In a few seconds, I want you to stop reading this article, and follow the instructions below. Machine learning and artificial intelligence (ML and AI) have seized Tech mindshare in a way few topics have in recent memory. A couple months ago I noticed people talking about artificial intelligence everywhere I looked. According to AI experts, everything from our jobs, to the wars we wage, to the food we eat, to the beer we drink, to the software we write will be affected. Not being one to enjoy surprises, I decided to spend my free time learning as much about the space (and what the future holds) as possible.

The sizeable majority of experts surveyed for this report envision major advances in robotics and artificial intelligence in the coming decade. To what degree will AI and robotics be parts of the ordinary landscape of the general population by 2025? Describe which parts of life will change the most as these tools advance and which parts of life will remain relatively unchanged. These are the themes that emerged from their answers to this question. AI and robotics will be integrated into nearly every aspect of most people's daily lives Many respondents see advances in AI and robotics pervading nearly every aspect of daily life by the year 2025--from distant manufacturing processes to the most mundane household activities. Jeff Jarvis, director of the Tow-Knight Center for Entrepreneurial Journalism at the City University of New York, wrote, "Think'Intel Inside'. By 2025, artificial intelligence will be built into the algorithmic architecture of countless functions of business and communication, increasing relevance, reducing noise, increasing efficiency, and reducing risk across everything from finding information to making transactions. If robot cars are not yet driving on their own, robotic and intelligent functions will be taking over more of the work of manufacturing and moving." Vint Cerf, vice president and chief Internet evangelist for Google, responded, "Self-driving cars seem very likely by 2025. Natural language processing will lead to conversational interactions with computer-based systems. Google search is likely to become a dialog rather than a client-server interaction. The Internet of Things will be well under way by this time and interaction with and among a wide range of appliances is predictable. Third party services to manage many of these devices will also be common."

Let me hear your body talk. A new electronic tattoo picks up on subtle noises inside the human body, including the sound of your heart, muscles and gastrointestinal tract. The skin patch could be used in medical monitoring, to detect irregular heartbeats, for example. It could also act as a human-machine interface to use your voice to control a video games. "Our body generates a lot of different sounds," says Howard Liu at the University of Illinois at Urbana-Champaign.

HAAS Alert is partnering with the city of Chicago to explore integrating HAAS' data with the city's traffic management system in order to, for example, adjust traffic signals in real time. Hohs said the company is also partnering with agencies in Palo Alto, Detroit and Grand Rapids, Mich., and is in talks with the Los Angeles Fire Department. Hohs said that although he is proud of the public safety benefit of HAAS Alert, he is mainly targeting navigation apps and car manufacturers for revenue development. He said he hopes to get his product onto consumers' mobile phones and, eventually, into self-driving cars that will automatically redirect based on the information provided by the app. "We want to get into services that users use every day," he said.

For the first time, a "one stop shop" of the machine intelligence stack is coming into view--even if it's a year or two off from being neatly formalized. The maturing of that stack might explain why more established companies are more focused on building legitimate machine intelligence capabilities. Anyone who has their wits about them is still going to be making initial build-and-buy decisions, so we figured an early attempt at laying out these technologies is better than no attempt. If this year's landscape shows anything, it's that the impact of machine intelligence is already here. Almost every industry is already being affected, from agriculture to transportation.

Ben Dickson is a software engineer and the founder of TechTalks. More posts by this contributor: Why it's so hard to create unbiased artificial intelligence How to facilitate the path to brownfield IoT development Why it's so hard to create unbiased artificial intelligence How to facilitate the path to brownfield IoT development Why it's so hard to create unbiased artificial intelligence The transportation industry is associated with high maintenance costs, disasters, accidents, injuries and loss of life. Hundreds of thousands of people across the world are losing their lives to car accidents and road disasters every year. According to the National Safety Council, 38,300 people were killed and 4.4 million injured on U.S. roads alone in 2015. The related costs -- including medical expenses, wage and productivity losses and property damage -- were estimated at $152 billion.

Scientists have developed a new artificial intelligence system that can more effectively extract data from the vast wealth of information present on the internet. The data necessary to answer myriad questions - about, say, the correlations between the industrial use of certain chemicals and incidents of disease, or between patterns of news coverage and voter-poll results - may all be online in form of plain text. However, extracting data from plain text and organising it for quantitative analysis may be prohibitively time consuming. Researchers from Massachusetts Institute of Technology (MIT) in the US developed a new approach to information extraction. Most machine-learning systems work by combing through training examples and looking for patterns that correspond to classifications provided by human annotators.

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Google Translate is rolling out a major upgrade that promises more human-like language translations. Google is bullish on its Neural Machine Translation technology, claiming that it's a bigger upgrade to the service than everything that's been accomplished in the last ten years combined. The company is rolling out the improvements to eight language pairs in Google search, the Translate apps, and the website. You'll find the new technology behind translations between English and French, German, Spanish, Portuguese, Chinese, Japanese, Korean and Turkish. Google says that makes up more than 35 percent of all language queries.

Last month at Dreamforce, the ultimate Salesforce conference, there was a lot of talk about artificial intelligence and use cases for businesses. Will artificial intelligence be a game changer in the way we interact with our prospective customers? How far do bots go before human engagement takes over? In some ways, artificial intelligence has already changed the world of sales with examples all around us. When Amazon recommends new books or products based on past purchases or when we see a friendly chatbot pop on the screen when visiting a website – these use cases rely on data analysis to predict what you might be interested in, ideally offering timely and helpful information that improves the customer experience.