GETTING computers to recognise other cars is surprisingly difficult. Earlier this year, the first fatal autonomous car crash happened when a Tesla Model S failed to distinguish a white truck against a brightly lit sky. Now a study has shown that self-driving cars can be taught the rules of the road by studying virtual traffic on video games such as Grand Theft Auto V (GTA V). Although firms like Google and Uber are teaching their software by physically driving millions of miles in the real world, they also train their algorithms using pre-recorded footage of traffic. But there's a catch: computers need hundreds of thousands of laboriously labelled images, showing where vehicles begin and end, to make them expert vehicle recognisers.

Carolina Huaranca is making a name for herself in Silicon Valley. During those three intensive days spent brainstorming new technologies, she realized she was not the only one. Huaranca was one of just two Latinos in a room of 100 people. Nonetheless, she gave birth to a start-up -- and a mission: to one day bring together Latinos so they, too, could have a shot at a career in the tech industry. Now as one of Silicon Valley's few Latina venture capitalists, Huaranca is making good on her promise by helping host Startup Weekend Oakland: Latinx Tech Edition.

Machine learning developers who want to use Google's Go language as their development platform have a small but growing number of projects to choose from. Rather than call out to libraries written in other languages, chiefly C/C, developers can work with machine learning libraries written directly in Go. Existing machine learning libraries in other languages have a far larger culture of users, but there's clearly an interest in having Go toolkits that take advantage of the language's conveniences. GoLearn, described as a "batteries included" machine learning library, is one of the most prominent. "Simplicity, paired with customisability, is the goal," the developers write in their introduction to the project.

Microsoft today is announcing the beta launch of version 2.0 of its open-source deep learning framework. Until now, the software has been called Computational Network Toolkit, or CNTK, but now Micorosft is changing the name to Cognitive Toolkit. Instead of just being accessible through the programming language C, Cognitive Toolkit now has native support for Python (specifically Python 3; Python 2 support is coming). The lack of Python has been the single biggest deficiency of Cognitive Toolkit, Microsoft chief speech scientist Xuedong Huang told VentureBeat in an interview. "That's why external adoption has been very small," Huang said.

Artificial intelligence programs have beaten chess masters and TV quiz show champions. Two exchange operators have announced plans to launch artificial intelligence tools for market surveillance in the coming months and officials at a Wall Street regulator say they are not far behind. Executives are hoping computers with humanoid wit can help mere mortals catch misbehaviour more quickly. The software could, for instance, scrub chat-room messages to detect dubious bragging or back slapping around the time of a big trade. It could also unravel complex issues more quickly, like "layering," where orders are rapidly sent to exchanges and then cancelled to move a stock price artificially.

It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. As Big Data is the hottest trend in the tech industry at the moment, machine learning is incredibly powerful to make predictions or calculated suggestions based on large amounts of data. Some of the most common examples of machine learning are Netflix's algorithms to make movie suggestions based on movies you have watched in the past or Amazon's algorithms that recommend books based on books you have bought before. So if you want to learn more about machine learning, how do you start? For me, my first introduction is when I took an Artificial Intelligence class when I was studying abroad in Copenhagen. My lecturer is a full-time Applied Math and CS professor at the Technical University of Denmark, in which his research areas are logic and artificial, focusing primarily on the use of logic to model human-like planning, reasoning and problem solving.

Leaders should always be asking themselves What's new?, What's next? and What's better?; that's where the future is. What technologies will drive the biggest changes in industries over the next 10 to 20 years and create the next economy? There are many that in combination will drive massive change across enterprises and all size of business. Specifically, I think 10 are essential, and shaping the industries of the future: drones, blockchain, big data, augmented reality, virtual reality, 3D printing, artificial intelligence, robots, internet of things, genetics. We will see them both in the consumer and enterprise domain; specifically in how we get stuff done, how we hire and how we collaborate. How might the way we work, hire and collaborate change in the future?

IBM is teaming up with Slack Technologies Inc. to make it easier for companies to build custom chatbots into the startup's workplace-messaging systems, the latest move by Big Blue to add more diverse business cases for its Watson artificial-intelligence technology. The two companies will release a developer toolkit that includes Watson technologies and can integrate easily into Slack, they said in a statement Wednesday. International Business Machines Corp. will also build a chatbot -- a conversation-based application -- that will help IT departments identify and resolve issues without having to leave the Slack platform. The startup's own customer-service bot will incorporate the Watson Conversation system, which includes technologies such as speech-to-text conversion and natural-language processing, or the ability for a computer to understand what a person is saying. "Right now, if you say something to Slackbot in Slack, it will kind of blindly take what you ask it and do a search," Slack Chief Executive Officer Stewart Butterfield said.

Artificial intelligence isn't just being used to automate cars... it's finding a home in conventional cars, too. GM has unveiled a partnership with IBM that will see the Watson cognitive computing platform power OnStar Go, its latest in-car service offering. The AI technology will suggest stores and services based on your location, your decisions and your habits. If you're driving home from work, for example, OnStar can remind you to pick up shopping on the way back. It can also recommend restaurants when you arrive in a new city, or tell you that a store order is ready for pickup.

MIT explains the motives for the project on its site: "Creating a visceral emotion such a fear remains one of the cornerstones of human creativity. This challenge is especially important in a time where we wonder what the limits of Artificial Intelligence are: Can machines learn to scare us?"