April 01, 2021

April 01, 2021

How standard silicon chips could be used for quantum computing

To create and read qubits, which are the building blocks of those devices, scientists first have to retain control over the smallest, quantum particles that make up a material; but there are different ways to do that, with varying degrees of complexity. IBM and Google, for example, have both opted for creating superconducting qubits, which calls for an entirely new manufacturing process; while Honeywell has developed a technology that individually traps atoms, to let researchers measure the particles' states. These approaches require creating new quantum processors in a lab, and are limited in scale. Intel, for example, has created a 49-qubit superconducting quantum processor that is about three inches square, which the company described as already "relatively large", and likely to cause complications when it comes to producing the million-qubit chips that will be required for real-world implementations at commercial scale. With this in mind, Quantum Motion set off to find out whether a better solution could be found in proven, existing technologies. "We need millions of qubits, and there are very few technologies that will make millions of anything – but the silicon transistor is the exception," John Morton, ... tells ZDNet.


Top 5 Attack Techniques May Be Easier to Detect Than You Think

The analysis shows attackers for the most part are continuing to rely on the same techniques and tactics they have been using for years. And, despite all the concern about sophisticated advanced persistent threat (APT) actors and related threats, the most common threats that organizations encountered last year are what some would classify as commodity malware. "Although the threat landscape can be overwhelming, there are many opportunities we have as defenders to catch threats in [our] networks," says Katie Nickels, director of intelligence at Red Canary. "The challenge for defenders is to balance the 'tried and true' detection opportunities that adversaries reuse with keeping an eye on new techniques and threats." Red Canary's analysis shows attackers most commonly abused command and script interpreters like PowerShell and Windows Command Shell to execute commands, scripts, and binaries. ... Attackers most commonly took advantage of PowerShell's interactive command-line interface and scripting features to execute malicious commands, obfuscate malware, and malicious activity to download additional payloads and spawn additional processes.


Preparing for enterprise-class containerisation

Beyond the challenges of taking a cloud-native approach to legacy IT modernisation, containers also offer IT departments a way to rethink their software development pipeline. More and more companies are adopting containers, as well as Kubernetes, to manage their implementations, says Sergey Pronin, product owner at open source database company Percona. “Containers work well in the software development pipeline and make delivery easier,” he says. “After a while, containerised applications move into production, Kubernetes takes care of the management side and everyone is happy.” Thanks to Kubernetes, applications can be programmatically scale up and down to handle peaks in usage by dynamically handling processor, memory, network and storage requirements, he adds. However, while the software engineering teams have done their bit by setting up auto-scalers in Kubernetes to make applications more available and resilient, Pronin warns that IT departments may find their cloud bills starting to snowball. For example, an AWS Elastic Block Storage user will pay for 10TB of provisioned EBS volumes even if only 1TB is really used. This can lead to sky-high cloud costs.


Practical Applications of Complexity Theory in Software and Digital Products Development

The first radical idea has to do with the theory and practice of Complexity. The second radical idea has to do with the human element in Complexity theory. Let’s start with the first one. Most of the literature on Complexity and most of the conversations revolving around Complexity are theoretical. This is true and has been true in the last 17 years, also in the software development community, in the products development community, and more in general in the broader Lean and Agile community. When you look into real teams and organisations, here and there you will find some individual who is passionate about Complexity, who knows the theory, and who is using it to interpret, understand, and make sense of the events happening around her/him and reacting in more effective ways. Complexity gives her/him an edge. But such a presence of Complexity thinking is confined. The first new radical idea is to shift up-side-down the centre of gravity of the conversation around Complexity; to make the practical applications of Complexity theory prominent.


Researchers show that quantum computers can reason

Admittedly, it’s not like you can run down to Best Buy today and purchase a quantum computer. They are not yet ubiquitous. IBM apparently is collecting quantum computers the way Jerry Seinfeld collects classic and rare cars. Big Blue also is installing a quantum computer at Cleveland Clinic, the first private-sector recipient of an IBM Quantum System One. But quantum computing’s time in the sun inches inexorably closer. “Quantum computing (QC) proof of concept (POC) projects abound in 2021 with commercialization already happening in pilots and building to broader adoption before 2025,” REDDS Capital Chairman and General Partner Stephen Ibaraki writes in Forbes. “In my daily engagements’ pro bono with global communities – CEOs, computing science/engineering organizations, United Nations, investments, innovation hubs – I am finding nearly 50% of businesses see applications for QC in five years, though most don’t fully understand how this will come about.” IBM has not been the only major tech company developing quantum computing technology. 


Service Meshes: Why Istio? An Introduction

In any microservice-based architecture, whenever there is a service call from one microservice to another. We are not able to infer or debug what is happening inside the networked service calls. This might lead to serious problems when we are not able to diagnose properly what is the problem if an unwanted situation arises. For example; performance issues, security, load balancing problems, tracing the service calls, or proper observability of the service calls. The severity of the issue gets multiplied when you have to cater to many microservices for any application to work properly. ... Istio has the most features and flexibility of any of these three service meshes by far: Cascading failure prevention (circuit breaking); Authentication and authorization. The service mesh can authorize and authenticate requests made from both outside and within the app, sending only validated requests to instances; Resiliency features (retries, timeouts, deadlines, etc.); Robust load balancing algorithms. Control over request routing (useful for things like CI/CD release patterns); The ability to introduce and manage TLS termination between communication endpoints; Rich sets of metrics to provide instrumentation at the service-to-service layer ...

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