognition. In February 2015 the company demonstrated its ability to identify sneakers through its app. Three months later, after training the software using 15,000 photos of shoes from an online retailer's website, Moodstocks claimed to be able to shop online for all the sneakers on sale in a Macy's store. Google has been introducing elements of machine learning into its existing online services, including Google Translate and Inbox, a next-generation interface for Gmail.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

The artificial intelligence software is learning how to recognize early signs of two eye diseases.Video provided by Newsy A link has been sent to your friend's email address. The artificial intelligence software is learning how to recognize early signs of two eye diseases.Video provided by Newsy Newslook