Bosch and the car manufacturer behind Mercedes, Daimler, have announced they are joining forces “to advance the development of fully automated and driverless driving”.
The two companies are to enter into a development agreement that they say will bring fully automated driving to urban roads by “the beginning of the next decade”.
To do this the two companies will develop software and algorithms that lead to an autonomous driving system.
Posted in robotics/AI, space travel
Erika Ilves is an entrepreneur who does not let herself be limited by the size of planet Earth while there is a whole universe out there. ‘For now, we are developing and training our mining robots on Earth. But in less than a decade they will underpin mining operations on the Moon and beyond,’ she claims.
2008 Disney-Pixar animation WALL-E takes us to planet Earth in 2805, abandoned by people and covered in heaps of trash. There is only one cute robot left whose job is cleaning up the planet. In real life, we do not have to wait another 800 years to see this happen. Robots like this already exist. And if we treat our resources more reasonably, the picture might not turn out be as gloomy as depicted in the movie.
‘Personally, I do not believe we will be running out of resources any time soon. We have plenty of resources on Earth to last us a few centuries,’ says Erika Ilves, cofounder of OffWorld, a company that is developing a new robotic work force to enable the settlement of the solar system. But Erika would not want to be among the first humans to set foot on Mars. Before moving people to other planets, it might be wiser to send robots out there.
Posted in ethics, robotics/AI
Artificial intelligence is not a vague concept we picked up from a science fiction novel. It is the single biggest technology trend since the Internet, and the money-making potential is huge.
Google, Amazon, and Microsoft are all ready to soar on the winds of change. Most people expect it to be a zero-sum game, but their varying strengths will allow them all to succeed.
Microsoft is likely going to own the enterprise segment. Amazon will probably win the consumer device fight, and Google could become a healthcare giant.
Who owns the work?
Man or his machine?
Google Deep Dream learned to make its own art using a machine learning algorithm. A question that must be considered in the future is: who owns art and other creations that AI makes?
And yet, as impressive and powerful as these new technologies and machines are—and they’re becoming more so all the time—I believe they’re an opportunity to be embraced by accountants.
Computers and software have evolved to a point where they can populate spreadsheets, crunch numbers, and generate financial statements and earnings reports more quickly and accurately than any human accountant. In fact, machines are already taking on many of an accountant’s old, routine, administrative chores—on-line tax returns, and book-keeping software, are great examples of routine work that accountants no longer have to do.
This is a good thing. It is already allowing for human accountants to be more sophisticated advisors and planners. In this way, technology can be best used as a tool that gives humans more space to focus on analysis, interpretation, and strategy. In other words, computers have enormous potential to empower—rather than displace—accountants.
We’ve created the world’s first Spam-detecting AI trained entirely in simulation and deployed on a physical robot.
Our vision system successfully flagging a can of Spam for removal. The vision system is trained entirely in simulation, while the movement policy for grasping and removing the Spam is hard-coded. Our detector is able to avoid other objects, including healthy ones such as fruit and vegetables, which it never saw during training.
Deep learning-driven robotic systems are bottlenecked by data collection: it’s extremely costly to obtain the hundreds of thousands of images needed to train the perception system alone. It’s cheap to generate simulated data, but simulations diverge enough from reality that people typically retrain models from scratch when moving to the physical world.
