Tip One: Do Both Empire State and Top of Rock But do one in the morning and one as the sun is setting to see the city in a different light. I was so grateful for this tip.

A small insurance startup, Root, has launched a car insurance specifically designed for Tesla vehicle owners that reduces the price of the policy the longer the vehicle runs in autonomous mode, on the basis that this mode is much safer than driving manually. Thus, drivers who spend a lot of time on the highway or in conditions where they can activate the autonomous mode will pay less insurance. The idea is based on the fact that a vehicle is increasingly a connected platform, a smartphone on wheels from which we can obtain a constant flow of information. To sign up for a Root policy, which typically offers much lower prices than its competitors, you must download an app that allows the company to access GPS, accelerometers and gyroscopes data on your smartphone, making it possible for the company to evaluate your driving. After about two to three weeks driving with the app, enough for the average driver to forget about the app and go back to his or her typical driving habits, the algorithm has created a user profile that includes how much time the vehicle is in use, frequent destinations, whether drivers change lane excessively, their driving speeds, to what extent they respect traffic rules, or if they use their smartphone while driving, among many other things.

Machine learning is a trending topic today and for good reason. It has enormous potential to transform entire markets and industries. Successful machine-learning startups will be the ones targeting vertical applications with a clear need for the technology. The consumer packaged goods industry is a good example. Machine learning can more accurately predict inventory levels to better manage the supply chain, reduce inventory costs, minimize excess capacity requirements, and eliminate stockouts.

Until a few years ago, computers couldn't tell the difference between images of dogs and ones of cats. Today, computer programs use machine-learning algorithms to study piles of data and learn about the world and its people. Algorithms can tell a banker whether someone will pay back a loan. They can pick the right applicant out of thousands of resumes. They assist judges to determine a prisoner's risk of returning to a life of crime.

At this year's SXSW the theme for our conference tech coverage is "AI for good." Technologists will be discussing how they are using new developments in artificial intelligence to solve complex, long-standing social problems, including crimes against children. Federico Gomez Suarez (pictured), senior technical program manager at Microsoft, spoke to John Furrier (@furrier), host of theCUBE, SiliconANGLE Media's mobile live streaming studio, during SXSW about his involvement in Thorn, a special outfit that works with law enforcement to rescue traffic or exploited children. "The fact that we're making a difference in those lives is extremely encouraging," Suarez said. He credits Microsoft's Hack for Good program for paving his avenue to Thorn.

As business opportunities for artificial intelligence multiply, how can industry leaders design the principles and technical standards into their products that benefit society as a whole?

For Silicon Valley, the headline was sweet nectar: Google DeepMind, the world's hottest artificial intelligence lab, embraces the blockchain, the endlessly fascinating idea at the heart of the bitcoin digital currency. The lab's re-imagining of the blockchain has very little to do with AI--or the blockchain, for that matter. If you want AI crossed with the blockchain, try wrapping your head around Numerai, the world's strangest hedge fund. To DeepMind's credit, its new project depends less on trendy ideas than an apparent desire to solve a real problem in the real world--one that involves the most private and personal information. DeepMind is building an auditing system for healthcare data. That may not sound sexy, but it matters.

The Indus script has long challenged epigraphists because of the difficulty in reading and classifying text and symbols on the artefacts. Now, a Chennai-based team of scientists has built a programme which eases the process. Ronojoy Adhikari of The Institute of Mathematical Sciences and Satish Palaniappan, who is at Sri Sivasubramaniya Nadar College of Engineering, have developed a "deep-learning" algorithm that can read the Indus script from images of artefacts such as a seal or pottery that contain Indus writing. Scanning the image, the algorithm smartly "recognises" the region of the image that contains the script, breaks it up into individual graphemes (the term in linguistics for the smallest unit of the script) and finally identifies these using data from a standard corpus. In linguistics the term corpus is used to describe a large collection of texts which, among other things, are used to carry out statistical analyses of languages.

We're a content intelligence company based in Dublin, Ireland. We make it easy for companies like Sony, Getty Images and Complex Media to collect and understand large volumes of human generated content on the web using Artificial Intelligence, Machine Learning and Natural Language Processing. Our Text Analysis and News APIs enable developers and data scientists to build intelligent content-focused apps and solutions with ease.

Machine learning (ML) technologies and solutions are expected to become a prominent feature of the information security landscape, as both attackers and defenders turn to artificial intelligence to achieve their goals. "The advent of machine learning in security comes alongside the increased capability for collecting and analyzing massive datasets on user behavior, client characteristics, network communications, and more. As we have already witnessed in many other technological domains, I think machine learning will become the main driver for innovation in information security in the coming decade," says security researcher Clarence Chio. Alongside Anto Joseph, a security engineer at Intel, Chio is scheduled to give Hack In The Box attendees a quick and practical introduction to the world of machine learning in April. But, he says in advance, machine learning is no silver bullet.