Tesla is making several big announcements this month, and Elon Musk just delivered the first: From now on, all new Tesla cars will be self-driving. The electric automaker also teamed up with Panasonic to build solar panels for its Powerwall home battery, which it's set to update next week. Hyperloop One is forging ahead on its futuristic transportation system by raising 50 million and hiring Uber's former CFO as an advisor. It looks like Apple has scrapped plans to build a self-driving car, and BMW showcased plans for a next-gen smart motorcycle that will never crash or tip over. In energy news, scientists accidentally discovered a cheap, simple way to transform CO2 into ethanol fuel.

Removing the battery from an off-the-shelf drone, the researchers attached a copper ring to the drone's electronics. Then, a transmitter on the ground connected to a power supply made a magnetic field. When the drone flew into the field, hovering at a distance of no more than 4 inches above it, it was able to draw power from that field, and convert it into direct current to power the small flying machine. The technology is still constrained by the narrow gap between drone and charger; 4 inches away from the charger is better than being plugged into it, but it's not a ton of space. Still, the team at Imperial College London seems confident in the results, floating concepts for drones that charge over power lines, drones that charge other drones, and even inductive charging stations that can land on Mars to recharge tired robotic rovers.

This post is by Joseph Sirosh, Corporate Vice President of the Data Group at Microsoft. We are only 6 days away from PASS Summit 2016 (@sqlpass) which kicks off next Wednesday, October 26th, in Seattle. SQL PASS Summit (#SQLSummit, #sqlpass) is the world's largest and most intensive technical training conference for Microsoft SQL Server (@SQLServer) and BI professionals. But more than that, it's a conference – planned and presented by the SQL Server community for the SQL Server community (#sqlfamily). It has the most technical sessions, the largest number of attendees, the best networking, and the highest-rated sessions and speakers of any SQL Server event in the world.

Anyone remember Rosie, the robotic housekeeper who petered around "The Jetsons" in the 1960s? "I swear on my mother's rechargeable batteries," she once joked, when asked by Judy Jetson to keep a secret. While we're still a few years away from a domesticated humanoid robot that can wash our dishes and make our beds, today's smart home products are designed to make your living space safer, more energy efficient, and easier to maintain. The following is a look at a few smart ways to bump up your home's I.Q. The maker of the first smart thermostat (in 2007) is back with an even more affordable model.

The energy landscape: what is driving change in renewable energy markets? A record 15.2bn was invested in UK clean energy last year. Energy system transformation: where are we at and where are we going? What are the positive economic effects of emerging technology in energy? Hear experts from leading industry players including BP, British Gas and the Centre for Sustainable Energy as they explain the opportunities of applying artificial intelligence and machine learning to manage energy generation and consumption.

The smart energy startup Verdigris announced today that it has raised 6.7 million to scale production of its Einstein smart sensor and frequency detectors. The sensors are used to predict the failure of machines and improve energy efficiency. Factories, manufacturing facilities, and other large buildings using Verdigris technology reduce energy use 8 to 22 percent, CEO Mark Chung told VentureBeat in a phone interview. The Einstein frequency detector from Verdigris made its debut in August. "Rather than take a big data approach where we study thousands of motors and this is the failure pattern, we instead take a physics based model which is looking at a signal through our sensors," Chung said.

Many real-world control applications, from economics to robotics, are characterized by the presence of multiple conflicting objectives. In these problems, the standard concept of optimality is replaced by Pareto-optimality and the goal is to find the Pareto frontier, a set of solutions representing different compromises among the objectives. Despite recent advances in multi-objective optimization, achieving an accurate representation of the Pareto frontier is still an important challenge. In this paper, we propose a reinforcement learning policy gradient approach to learn a continuous approximation of the Pareto frontier in multi-objective Markov Decision Problems (MOMDPs). Differently from previous policy gradient algorithms, where n optimization routines are executed to have n solutions, our approach performs a single gradient ascent run, generating at each step an improved continuous approximation of the Pareto frontier. The idea is to optimize the parameters of a function defining a manifold in the policy parameters space, so that the corresponding image in the objectives space gets as close as possible to the true Pareto frontier. Besides deriving how to compute and estimate such gradient, we will also discuss the non-trivial issue of defining a metric to assess the quality of the candidate Pareto frontiers. Finally, the properties of the proposed approach are empirically evaluated on two problems, a linear-quadratic Gaussian regulator and a water reservoir control task.

I love my garden at home, but the one thing I can't stand: weeds. No matter what I do, the little buggers pop up between all of our plants and vegetables. If I take off for just one weekend, the garden is packed with them. Well, a new startup may just have the answer in the form of a tiny, adorable robot. It's called the Tertill, and its premise is amazingly simple: it's a small, waterproof, solar-powered robot that hangs out in your garden and trims any weeds that it finds as soon as they pop up.

While major tech companies are in a race to develop real-life artificial intelligence applications, self-aware AI might come sooner than you think. Major companies in the tech industry are racing to implement artificial intelligence technology into smartphones and other internet-linked devices in order to make them think like people. CBS News reports that artificial intelligence (AI) projects at Carnegie Mellon aim to bring this emerging technology closed to our daily life. F0r instance, the CMU Highly Intelligent Mobile Platform is a robot designed to perform dangerous tasks in situations that would put humans in too much risk, such as the 2011 disaster in Japan, at the Fukushima nuclear plant. Because CHIMP is designed to be able to work independently in disastrous conditions, it needs both mental and manual good skills.

It does not pay to underestimate a monkey with a rock. Scientists studying the stone-smashing habits of bearded capuchin monkeys in Brazil have found that the primates inadvertently produce stone flakes that look very similar to the flakes used as cutting tools by early humans. The findings, published in the journal Nature, could snarl the links that paleoanthropologists make between early Stone Age artifacts and the emergence of primitive human technology. "It does raise interesting questions about the level of cognitive complexity -- how intelligent a hominin has to be in order to produce what we thought was a sophisticated technology," said lead author Tomos Proffitt, a paleoanthropologist at Oxford University. When anthropologists explore early human settlements, they typically search for signs of tool use, whether by looking at the cuts on butchered animal bones or finding the tools themselves.