Silicon Valley’s leaders were experiencing a rare and remarkable paroxysm of self-doubt.
It wasn’t just their sense that they’d poorly deployed their wealth or that, cloistered on the West Coast, they’d misjudged the electorate. They were also coming to wonder if they’d helped create the circumstances that led to Trump’s rise.
After the election, Mark Zuckerberg acknowledged Facebook’s role in polarizing citizens by surfacing articles that reinforced their worldviews.
Faced with accusations that Twitter had helped Trump set up a one-man propaganda machine, Ev Williams, the company’s co-founder, told The New York Times, “If it’s true that he wouldn’t be president if it weren’t for Twitter, then yeah, I’m sorry.”
As it became clearer that Silicon Valley’s incessant disruption of older industries contributed to the numbers of underemployed, underpaid Rust Belters who’d helped put Trump in office …
Daimler, which has annual sales of 153 billion euros ($181 billion), said it did not plan to divest any of its divisions and no final decision on the legal split had been made.
Under the proposals, Daimler would be split into three independent stock corporations with their own management and supervisory boards capable of signing cross-shareholding agreements with any partners, a person familiar with the matter said, without giving more details.
Supply firms have flocked to China’s booming aerospace sector, which is looking to supply parts faster and cheaper in a competitive global market. China’s exports of parts to the U.S. aerospace industry have trebled to $1.2 billion since 2009, U.S. trade data show.
The demand has fueled the rise of smaller makers of airplane parts in an industry that has been dominated by state-owned firms.
China’s aerospace industry isn’t just a supplier to foreign plane makers. Its airlines are among the biggest buyers of Boeing and Airbus (AIR.PA) planes, but China is now building its own passenger jets, flying its first narrow-body C919 plane in May.
Once people cease to drive, what do they do? A new market will open up, called the “Passenger Economy,” a term coined by Intel® CEO Brian Krzanich.
Different applications, markets, and businesses can shoot out of this inflection point in how we carry out our lives. Consumer services such as entertainment, advertising, and personal or financial services might be carried out inside autonomous vehicles as people travel to work.
Intel’s Katherine (Kathy) Winter, Vice President and General Manager of the Automated Driving Division, deliberates a passenger economy and the new markets it will incite. “It’s probably the smaller piece right now, but mostly because we can’t imagine what it is yet,” she states. Winter suggests that this portion of the passenger economy would include “the new services that a person in an [autonomous] vehicle could be consuming; something [like] entertainment, education, advertising, things like that.”
Today, the half-life of a learned skill is reducing at a significant rate. According to John Seely Brown, co-author of the book, The New Culture of Learning, it stands at approximately 5 years. This means that much of what you learned 10 years ago is obsolete, and half of what you learned 5 years ago is irrelevant, no matter what industry you work in.
One of the reasons people fail to learn quickly is that they don’t build a solid enough foundation. They paralyze their progress by forcing themselves to move past concepts they haven’t yet mastered. If you can’t get an “A” grade in arithmetic, you shouldn’t progress to algebra — otherwise you’ll struggle trying to learn calculus.
Whether you need to jump start a job search, climb the ladder, or excel in your current role, it’s always a good idea to expand, hone, and refresh your skills. This is where Ciena can help.
I’m so excited to tell you about Ciena Learning’s new Discover Series, an entire library of free, self-paced learning courses for our industry.
With respect to surveillance solution integrators, these projections are deceptively low. Integrators face not only an increase in unit sales but also a rise in the performance levels each solution must support.
Surveillance industry trends point to IP-based communications replacing analog, an increasing number of surveillance streams feeding into network-based storage servers/appliances, and a rising number of cameras supporting ever higher resolution. Within the traffic surveillance market, increasing image resolution can be particularly critical, as cameras tend to be located a significant distance from passing vehicles.
Only higher resolution (backed by high-quality image sensors) will deliver the level of detail necessary to identify information such as license plate characters, car body damage, or driver facial features.
Higher image resolution requires higher video stream bandwidth and storage requirements.
Trucks are by far the single most-used mode to move freight around the country, moving 63 percent of the total tonnage in 2015. Nearly 18.1 billion tons of goods worth about $19.2 trillion moved on our nation’s transportation network in 2015, based on current Freight Analysis Framework 4 (FAF4) estimates.
Driver shortages and necessary safety regulations that limit time behind the wheel make fully autonomous trucks (ATs) that much more attractive. Regulations restrict the number of hours that commercial truck drivers can work. Drivers transporting property cannot drive more than 11 hours before taking ten consecutive hours off.
LIDAR (Light Detection and Ranging) sensors are key to self-driving cars, as they are the real eyes of the system, lending depth perception to the process of decision-making in driving.
Late-model LIDAR sensors are about the size of a coffee can. A LIDAR sensor visualizes the world in 360 degrees, bouncing pulsed laser beams off nearby objects all around it to create a 3D map of the real world in real time.
LIDAR sends a fixed train of light pulses to a target, with a known time interval between pulses. The pulse train hits an object in its path and returns a portion to the LIDAR. The system can measure the time of flight (ToF) of the pulses with an accurate range and speed. However, LIDAR is not perfect. LIDAR can be susceptible to failures associated with sunlight and nearby LIDAR sensors.
The LIDAR industry’s struggle to keep up with orders is causing lead times as long as six months.
For Maria Gini, the greatest advantage distributed systems offer is robustness. “If I’ve built my [distributed] system properly, if one robot breaks other robots can still do the work. Whereas if I have a central system then if one robot breaks maybe the system doesn’t know and if it does know it has to reallocate everything.
“Centralized systems produce better quality solutions, but they aren’t as robust to failures.
When it released its first open-source system on a chip, the Freeform Everywhere 310, last year, Silicon Valley startup SiFive was aiming to push the RISC-V (“risk five”) architecture to transform the hardware industry in the way that Linux transformed the software industry.
Now the company has delivered further on that promise with the release of the U54-MC Coreplex , the first RISC-V-based chip that supports Linux, Unix, and FreeBSD.
This latest development has RISC-V enthusiasts particularly excited because now it opens up a whole new world of use cases for the architecture and paves the way for RISC-V processors to compete with ARM cores and similar offerings in the enterprise and consumer space, overcoming what Kang said is was a big criticism as far as the quality of the RISC-V architecture. Now applications such as AI and machine learning and IoT devices can be developed using open-source chip hardware.