Daily Archives: July 7, 2020

China after November

By Basil A. Coronakis – The war between the US and China that started shortly after the election of Donald Trump in 2016 and has since continue at relatively low intensity w

There is no doubt, of course, that it will continue at even stronger pace after the election, regardless of who the winner is, whether it is the remains of the Democratic party or of the Republicans. Indeed, Trump has brought the US’ relations with China to a point of no return. And regardless whether he will or not win a second term, the Sino-American war will not stop.

American society has been intelligently brain-washed by the Trump Administration into holding China responsible for the Wuhan Virus pandemic, and the more lives it costs in the United States, the more Americans will hold China responsible. As this is, for ordinary Americans, a matter of life or death, their anger and hatred for China will continue to grow in parallel with the pandemic effects.

It would be far fetched to speculate that Trump has handled the pandemic in the way to have exactly this effect, but there is no doubt that he maximized it as an excellent detergent for brain-washing the people of Main Street.

Americans are convinced that China is responsible for the pandemic, which is true, but to communicate this sort of truth efficiently, and to engage the entire population of the United States, was a victorious tactical maneuver in the New Cold War against China.

Now all Americans are psychologically engaged against China and this is the bond that the next president will be forced to continue the war against China. If he does not, he will certainly be accused for high treason, an accusation which regardless of what the impact is on his presidency, will carry on in the historical record.

For China, this war is a win-win situation because if Beijing loses, it will be completely isolated from the rest of the world and will have no external influences, which means no dangers, thus leaving the Communist regime with eternal power. For China’s Communists, isolation is the best-case scenario as they will maintain power and extend their totalitarian rule to all aspects of life by eliminating any potential threat to their grip on power, all of which will be done pretty easily as the Chinese people have never sensed freedom or democracy, and they are trained to work for a handful of rice under the shadow of the Great Helmsman. more>

Updates from McKinsey

How to build a data architecture to drive innovation—today and tomorrow
Yesterday’s data architecture can’t meet today’s need for speed, flexibility, and innovation. The key to a successful upgrade—and significant potential rewards—is agility.
By Antonio Castro, Jorge Machado, Matthias Roggendorf, and Henning Soller – Over the past several years, organizations have had to move quickly to deploy new data technologies alongside legacy infrastructure to drive market-driven innovations such as personalized offers, real-time alerts, and predictive maintenance.

However, these technical additions—from data lakes to customer analytics platforms to stream processing—have increased the complexity of data architectures enormously, often significantly hampering an organization’s ongoing ability to deliver new capabilities, maintain existing infrastructures, and ensure the integrity of artificial intelligence (AI) models.

Current market dynamics don’t allow for such slowdowns. Leaders such as Amazon and Google have been making use of technological innovations in AI to upend traditional business models, requiring laggards to reimagine aspects of their own business to keep up. Cloud providers have launched cutting-edge offerings, such as serverless data platforms that can be deployed instantly, enabling adopters to enjoy a faster time to market and greater agility. Analytics users are demanding more seamless tools, such as automated model-deployment platforms, so they can more quickly make use of new models. Many organizations have adopted application programming interfaces (APIs) to expose data from disparate systems to their data lakes and rapidly integrate insights directly into front-end applications. Now, as companies navigate the unprecedented humanitarian crisis caused by the COVID-19 pandemic and prepare for the next normal, the need for flexibility and speed has only amplified.

For companies to build a competitive edge—or even to maintain parity, they will need a new approach to defining, implementing, and integrating their data stacks, leveraging both cloud (beyond infrastructure as a service) and new concepts and components. more>

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Updates from Ciena

How governments can solve layer 3 network complexity
What if government agencies could monitor and analyze their IP networks to ensure peak efficiency and service continuity—all while trying to modernize the network, balance cost, performance, and resiliency? Jim Westdorp, Ciena Government Solutions’ Chief Technologist, explains how this is possible.
By Jim Westdorp – The dynamic nature of IP networking makes it virtually impossible to know at any point in time how traffic is traversing your networks. Troubleshooting problems by issuing pings and router CLI commands, scanning log files, and manually correlating the results is imprecise and inefficient. Many government networks disable services like Internet Control Message Protocol (ICMP), which makes these inefficient tasks impossible. The results can impact service delivery, the agility of the network, and mission.

Traditional management tools have several limitations. For example, they can’t:

  • Provide real-time visibility into routing paths across the network
  • Provide unique alerts for Layer 3 technologies related to: state changes, pathing, performance, and the availability of the network elements to route packets
  • Show and model how routing errors and changes impact service delivery
  • Understand the resiliency of the network
  • Correlate routing events with performance metrics of network services to assure service performance
  • Compute and provision transport paths to deploy new services
  • Provide unified visibility and analysis for multi-vendor, multi-layer networks

Think about all the things you’d like to be able to do with your network, and ask yourself a few questions:

  • What if you could get a graphical view of all the IP flows in your network and gain deeper insights into traffic patterns, flows, and congestion?
  • What if you could drill deep into specific flows to understand the detailed route and particular pieces of network equipment those flows traversed?
  • What if you could troubleshoot your network using DVR-like functionality to see the exact state of the network at the time of an event, even if it was days in the past?
  • What if you had automated analytics to help identify the best paths to route traffic through your network?
  • What if your cyber team could utilize the same platform to be alerted to conditions indicative of external interference with a government?

Often, “what-ifs” are hypotheticals. Not in this case, with Blue Planet’s Route Optimization and Analysis (ROA).  This technology has been field-proven for more than a decade with government entities that have strategic imperatives to monitor and analyze their IP Networks to ensure peak efficiency and service continuity—all while trying to modernize the network, balance cost, performance, and resiliency. more>

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Updates from Chicago Booth

Ever closer to an optimally cost-efficient assembly-line operation
By Chuck Burke and Vanessa Sumo – Companies such as Dell and BMW use an assemble-to-order production strategy that keeps common components on the factory floor, ready for final assembly into the type of personal computer or vehicle that a customer orders. This is great for companies looking to satisfy a large volume of demand but that don’t want to build whole units in advance, to avoid any unsold products.

However, the difficulty of estimating how much of each component to hold in stock and how to allocate components to each product can keep companies from maximizing ATO’s benefits in practice.

A cross between two alternate production strategies

Make-to-stock strategy: MTS managers forecast consumer demand and match anticipated orders with an inventory of fully assembled products.

Make-to-order strategy: On the other hand, MTO systems wait for a customer’s order to arrive before starting production. Because this can include procuring parts and assembling components, MTO often results in a longer lead time.

Assemble-to-order strategy: An ATO strategy aims to combine the best of both systems—its flexibility lets companies fulfill large orders relatively quickly with minimal unsold inventory, yet still allows customers to partially customize orders. Here is how it works:

Managers must decide the quantity of components to order even before they can ascertain customer demand for their products.

When customers’ orders arrive, managers must then choose how to allocate the supply of components to each product for assembly. more>

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