Choosing what they will work on in the future is a difficult decision that adolescents often make considering their skills and the needs of a job market that in a matter of 5 years can be radically transformed. Beyond the aptitude tests, a Colombian venture states that using artificial intelligence it is not only possible to find out what someone will be good at, but also to bring them closer to their life purpose. That ambitious mission is the dream of Life Design, a professional guidance software that is postulated as a tool of self-knowledge through technology. The company, which started in January 2018, closed the first round of investment of $ 150,000 and has worked with 2,000 active users since October last year. According to Felipe Rojas, one of the co-founders, unlike traditional methods, Life Design's philosophy is not to create only the professionals that the industry needs, but to identify what the student is interested in, their tastes, preferences and skills and then connect them.

Canadian investors have had a lot to digest in the first half of 2020. From oil price wars to a global pandemic, these are dangerous waters to traverse. However, investors should not remain on the sidelines. Today, I want to discuss why an investment in top artificial intelligence stocks could be worth a fortune down the road. In late 2019, I'd discussed why Kinaxis (TSX:KXS) was perfect for investors who wanted exposure to artificial intelligence development.

We were promised robots everywhere -- fully autonomous robots that will drive our cars end-to-end, clean our dishes, drive our freight, make our food, pipette and do our lab work, write our legal documents, mow the lawn, balance our books and even clean our houses. And yet instead of Terminator or WALL-E or HAL 9000 or R2-D2, all we got is Facebook serving us ads we don't want to click on, Netflix recommending us another movie that we probably shouldn't stay up to watch, and iRobot's Roomba. Where are all the robots? This is the question I've been trying to investigate while building my own robotics company (a currently stealth company named Chef Robotics in the food robotics space) as well as investing in many robotics/AI companies through my venture capital fund Prototype Capital. Industrial six degrees of freedom (read as six motors serially attached to each other) robot arms were actually developed around 1973 and there are hundreds of thousands of them out there -- it's just that up to this point, almost all of these robots have been in the extremely controlled environment of factory automation doing the same thing over and over again millions of times. And we've formed many multibillion dollar companies through these factory automation robots including FANUC, KUKA, ABB and Foxconn (yes they make their own robots). Go to any automotive manufacturing plant and you'll see hundreds (or in Tesla's case, thousands). They work insanely well and can pick up massive payloads -- a full car -- and have precision sometimes up to a millimeter.

Researchers at Duke University, North Carolina, have developed a new AI tool that can turn blurry, unrecognisable images of people's faces into eerily convincing computer-generated portraits, in finer detail than ever before. Previous methods have been capable of scaling images up to eight times their original resolution. But the Duke team's algorithm creates realistic-looking faces with up to 64 times the resolution – "imagining" missing features such as fine lines, eyelashes, and stubble – based on just a handful of pixels. "Never have super-resolution images been created at this resolution before with this much detail," said Duke computer scientist Cynthia Rudin, who led the team. The system cannot be used to identify people, the researchers say.

You may be able to help NASA's Curiosity rover drivers better navigate Mars. Using the online tool AI4Mars to label terrain features in pictures downloaded from the Red Planet, you can train an artificial intelligence algorithm to automatically read the landscape. Is that a big rock to the left? AI4Mars, which is hosted on the citizen science website Zooniverse, lets you draw boundaries around terrain and choose one of four labels. Those labels are key to sharpening the Martian terrain-classification algorithm called SPOC (Soil Property and Object Classification). Developed at NASA's Jet Propulsion Laboratory, which has managed all of the agency's Mars rover missions, SPOC labels various terrain types, creating a visual map that helps mission team members determine which paths to take.

The Government is still using a late 20th Century mindset when Britain chose to intervene in the Balkans, Afghanistan and Iraq. "But in 2010, the world began to change," he said. Britain dropped the ball on state competitors, leading to a failure to keep up with Russian and Chinese military technology." He pointed to a defence programme which "isn't enough to allow Britain to make an independent contribution within Nato or any other coalition. "We can't afford even to pay for the things we've kept, and we choose not to see that the list ignores things the Armed Forces knows it will need to go to war at a state level.

Today's smart-lighting systems still must be set up manually by the user. The OpenLicht project has developed a prototype for a more intelligent lighting system... German research project OpenLicht has successfully developed a smart-lighting system based on open-source software and machine-learning libraries, plus inexpensive hardware, that can automatically adjust lighting in a room based on what the user is doing. Today's smart-lighting solutions are based on smart bulbs such as the Philips Hue and Osram Lightify. While they offer some smart features, they generally require manual control by the user via a smartphone app. Some can be programmed (for example, to turn on and off at certain times), but the rules still have to be set up manually, so the basic relationship between user and lighting system is not changed by making it smarter.

Three images from the tool called AI4Mars show different kinds of Martian terrain as seen by NASA's Curiosity rover. By drawing borders around terrain features and assigning one of four labels to them, you can help train an algorithm that will automatically identify terrain types for Curiosity's rover planners. Using an online tool to label Martian terrain types, you can train an artificial intelligence algorithm that could improve the way engineers guide the Curiosity rover. You may be able to help NASA's Curiosity rover drivers better navigate Mars. Using the online tool AI4Mars to label terrain features in pictures downloaded from the Red Planet, you can train an artificial intelligence algorithm to automatically read the landscape.

Robotic interaction could facilitate more socially distanced models of operation to enable a safer and faster reopening and recovery of some hotels impacted by the COVID-19 outbreak, according to researchers. The researchers, including those at the University of Surrey in the UK, spoke to 19 hotel human resource (HR) experts to identify the key trends and major challenges that will emerge in the next ten years. They said while service robots are anticipated to increase efficiency and productivity of hotel activities, they may also pose challenges such as high costs, skill deficits and significant changes to the organisational structure and culture of hotels. The anticipated applications and integration of robotic technology will require leaders of the future to carefully consider the balance between the roles of service robots and human employees in the guest experience, according to the paper published in the International Journal of Contemporary Hospitality Management. The researchers noted that their project completed in March 2020 just as COVID-19 broke out and as the virus rendered non-essential travel impossible, most hotels around the globe are feeling a catastrophic economic impact.

Made your mind towards machine learning but are confused so much that where to get started? I faced the same confusion that what should be a good start? Should I learn Python or go for R? Mathematics was always a scary part for me, and I was always worried that from where should I learn math? I was also worried about how I should get a strong basis for Machine Learning. Anyway, you should be congratulated that at least you have made your mind.