Perhaps the home of the future will be filled with robots. Or maybe that home itself will be a robot. That's the vision some technologists have for the future of domestic living, and a startup called Brain of Things announced Thursday that it is developing what the company's founder refers to as "robot homes" in three locations in California. These apartments come with a stunning array of sensors and automated fixtures and appliances. They also have the ability to learn and adapt to residents' habits and preferences to an almost creepy degree, thanks to computer servers that collect data and use it to build models of behavior using machine-learning algorithms.

Inside a modest-looking office building in Tokyo lives an unusually clever industrial robot made by the Japanese company Fanuc. Give the robot a task, like picking widgets out of one box and putting them into another container, and it will spend the night figuring out how to do it. Come morning, the machine should have mastered the job as well as if it had been programmed by an expert. Industrial robots are capable of extreme precision and speed, but they normally need to be programmed very carefully in order to do something like grasp an object. This is difficult and time-consuming, and it means that such robots can usually work only in tightly controlled environments.

Google's AlphaGo software has defeated human Go grandmaster Lee Sedol 4-1 in a five-game series. Despite Lee coming back to win the fourth game (see page "Machine outsmarts man in battle of the decade"), for many the realisation of what was taking place was stark. "I didn't think AlphaGo would play the game in such a perfect manner," Lee admitted in shock. The showdown has drawn eyes from around the world – 30 million people watched it in China alone. Like Deep Blue checkmating chess grandmaster Garry Kasparov, or Watson answering questions on Jeopardy!, it represents a milestone in our relationship with machines.

A fast-food chain with restaurants in 28 states is getting ready to start serving burgers and fries in Champaign-Urbana. Bruce Kim, director of franchise development for Checkers and Rally's Restaurants, said the company is in the process of awarding a franchise for up to three new Checkers restaurants in the area. "We are a quick-service restaurant," he said. "We are known for our seasoned, seared and grilled burgers; fries; grilled, all-meat hot dogs; crazy good chicken wings; golden fish sandwiches; and ice cream. "Our seasoned fries were named the best fries for 2015 by Yahoo." Kim said Checkers restaurants typically stay open late, with most of them serving customers in their double drive-thru until 2 or 3 a.m. The Tampa, Fla.-based chain has 828 locations nationwide, and the website Thrillist recently named Checkers the fastest-growing fast-food chain in Illinois. Kim said the chain is up to 20 Checkers restaurants and seven Rally's restaurants in the state, and the next step is to start building stores in Champaign County. "There is plenty of room to grow, and we are trying to build several locations in Champaign-Urbana," Kim said. "Our studies show we have room for three stores, with our growth franchise-driven." "The community has a good, solid income base, good ethnic diversity and lots of university students.

Some time ago I started a journey into one of the most exciting fields in Computer Science -- Machine Learning. This is my subjective guide for anyone who would like to explore this topic, but don't know how to start. Your first steps should lead to Stanford Machine Learning class at Coursera by Andrew Ng. This course is simply brilliant! Along a way, you will be given everything you need to know, including algebra review.

Digital expertise will become increasingly critical in the insurance sector as digitization and machine learning leads to more highly'automatable' insurance according to management consultants McKinsey & Company. Meanwhile a separate piece of research by Accenture found that insurance companies are accelerating the shift to a radically different distribution model, where they say digital will play an increasingly important role in most interactions, and were agents' efforts are being refocused to add more value. And analysis by research outfit Ovum suggests strong investment in digital channels also. According to Ovum, " When it comes to investment, digital channels remains the top area for insurers. However, the significant majority of insurers will be increasing budgets across a broad range of functional areas with no single activity completely dominating spend. This reflects the complex set of priorities that IT groups are being asked to meet by the wider business, simultaneously addressing revenue growth, operational efficiency and regulatory compliance."

We at Venture Scanner are tracking 957 Artificial Intelligence companies across 13 categories, with a combined funding amount of 4.8 Billion. The 15 visuals below summarize the current state of Artificial Intelligence. Deep Learning/Machine Learning (General): Companies that build computer algorithms that operate based on their learnings from existing data. Examples include predictive data models and software platforms that analyze behavioral data. Deep Learning/Machine Learning (Applications): Companies that utilize computer algorithms that operate based on existing data in vertically specific use cases.

"Really, the only game left after chess is Go," was how Demis Hassabis set the scene ahead of AlphaGo's match with world champion Lee Sedol earlier this month. Either Hassabis's copy of the latest Street Fighter didn't get delivered on time, or he was trying to be a little poetic to mark the occasion. Either way, you'd be forgiven for thinking there really were no games left to conquer after the media reaction to AlphaGo winning the first three games in a best-of-five against its human opponent. It's been a curious month to be an AI researcher. Watching the contest, which AlphaGo eventually won 4-1, I've learned a lot about Go and one of the most interesting things is how the spaces left empty on the board can often be as important and meaningful as the spaces where stones are played.

Humans have been taking a beating from computers lately. The 4-1 defeat of Go grandmaster Lee Se-Dol by Google's AlphaGo artificial intelligence (AI) is only the latest in a string of pursuits in which technology has triumphed over humanity. Self-driving cars are already less accident-prone than human drivers, the TV quiz show Jeopardy! is a lost cause, and in chess humans have fallen so woefully behind computers that a recent international tournament was won by a mobile phone. There is a real sense that this month's human vs AI Go match marks a turning point. Go has long been held up as requiring levels of human intuition and pattern recognition that should be beyond the powers of number-crunching computers.

Editor's note: This is the third in a series of articles about the effects of software and automation on the economy. You can read the other stories here and here. The way Hod Lipson describes his Creative Machines Lab captures his ambitions: "We are interested in robots that create and are creative." Lipson, an engineering professor at Cornell University (this July he's moving his lab to Columbia University), is one of the world's leading experts on artificial intelligence and robotics. His research projects provide a peek into the intriguing possibilities of machines and automation, from robots that "evolve" to ones that assemble themselves out of basic building blocks. A few years ago, Lipson demonstrated an algorithm that explained experimental data by formulating new scientific laws, which were consistent with ones known to be true. He had automated scientific discovery. Lipson's vision of the future is one in which machines and software possess abilities that were unthinkable until recently.