With a historic net neutrality vote set to take place tomorrow, people across the United States are rightly concerned about the future of the internet. Visions of price-tiered online spaces dancing in their heads, constituents all over the country are reaching out to their elected officials in a likely doomed effort to forestall what many see as the inevitable destruction of our mostly level digital playing field. But tomorrow's vote is about more than whether Comcast can charge you extra for streaming movies on Netflix. Just as the internet has seeped into many unexpected facets of our lives, abandoning net neutrality could have unexpected consequences in places you might not expect. If Elon Musk is correct, driverless cars could soon be everywhere.
A driverless car system under development at Apple has been showcased to a select group of machine learning experts. The firm's director of AI is reported to have shared secret details of its ongoing automated motoring projects at an industry event. This is believed to included the tech company's self-driving technology that uses laser sensors, called'VoxelNet', to spot cyclists and pedestrians. A driverless car system under development at Apple has been showcased to a select group of machine learning experts. The firm's director of AI is reported to have shared secret details of its ongoing automated driving projects at an industry event'VoxelNet' was first revealed in a paper, submitted on November 17 to independent online journal arXiv, by Yin Zhou and Oncel Tuze.
Autonomous driving systems are changing the way we think about the future of personal transportation. How soon will we have access to vehicles that don't require human control? Are driverless cars just around the corner? What will our travel be like if we're spending a lot less time behind the wheel? What technology actually makes autonomous driving possible?
Deep learning, an advanced machine-learning technique, uses layered (hence "deep") neural networks (neural nets) that are loosely modelled on the human brain. Machine learning itself is a subset of Artificial Intelligence (AI), and is broadly about teaching a computer how to spot patterns and use mountains of data to make connections without any programming to accomplish the specific task--a recommendation engine being a good example. Neural nets, on their part, enable image recognition, speech recognition, self-driving cars and smarthome automation devices, among other things. However, the success of deep learning is primarily dependent on the availability of huge data sets on which these neural nets can be trained, coupled with a lot of computing power, memory and energy to function. To address this issue, says a 14 November press release, researchers at the University of Waterloo, Canada, took a cue from nature to make this process more efficient, thus making deep-learning software compact enough to fit on mobile computer chips for use in everything from smartphones to industrial robots.
While Apple hasn't hid its self-driving car ambitions, until now, little has been known about the mysterious project. But now, computer scientists at the firm have posted a paper online, shedding light on how the self-driving cars could work. The paper reveals that Apple's self-driving cars can better spot cyclists and pedestrians using laser sensors, in a new software approach called'VoxelNet.' While Apple hasn't hid its self-driving car ambitions, until now, little has been known about the mysterious project. Self-driving cars often use a combination of normal two-dimensional cameras and depth-sensing'LiDAR' units to recognize the world around them.
The most dangerous part of any car, say the experts, 'is the nut behind the steering wheel'. Human error is to blame for most accidents, so remove that'nut' and let the car drive itself and many lives will be saved, runs the argument now pushed by ministers, manufacturers and supporters of what is known as'autonomous driving'. And it certainly seems as if it's full speed ahead for the driverless car. The Prime Minister Theresa May and Chancellor Philip Hammond yesterday confirmed plans -- widely trailed ahead of the Budget tomorrow -- to invest £900 million to deliver'fully driverless cars' by 2021. But is the Government right to be putting its foot on the accelerator?
But if you were being very precise--if you were a team of Massachusetts of Technology researchers who study human-machine interactions--you wouldn't say that all those Americans are "driving," exactly. The new driver assistance systems on the market--like Tesla's's Autopilot, Volvo's's Pilot Assist, and Jaguar Land Rover's InControl Driver Assistance--mean that some of those travelers are doing an entirely new thing, participating in a novel, fluid dance. The human handles the wheel in some situations, and the machine handles it in others: changing lanes, parking, monitoring blind spots, warning when the car is about to crash. We might need a new word. Fully autonomous cars won't swarm the roads en masse for decades, and in the meantime, we'll have these semiautonomous systems.
Street signage is the iconography of the automobile age. It's like highly functional pop art: silhouettes of schoolchildren, white arrows, rectangular cries of WRONG WAY and, most central of all, the ubiquitous stoplight. The traffic light might be the first part of that iconographic world to be transformed, or vanish altogether, once we are fully in the age of autonomous cars. Robots, after all, won't need signs to optimize the way they move through urban landscapes. Urban-transportation experts have been busily creating computer simulations to show how this might work.
Next month in San Francisco, Uber will stand trial in federal court for allegedly cheating in the race to commercialize self-driving cars. Google parent Alphabet accuses Uber of stealing designs for sensors called lidars that give a vehicle a 3-D view of its surroundings, an "unjust enrichment" it says will take $1.8 billion to heal. Meanwhile in Toronto, Uber has a growing artificial-intelligence lab led by a woman who's spent years trying to make lidar technology less important. Raquel Urtasun joined Uber to set up a new autonomous-vehicle research lab in May--almost three months after Alphabet filed suit. She still works one day a week in her old job as an associate professor at the University of Toronto.
You're lying on your stomach, with your arms draped forwards, almost like you're going to get a shoulder massage. Except this is not a moment for relaxation. Through a VR headset, you see flashes of color, an unfamiliar view of the world, a group of red lines that looks something like a person. And now you have to make a decision, because you're rolling forward, head first, and your right hand is wrapped around the joystick that determines which way you're going. Do you continue forward, and risk hitting that blob that might be a human being?