On my first day working for MILLA, an autonomous shuttle company, I discovered a shuttle that can drive up to 30 km/h; quite an improvement if you compare it to our competitors at the time driving at 5–8 km/h. At the time, the shuttle was new and there was no GPU yet on it. In case you don't know what a GPU is, here's a quick picture that explains it well: A GPU (Graphic Processing Unit) parallels the processes so operations are done faster. In a self-driving car, this can be super useful for computer vision or point cloud processing. It was first released in video games because of the need to display multiple things at the same time.
The world never changes quite the way you expect. But at The Verge, we've had a front-row seat while technology has permeated every aspect of our lives over the past decade. Some of the resulting moments -- and gadgets -- arguably defined the decade and the world we live in now. But others we ate up with popcorn in hand, marveling at just how incredibly hard they flopped. This is the decade we learned that crowdfunded gadgets can be utter disasters, even if they don't outright steal your hard-earned cash. It's the decade of wearables, tablets, drones and burning batteries, and of ridiculous valuations for companies that were really good at hiding how little they actually had to offer. Here are 84 things that died hard, often hilariously, to bring us where we are today. Everyone was confused by Google's Nexus Q when it debuted in 2012, including The Verge -- which is probably why the bowling ball of a media streamer crashed and burned before it even came to market.
Artificial intelligence (AI) is probably today's hottest tech growth trend. Spending on AI systems will soar from $37.5 billion in 2019 to $97.9 billion in 2023 -- that's a 28.4% compound annual growth rate -- according to estimates by research firm IDC. So it makes great sense for investors to want some exposure to AI in their portfolios. To help you cut through the many investment choices, we asked three Motley Fool contributors who cover the AI space to name their top AI stock pick for 2020 and beyond. The kicker here is that they needed to love their stock pick enough to own it.
The Nuvo-6108GC GPU computer from Neousys was presented to the customer as a suitable solution for their needs, reported to be the world's first'Industrial-grade edge AI GPU computer supporting high-end NVIDIA RTX 2080 graphics card'. The Nuvo-6108GC GPU computer is able to support the heavy power consumption requirements in order to offer reliable GPU computing performance in industrial environments, and has a patented airflow design and multiple storage drives in a compact form factor. To meet the customer's requirements, Neousys provided a bespoke card cage assembly for the specialised graphics card to secure it in place and protect against the shock and vibration that is commonplace with in-vehicle applications. The fact that all this was incorporated in to an in-vehicle box PC made the Nuvo-6108GC from Neousys the perfect all-in-one GPU computing solution for this innovative autonomous vehicle project. To find out more about WMG, University of Warwick's autonomous vehicle project click here.
The new TX-GAIA (Green AI Accelerator) computing system at the Lincoln Laboratory Supercomputing Center (LLSC) has been ranked as the most powerful artificial intelligence supercomputer at any university in the world. The ranking comes from TOP500, which publishes a list of the top supercomputers in various categories biannually. The system, which was built by Hewlett Packard Enterprise, combines traditional high-performance computing hardware -- nearly 900 Intel processors -- with hardware optimized for AI applications -- 900 Nvidia graphics processing unit (GPU) accelerators. "We are thrilled by the opportunity to enable researchers across Lincoln and MIT to achieve incredible scientific and engineering breakthroughs," says Jeremy Kepner, a Lincoln Laboratory fellow who heads the LLSC. "TX-GAIA will play a large role in supporting AI, physical simulation, and data analysis across all laboratory missions."
Apple is planning to drop its existing screen technology across its iPhones, according to a new report. As well as meaning the latest OLED displays will come all of its phones, the technology could allow for radical new designs in the iPhone. Future models could include bendy screens, for instance, or allow them to be controlled in entirely different ways. The LCD display has been a fixture of the iPhone since it was first released in 2007. It has featured in just every model since, until the iPhone X arrived last year.
LG has unveiled the world's first consumer-ready rollable television at the CES 2019 trade show in Las Vegas. The South Korean electronics giant said the "revolutionary form factor" of its Signature OLED TV R will define the next generation of television. A concept for the roll-up screen was first demonstrated at the world's biggest technology showcase in 2016 but it has taken three years to develop a commercially viable version of the television. The Signature OLED forms part of a new trend that has seen manufacturers attempt to diminish the presence of large televisions in the living room when they are not in use. Samsung's answer is Ambient Mode, a setting that blends the screen with the wall behind it when it is on standby.
The Apple Watch's long promised heart features have finally arrived on people's watches. When the Series 4 was announced in September, the company said that it would let people take ECGs and see if their heartbeat is irregular. But it would not be available straight away because it had to be approved by regulators, it said at the time. Now the features have been given clearance by the US Food and Drug Administration and so will finally be available, arriving through a software update. The ECG and atrial fibrillation features are not yet available outside the US, including in the UK.
Raspberry Pi now supports TensorFlow, so you can start your own machine learning projects on the tiny computer. Waymo is beginning to wedge its way into the public transport system in Arizona. AI on Raspberry Pi: The latest version of TensorFlow can now be run on the Raspberry Pi. "Thanks to a collaboration with the Raspberry Pi Foundation, we're now happy to say that the latest 1.9 release of TensorFlow can be installed from pre-built binaries using Python's pip package system," according to a blog post written by Pete Warden, an engineer working on the TensorFlow team at Google. It's pretty easy to install if you've got a Raspberry Pi running Raspbian 9.0 and either Python 2.7 or anything newer than Python 3.4. After that it's only a few simple lines of code, and you're done.
Traffic hell is alive and well in Los Angeles. In 2017, Angelenos were stuck on the road for 102 hours each (more than four full days), costing the city $19.2 billion, according to INRIX's annual global traffic scorecard. Traffic is almost as bad--and costly--in Moscow, Sao Paulo, and London. But this is the 21st century! Can't AI fix these problems by optimizing traffic flow?