The Jetson boards are siblings to NVIDIA's Drive PX boards for autonomous driving and the TX2 shares the same Tegra "Parker" silicon as the Drive PX2. There are many synergies between the two families as both can be used to add local machine learning to transportation. One of my favorite products on display using the Jetson board is a portable handheld 3D scanner from Artec. Key advantages of the Jetson TX2 over the original TX1 are that it adds two additional, higher performing Denver CPU cores to the four Cortex-A57 cores in the TX1, NVIDIA's latest Pascal GPU, and it offers twice the memory capacity and bandwidth.
Expanding on their Jetson TX1 and TK1 products for embedded computing, NVIDIA announced last week their Jetson TX2 platform--a hardware and software platform the size of a credit card designed to deliver AI computing at the edge. NVIDIA touts Jetson TX2 as delivering "unprecedented deep learning capabilities," and based on the form factor, they may be right as it paves the way for a number of cutting-edge uses--from highly intelligent factory robots and commercial drones, to cameras with AI for smart cities. Operating at its maximum performance mode, NVIDIA says it will deliver twice the performance of Jetson TX1, using less than 15 watts of power. Running at maximum energy efficiency mode, NVIDIA says it can achieve twice the energy efficiency of TX1, while using less than 7.5 watts of power.
This year's Game Developers Conference (GDC) set the battleground for another skirmish between long-time Graphics Processing Unit (GPU) foes AMD and NVIDIA. Because this event was held during the Game Developers Conference (GDC), developer tools were an appropriate topic. The "Ti" brand is a traditional NVIDIA mid-life "kicker" product, but with the company's 35% nominal performance increase, this version is the company's most aggressive Ti product yet. The big push for higher performance could be because NVIDIA is anticipating AMD's higher GPU performance with the Vega architecture and wanted to preemptively counter it.
In the near-future, however, AI advances will give rise to increasingly powerful applications like personal assistants with more robust utility in the workplace and in our personal lives. These assistants could provide personalized information, help us make more informed decisions, and perhaps even provide physical assistance. One such technique is transfer learning, which allows AI engineers to apply a trained model to completely new types of problems with little additional training. The computational power to train and run these systems will greatly benefit from hardware innovation, including neuromorphic chips or even quantum computers powerful enough to process diverse information types simultaneously.
Innovation in the white-hot digital performance management (DPM) market continues to accelerate, and it was clear from this week's Perform conference in Las Vegas that Dynatrace is setting the pace. In fact, Coop's mobile application is state-of-the-art, featuring digital payments, couponing, and e-receipts, with in-store location tracking and streaming video content on the way. "We're using davis for everything we can," says Jeppe Lindberg, Application Performance Manager at Coop Denmark. "Coop is working with Dynatrace to deliver relevant data to relevant people inside Slack," Lindberg explains.
A 2017 Chrysler Pacifica hybrid minivan equipped with Waymo's self-driving vehicle technology. Along with better components, Waymo's automated system is performing more reliably in real-world driving, based on the latest annual figures filed with California's Department of Motor Vehicles. Since then it has racked up about 2.5 million test miles in automated mode, and billions of simulated miles, including a billion such miles in 2016 alone, the company said on Sunday. Ride-hailing giant Uber has announced plans to eventually convert its service from human-driven vehicles to fully robotic cars and trucks available on demand, and it garnered attention in September for a test program in Pittsburgh with prototype driverless cars (each with two technicians in the front) and a failed attempt at a similar program in San Francisco (scrubbed after Uber declined to apply for a $150 permit from California's DMV for its fleet).
When it comes to hardware design language, non-Apple/-Samsung phones tend to be all over the place, even within the same product line. Meizu, on the other hand, has stuck with the same design language over at least a half dozen phones released in the past two to three years. That coupled with the quad HD AMOLED display (another jump, as previous Meizu phones mostly used 1080p LCD panels) give this phone a decidedly more premium feel than not just other Meizu phones, but most phones at this price point ($2,999 yuan/US$430). The Pro 6 Plus scored a 112,795 on Antutu (left), which is among the highest of all phones released this year; the phone uses USB-C with Meizu's own fast charge technology that supports up to 24-watt charge (middle); the device scored a 1,469 and 3,471 on Geekbench's single- and multi-core tests.
In our previous analysis, we discussed how Intel is competing with Nvidia in the data center coprocessor market. These computational capabilities make GPUs ideally suited for use as coprocessors in High Performance Computing environments. It is worth noting that GPUs have a parallel architecture with hundreds of cores, making it highly suited for matrix and vector operations in both deep learning and 3D computer graphics. Currently, it is debatable as to which one – Intel's Xeon Phi processor family (formerly code-named Knightsbridge) or Nvidia's Tesla processors – is better in terms of performance.
As tech and auto companies vie for leadership in self-driving vehicle technology, Hyundai Motor's top priority isn't how fast it can be perfected. Unlike heavily modified vehicles being tested by Uber in Pittsburgh and San Francisco (where the ride-hailing giant has sparked a legal fight with regulators) that have bulky rooftop LiDAR sensor and camera rigs, Hyundai's automated driving gear on the Ioniq is well-disguised. "We start with a design that is not overly complex to keep it attainable to the average buyer while still meeting performance requirements," Dipko said. While Tesla Motors intends to add full self-driving capability to its electric vehicles within the next two years or so, most automakers intend to begin deploying autonomous vehicles in the early 2020s, including Hyundai.
Though Intel is the leader in data centers microprocessor market, with more than 90% market share, it has more recently lagged in the market for coprocessors, where Nvidia has generated momentum. While Intel witnessed a mere 13% year over year growth in its revenue from the Data Center Group in Q3 2017, Nvidia data center revenues nearly tripled during the same period. Earlier this year, Intel announced the acquisition of the deep learning technology startup Nervana Systems. According to Diane Bryant, executive vice president and general manager of Intel's Data Center Group, Nervana has a fully-optimized software and hardware stack for deep learning and has the advanced expertise in accelerating deep learning algorithms, which can help Intel expand its capabilities in the field of AI (artificial intelligence).