Mobile World Congress 2017 -- Telef--nica has taken a bold leap into the age of artificial intelligence with its launch today of a new digital assistant called Aura, which appears to be the product of a two-year research initiative at the Spanish telco that has been a closely guarded secret. Unveiled in Barcelona on the cusp of this year's Mobile World Congress, Aura sounds and works much like Apple Inc. (Nasdaq: AAPL)'s Siri or Amazon.com Inc. (Nasdaq: AMZN)'s Alexa, allowing customers to check on details of their Telef--nica service -- and ask for problems to be resolved or new features to be provided -- using a voice interface on a mobile device. Judging by the demonstration at Telef--nica's offices in Barcelona, Aura works at least as effectively as the digital assistants developed by the web giants but differs in one important respect: It stores and can act upon all of the information about a particular user that is relevant to his or her relationship with the operator. In fact, Telef--nica balks at the "digital assistant" label, preferring to think of Aura as a "cognitive intelligence" system than a neat bit of voice-recognition software.

Opinions expressed by Forbes Contributors are their own. The author is a Forbes contributor. The opinions expressed are those of the writer. Unless you've been on a sabbatical deep in the rainforests of Peru, you've probably heard about Artificial Intelligence (AI). But if you still relate it to all things science fiction and robotic, it's time to look further.

The first autonomous car race, named Roborace, occurred this weekend in Buenos Aires, Argentina, as a prelude to the Formula E championship. Two self-driving racecars took to the track, but sadly one crashed before the race ended. The Devbot electric vehicle misjudged a corner while travelling at over 150km/h, faster than most self-driving car tests carried out by Google, Tesla, and other automakers. "One of the cars was trying to perform a manoeuvre, and it went really full-throttle and took the corner quite sharply and caught the edge of the barrier," Roborace's chief marketing officer Justin Cooke told the BBC. "It's actually fantastic for us because the more we see these moments the more we are able to learn and understand what was the thinking behind the computer and its data."

For the first time ever, self-driving race cars zoomed through a course in public, with impressive (well, for one of them, anyway) results. Roborace, the self-driving racing series Formula E announced in 2015, made history with its first public trial race at the Buenos Aires ePrix last weekend. The two competitors: Devbots 1 and 2, which raced each other in a sprint around the Puerto Madero street circuit. Roborace says the winning Devbot 1 hit a top speed of 186 kph (115 mph) during the contest. Formula E's normal manned cars can reach about 225 kph (140 mph), not waaay faster than the self-driving car.

Fans attending Formula E's Buenos Aires ePrix got a nice treat: the first'race' between self-driving cars on a professional track, courtesy of a test from Roborace. Only... it didn't quite go according to plan. Roborace's two test vehicles (known as DevBots) battled it out on the circuit at a reasonably quick 115MPH, but one of the cars crashed after it took a turn too aggressively. The racing league was quick to tout the safety advantages of crashing autonomous cars ("no drivers were harmed"), but it's clear that the tech is still rough around the edges. Not that Roborace is likely to dispute the need for improvement -- that's what a test like this is for.

Brain Tunnelgenix Technologies Corp (BTT Corp) is a med-tech company with offices in the US and Brazil. They have a biological discovery patent on the Brain Thermal Tunnel and are developing several solutions around this to help improve your health through continuous monitoring of your brain temperature. BTT treats brain temperature like a multichannel signal and uses this to perform analysis and pattern recognition to further insights into customers' health on a personalized basis. Join Jerry Nixon as he welcomes Robert Ortega, CTO of BTT Corp, and the team from Microsoft – David Crook and Yun Chou - as they discuss how by working together they developed an Azure IoT solution to help with brain thermal tunnel pattern recognition. If you're interested in learning more about the products or solutions discussed in this episode, click on any of the below links for free, in-depth information:

In the hope of bringing internet access to even the most remote corners of the globe, Google parent Alphabet's'Loon' project has taken a big step closer. Alphabet said artificial intelligence-infused navigation software has significantly sped up plans, helping to smartly guide high-altitude balloons to improve coverage. While the firm has not said when it expects the balloons to be up and running, Astro Teller, head of the team at Alphabet unit X said: 'We are looking to move quickly, but to move thoughtfully.' Alphabet said artificial intelligence-infused navigation software has significantly sped up plans, helping to smartly guide high-altitude balloons to improve coverage. Teller said: 'Our timelines are starting to move up on how we can do more for the world sooner.'

Data and analytics leaders face a dilemma. Without data scientists, venturing into machine learning and data science is difficult. Without any successful pilots, convincing the business to hire data scientists is equally challenging. Enterprises don't have to have a large data science lab in order to take advantage of machine learning. "Many organizations are still in the early phases of their data science journey and struggle to understand what machine learning and data science can do for them," says Cindi Howson, research vice president at Gartner.

A nonprofit group is testing this drone to see how fast it could get medications from a town to a remote village in Peru that's six hours away by boat. A nonprofit group is testing this drone to see how fast it could get medications from a town to a remote village in Peru that's six hours away by boat. If a snake bites you in a remote Amazonian village like Pampa Hermosa, Peru, and the local doctor is out of the right anti-venom, it might be wise to prepare some goodbyes. The nearest resupply, in a town called Contamana, is up to six hours away by riverboat, and you might not last that long. But you might last 35 minutes, the travel time between Pampa Hermosa and Contamana as the drone flies. A single unmanned aerial vehicle or UAV could dart over the lush canopy with a vial of lifesaving anti-venom, and a nonprofit called WeRobotics is trying to make that a reality.

Future projection of climate is typically obtained by combining outputs from multiple Earth System Models (ESMs) for several climate variables such as temperature and precipitation. While IPCC has traditionally used a simple model output average, recent work has illustrated potential advantages of using a multitask learning (MTL) framework for projections of individual climate variables. In this paper we introduce a framework for hierarchical multitask learning (HMTL) with two levels of tasks such that each super-task, i.e., task at the top level, is itself a multitask learning problem over sub-tasks. For climate projections, each super-task focuses on projections of specific climate variables spatially using an MTL formulation. For the proposed HMTL approach, a group lasso regularization is added to couple parameters across the super-tasks, which in the climate context helps exploit relationships among the behavior of different climate variables at a given spatial location. We show that some recent works on MTL based on learning task dependency structures can be viewed as special cases of HMTL. Experiments on synthetic and real climate data show that HMTL produces better results than decoupled MTL methods applied separately on the super-tasks and HMTL significantly outperforms baselines for climate projection.