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Tech's Pioneers Have Been Left Behind. Their Stocks Are Cheap--and Complicated.


Cisco Systems (ticker: CSCO), IBM (IBM), Intel (INTC), Oracle (ORCL), Seagate Technology (STX), Western Digital (WDC), Xerox Holdings (XRX), HP Inc. (HPQ), and Hewlett Packard Enterprise (HPE) still employ a total of 900,000 people. They account for $363 billion in annual revenue and $840 billion in stock market value. But their sales, accounting for inflation, are mostly going in reverse. The best of the bunch, Western Digital, is forecast to grow 4.4% next year. Xerox, the worst, is likely to see a 4.7% decline. Wall Street bankers have begun to mount a rescue effort.

Nvidia's New EGX Platform Brings Power of Accelerated AI to the Edge


Nvidia has announced the launch of EGX Edge Supercomputing Platform designed to let organisations easily deploy the hardware and software necessary for high-performance, low-latency AI workloads. Instead of being deployed inside big data centres, an EGX deployment is designed to sit at the edge of the cloud which, Nvidia believes, makes it ideal for the next generation of use cases. "We've entered a new era, where billions of always-on IoT sensors will be connected by 5G and processed by AI," Jensen Huang, Nvidia founder and CEO, said at a keynote ahead of MWC Los Angeles earlier this week. "Its foundation requires a new class of highly secure, networked computers operated with ease from far away. "We've created the Nvidia EGX Edge Supercomputing Platform for this world, where computing moves beyond personal and beyond the cloud to operate at planetary scale," he added. The EGX stack includes an Nvidia driver, Kubernetes plug-in, Nvidia container runtime, and GPU monitoring tools, delivered through the Nvidia GPU Operator, which allows you to standardise and automate the deployment of all necessary components for provisioning GPU-enabled Kubernetes systems. Nvidia will certify hardware as'NGC Ready for Edge' that customers will be able to buy from partners such as Advantech, Altos Computing, ASRock RACK, Atos, Dell Technologies, Fujitsu, GIGABYTE, Hewlett Packard Enterprise, Lenovo, MiTAC, QCT, Supermicro, and TYAN. Nvidia says EGX is already being used by customers. At Walmart's Intelligent Retail Lab in Levittown, New York, for example, EGX enables real time processing of more than 1.6 terabytes of data generated each second to "automatically alert associates to restock shelves, open up new checkout lanes, retrieve shopping carts, and ensure product freshness in meat and produce departments." The EGX platform features software to support a wide range of applications, including Nvidia Metropolis, which can be used to power smart cities and build intelligent video analytics applications. The city of Las Vegas, for example, is using EGX to capture vehicle and pedestrian data to make its streets safer. San Francisco's Union Square Business Improvement District is using EGX to capture real-time pedestrian counts for local retailers. "We use our smartphones sporadically -- we type into it, or watch a movie now or then -- and frankly there are only seven and a half billion of us," Huang said. "In the case of sensors, it will be streaming all the time.

Top 10 Patent Recipients for 2018 Include IBM, Apple and Microsoft


IBM earned a record 9,100 U.S. patents in 2018, marking the 26th year in a row the Armonk, New York-based company has been the top recipient. Samsung was second with 5,850 patents while tech giants Apple and Microsoft also appeared in the top ten, according to a list compiled by research service IFI Claims. IBM's latest patent haul, which topped the 9,043 it received last year, includes a growing number of inventions related to artificial intelligence and quantum computing, which many people see as critical technologies of the future. Google, which came in at number seven on last year's list, did not crack the top ten patent recipients for 2018. Meanwhile, Apple rose to ninth from eleventh.

How much did a personal computer cost the year you were born?

USATODAY - Tech Top Stories

The Scelbi was initially advertised in the back of an amateur radio magazine in 1974. The product would only sell about 200 units and was discontinued before the end of the decade. At about 50 pounds, IBM's 5100 Portable Computer was hardly portable by today's standards. A decade earlier, a computer with the same processing capacity would weigh about half a ton. A fully functioning Apple I computer is on display with its interfaces at Sotheby's in New York, June 8, 2012.

Nvidia is unstoppable--until somebody invents a better AI chip


Nvidia stock is soaring, up more than 14% in after-hours trading, beating Wall Street's expectations for its first quarter. The graphics processing unit (GPU) company announced its first quarter earnings today with revenue of $1.94 billion, a 48% gain year over year. While gaming drives most of the company's sales, its largest area of growth over the past year was selling GPUs that power the artificial intelligence and graphics processing in datacenters. That sector of business saw 186% growth year over year, just a dip below last quarter's 205% growth. Nvidia has built itself into a leader in this space, selling enterprise GPUs to Google, Microsoft, Amazon, IBM, Tencent, and Baidu.

Is GPU technology giving Spark a flame? #BigDataNYC


Gearing up for three days of coverage of BigDataNYC 2016 at 37 Pillars in New York City, the SiliconANGLE Media team and NVIDIA Corp. hosted The Future: AI-Driven Analytics, An Evening of Deep Learning. This event kicked off the conversation about deriving benefits from Big Data to advanced Artificial Intelligence (AI) and Machine Learning (ML). An event panel met to talk about deep learning, what it means, where it's headed and implications for next-gen apps. Panelists Jim McHugh, VP and GM of NVIDIA Corp.; Randy Swanberg, distinguished engineer at IBM; Ram Sriharsha, product manager, Apache Spark, at DataBricks, Inc.; and Josh Patterson, director of Field Engineering at Skymind joined host George Gilbert, (@ggilbert41), Big Data analyst at Wikibon and theCUBE cohost (from the SiliconANGLE Media team), to talk about deep learning and where is going in the future. Gilbert began the panel discussion by saying that the real advance that is impending right now is the magnitude of cores that use GPUs (Graphics Processing Unit) as auxiliary processing units, which he feels is going to change the future of where computation will go.