You can get a pretty good idea of a country's wealth by seeing how much it shines at night -- just compare the intense brightness of China and South Korea to the dark mass of North Korea that's sandwiched between them. But nighttime lights don't tell you which neighborhoods or villages within a large region are merely poor and which are home to people living in abject poverty. That's the level of detail policymakers need when they decide where to deploy their economic development programs. You could get that detail by sending legions of survey-takers into crowded slums and sparsely populated rural areas. But that would be hugely time-consuming and cost tens of millions of dollars or more.

It is fairly straight-forward to build chatbots that send reminders, ask (and record) basic information, and answer common questions. For example, the US government tracks veterans who are receiving chemotherapy and recovering at home. Particular inputs to an automated system can trigger human support systems to get more involved. This can be a useful way of generating training data but that training data is a byproduct of the real goal, which is to help individual, caregivers, and healthcare providers to give the best care possible. AI doctors are unlikely to replace doctors anytime soon–neither the technology nor society are ready for that.

Machine learning is technology which trains software so developers don't have to code it by hand. The number of new companies in the category has grown exponentially over the past few years. Here are 10 machine learning startups worth a closer look. Machine learning companies are being snapped up in droves by tech giants cognizant that these startups represent a new wave of technology innovation. This month alone, Intel announced plans to acquire deep learning startup Nervana Systems.

When was the last time you asked your computer something? There's Siri, Google, and Cortana of course, but these systems, clever as they may be, are the thin end of a newly emerging wedge of remarkable new approaches to computer learning and marketing. If you need proof that we are entering a new era of machine learning and artificial intelligence (AI) you need to look no further than Google's DeepMind project. Early this year DeepMind, Google's AI computer, developed initially in London, challenged and beat South Korean Grandmaster Lee Sedol at the ancient game of Go. Why this challenge is so important requires you to think back to the Deep Blue computer, which finally beat Gary Kasparov at chess in the 1990s. Deep Blue had it easy.

WHEN Germany occupied Poland during the second world war, a young Pole was scratching a living under false papers as a car mechanic. The man, Stanislaw Lem, who was to become one of world's most famous science fiction writers, used to "mend" German vehicles so they would break down. The habit never left him. With Summa Technologiae, his masterwork of non-fiction which has been translated into English for the first time, Lem has taken Western civilisation for a spin – with spectacular consequences. The book will be a fabulous shock to those who know only his science fiction, such as Solaris or The Cyberiad.

From picking our favorite restaurants to predicting weather and correcting global food shortages, artificial intelligence is already augmenting everyday life. Firmly rooted in the realm of science fiction, artificial intelligence (AI) has often felt external – something happening out there. In reality, AI is a huge part of our everyday lives. We just don't recognize it. Bank alerts of suspected fraudulent charges, smartphone notifications to exercise, Siri or Cortana's ability to recognize voices – are all examples of AI. "Artificial intelligence is basically where machines make sense, learn, interface with the external world, without human beings having to specifically program it," said Nidhi Chappell, director of machine learning at Intel. AI improves lives in many other areas too.

Artificial Intelligence Marketing used to be a concept only speculated about in science fiction movies. Who would've thought that in 2016, it would start to play a real role in our daily lives? Because of the wide reaching applications of Artificial Intelligence, marketers must take note and determine ways to use it to their advantage. AI presents marketers with the unique opportunity to run campaigns in a way that have previously never been done or even thought of. This data driven, personal touch will allow marketers to get quite personal with the audience.

I read an interesting article about Google using their DeepMind AI system to improve their power usage efficiency by 15% – which adds up to hundreds of millions of dollars of savings. Of course, DeepMind has been a big investment for Google and finding areas for them to gain efficiency leads to immediate payback – not necessarily covering the entire investment, but savings that add up over time to those hundreds of millions. Like any good organization, I'm sure that Google started with metrics so they had a handle of not just what the costs were, but where the biggest cost impacts were occurring. As the saying goes, "you can't change what you don't measure". However, a lot of organizations get stuck in metrics mode and never get around to the work of actually optimizing – they are are always measuring but never changing.

At Gigaom Change Leader's Summit 2016 in September, we will be exploring seven key business technologies that are real today. In anticipation of that event, we are doing a series of short pieces on the featured technologies. In 1950, Alan Turing asked the question of whether a machine can think. In 1955, John McCarthy coined the term "Artificial Intelligence." In 1956, a group consisting of McCarthy and three other AI scientists proposed a summer retreat to work out the essentials of the new field.

The Chinese military is looking to adapt its technology with the belief that future combat missions will require weapons to be both cost-efficient and flexible. They will also be based on a modular design, which will allow the missiles to be configured in regards to what mission they will be carrying out. "We plan to adopt a'plug and play' approach in the development of new cruise missiles, which will enable our military commanders to tailor-make missiles in accordance with combat conditions and their specific requirements," Wang Changqing of the China Aerospace and Industry Corp told China Daily newspaper. He added that Chinese engineers had been researching the use of artificial intelligence in cruise missiles for a number of years and that the country was the world leader in this field. However, he did not produce any evidence to back up his claims.