What is quantum computing?

An ordinary computer chip uses bits. These are like tiny switches, that can either be in the off position – represented by a zero – or in the on position – represented by a one. Every app you use, website you visit and photograph you take is ultimately made up of millions of these bits in some combination of ones and zeroes.

This works great for most things, but it doesn’t reflect the way the universe actually works. In nature, things aren’t just on or off. They’re uncertain. And even our best supercomputers aren’t very good at dealing with uncertainty. That’s a problem.

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That’s because, over the last century, physicists have discovered when you go down to a really small scale, weird things start to happen. They’ve developed a whole new field of science to try and explain them. It’s called quantum mechanics.

Quantum mechanics is the foundation of physics, which underlies chemistry, which is the foundation of biology. So for scientists to accurately simulate any of those things, they need a better way of making calculations that can handle uncertainty. Enter, quantum computers.

Blockchain Developer/Engineer

As the name suggests, Blockchain Developer/Engineers are software experts who specialize in Blockchain technology. Blockchain Developer/Engineers handle and oversee the complete life cycles of Blockchain applications, right from research and analysis to their design and execution.

They use a combination of various Blockchain programming languages (Simplicity, Solidity, Rholang, JavaScript, C++, etc.) to create advanced interfaces, features, and architecture for Blockchain systems. Apart from setting up the necessary infrastructure for Blockchain applications and solutions, Blockchain Developer/Engineers also set up essential security measures to protect the systems from cyber attacks and also to establish standard work practices.

Blockchain Developer/Engineers must possess an in-depth understanding of the Blockchain architecture, Data Structures, cryptography, smart contract development, and web development.

SLA based services are services that are based on a service level agreement (SLA). This is a contract between a service provider and the end user that sets out the level of service that the service provider is expected to offer. They define what the customer is going to receive in exchange for their money, although not how the service will be delivered.

Computers Already Learn From Us

Artificial intelligence seems to be everywhere, but what we are really witnessing is a supervised-learning revolution: We teach computers to see patterns, much as we teach children to read. But the future of A.I. depends on computer systems that learn on their own, without supervision, researchers say.

When a mother points to a dog and tells her baby, “Look at the doggy,” the child learns what to call the furry four-legged friends. That is supervised learning. But when that baby stands and stumbles, again and again, until she can walk, that is something else.

Computers are the same. Just as humans learn mostly through observation or trial and error, computers will have to go beyond supervised learning to reach the holy grail of human-level intelligence.

“We want to move from systems that require lots of human knowledge and human hand engineering” toward “increasingly more and more autonomous systems,” said David Cox, IBM Director of the MIT-IBM Watson AI Lab. Even if a supervised learning system read all the books in the world, he noted, it would still lack human-level intelligence because so much of our knowledge is never written down.

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Supervised learning depends on annotated data: images, audio or text that is painstakingly labeled by hordes of workers. They circle people or outline bicycles on pictures of street traffic. The labeled data is fed to computer algorithms, teaching the algorithms what to look for. After ingesting millions of labeled images, the algorithms become expert at recognizing what they have been taught to see.

But supervised learning is constrained to relatively narrow domains defined largely by the training data.

AWS Certified Solutions Architect Associate Certification

When I first set out to get an AWS certification, I had a few false starts. I’d be good for about a week, putting in an hour or two of study every night, but then I’d allow something to interrupt my routine. Finally, I decided I needed to set myself a hard deadline, so I actually booked the exam. This definitely made me get my a&@ in gear. I was a bit stressed in the days leading up to the exam, but had I not put the pressure of a deadline on myself, who knows how many more false starts I would have had.

Find a study buddy
Getting AWS certified is very much encouraged by our leadership. I have plenty of colleagues who have gotten certified and I picked their brains relentlessly. A few other colleagues were also preparing for certification, so we partnered up to study on occasion, which provided me much more motivation. Also we found that a little healthy and jovial competitiveness pushed us to do our best.

Learn the theory and do the labs
AWS provides plenty of certification prep and training opportunities. I found it tempting to power through all the theory material and come back to the labs later, but it was more effective to do the labs immediately after learning the relative theory. While the exams don’t have any labs, using the labs to get firsthand experience applying the theory improved my mental model and made it easier to recall the material.

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Don’t expect to see the same questions you studied in the actual exam
During my exam prep, I answered hundreds of sample questions. And while the themes and required knowledge were similar, never once did I see a practice question on the actual exam. In this respect, I’m not sure learning by rote—practicing the same questions over and over again—will really benefit a candidate. With that being said, the sample questions were vital to my study because when I got one wrong, I went back to the prep material to understand why I was wrong, and thus improved my knowledge.

Enterprises Will Unlock Hidden Value in Their Own Workforces

If 2019 was the year we identified the most acute challenges facing various industries — in the form of macroeconomic trends as well as industry-specific factors — 2020 will be the year we confront those issues.

For most companies, this looks like addressing a skills gap that grows at the same rate technology progresses. This is to say, in the tech industry, it’s a gap that grows quickly.

In this way, progress can be unforgiving, both to companies left searching for skilled labor and for workers who are left behind during these economic shifts. The consequences bleed through to the rest of the economy in the form of anemic productivity, shrinking revenue, and reduced customer satisfaction.

Some of these changes, like automation, are sweeping through the entire economy. Many leaders thought, somewhat conveniently, that white collar jobs would be insulated from the instability that would come to characterize lower-skilled labor — but white collar jobs might be just as vulnerable, according to new reports.

Permanent Transition
Automated programs now act as corporate recruiters, generating insights for market analysis firms, and executing high-frequency trades in finance — all functions of jobs that we understand to be well-paying, professional and, above all, safe (for now).

Clearly, there’s no class of workers excluded from the changes that are taking place. Artificial intelligence, the enabling technology behind automation, is forcing a broad economic realignment as firms compete to leverage its benefits and protect themselves from risk.

Technology always has been a differentiator, but the rate at which industry-changing innovations come to market is faster than ever before. As firms adopt new tech at corresponding rates to gain an edge on the competition, their workforces repeatedly are thrown into phases of transition that are beginning to feel permanent.

Companies with workforces small enough or agile enough to adapt can thrive. However, a status quo of permanent transition could exclude vast swaths of people from participating, especially in organizations with large, diversified business units.

Even organizations founded in the digital era with young, tech-savvy workforces aren’t excluded from the challenges that the current software environment presents to people at work.

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An example of this is the rise of the gig economy workforce. Workers are distributed, they work independent schedules, and they establish highly varied work patterns. The flexibility and independence this offers can make an organization nimble and adaptable.

Top Engineering Colleges in India

Many ranking agencies release the list of these colleges rank wise every year. These rankings are also released according to different categories like top private and top public engineering colleges in India, top engineering colleges in south India, etc. Many agencies also release rankings city-wise, state-wise and stream-wise.

Some of the examples of these ranking lists are Top MBA Colleges in India, Top Engineering Colleges in Karnataka, etc. These rankings are based on different parameters like Placements, Faculty Quality, Teacher-Student Ratio, Perception of the University, Fees, etc. We have listed some of the top rankings for these engineering colleges below.

Top Engineering Colleges in India: NIRF Ranking
NIRF (National Institutional Ranking Framework) is the ranking agency of the Ministry of HRD, Government of India. It releases the most trusted and comprehensive ranking list of the top colleges in India. NIRF rankings are released for 8 different categories including University, College, Engineering, Management, Architecture, Pharmacy, Law, and Medical colleges.

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Return on Investment or ROI shows how profitable it is to pursue a particular course from a particular college. It is the comparison of the fee you invest while studying and the return you get in the form of placement. In the case of popular management and engineering courses, choosing a college or university based on the ROI factor can be very much beneficial.

Linux computer operating system

Linux, computer operating system created in the early 1990s by Finnish software engineer Linus Torvalds and the Free Software Foundation (FSF).

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open source: Linux
By 1991 Internet access had become sufficiently common that e-mail could knit together a large worldwide community of volunteer developers…
While still a student at the University of Helsinki, Torvalds started developing Linux to create a system similar to MINIX, a UNIX operating system. In 1991 he released version 0.02; Version 1.0 of the Linux kernel, the core of the operating system, was released in 1994. About the same time, American software developer Richard Stallman and the FSF made efforts to create an open-source UNIX-like operating system called GNU. In contrast to Torvalds, Stallman and the FSF started by creating utilities for the operating system first. These utilities were then added to the Linux kernel to create a complete system called GNU/Linux, or, less precisely, just Linux.

Linux grew throughout the 1990s because of the efforts of hobbyist developers. Although Linux is not as user-friendly as the popular Microsoft Windows and Mac OS operating systems, it is an efficient and reliable system that rarely crashes. Combined with Apache, an open-source Web server, Linux accounts for more than a third of all servers used on the Internet.

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Because it is open source, and thus modifiable for different uses, Linux is popular for systems as diverse as cellular telephones and supercomputers. The addition of user-friendly desktop environments, office suites, Web browsers, and even games helped to increase Linux’s popularity and make it more suitable for home and office desktops. New distributions (packages of Linux software) were created throughout the 1990s. Some of the more well-known distributions include Red Hat, Debian, and Slackware.

Network Speeds

Ethernet network speeds have evolved significantly over time and typically range from Ethernet (802.11) at 10 Mbps, Fast Ethernet (IEEE 802.3u) at 100 Mbps, Gigabit Ethernet (IEEE 802.3-2008) at 1000 Mbps and 10 Gigabit Ethernet (IEEE 802.3a) at 10 Gbps. But many other Ethernet speeds are available for specialized applications. These include 2.5 Gbps, 5 Gbps, 25 Gbps, 40 Gbps, 50 Gbps and 100 Gbps speeds.

These switch speeds are designed to allow tiered network building for any-to-any rate connectivity. Access switches might support 10/100/1000 Mbps Ethernet speeds for connecting to end users. This traffic is aggregated into distribution switches over faster connections, typically 10 Gbps. The final aggregation is to a core switch which utilizes 10 Gbps connections. Other speeds are for specialized access applications such as using 2.5Gbps connections for high-performance wireless access points, or in the data center where server links can utilize 10/25/40 Gbps connections.

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Transition Networks supports all of these different networking speeds to provide the most flexibility to all of our customers. Our switches are available in enterprise grades or hardened temperature grades as well as managed or unmanaged so that you can get the network switch that will work best for your needs. Lastly, our switches are available with Power-over-Ethernet to provide power and connectivity to your network.

Why cybersecurity should be India’s foremost priority

The Cybersecurity Policy of 2013 is open and technology neutral. But it needs upgradation. The digital economy today comprises 14-15% of India’s total economy, and is targeted to reach 20% by 2024. India has more than 120 recognised ‘data centres’ and clouds.

The average data consumption per person a year is in the range of 15-20 gigabits. The growth rate in data generation is more than 35%. With more inclusion of artificial intelligence (AI), machine learning (ML), data analytics, cloud technology.

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Countries have now started taking different approaches, which include tackling matters related to data sovereignty, data localisation, internet governance, handling fake news and international law. The change in military doctrines favouring the need to raise cyber commands reflects a shift in strategies, which include building deterrence in cyberspace.

The concept of ‘active cyber defence’ is generally being adopted to address the new challenges. Examples of this are EU’s General Data Protection Regulation (GDPR), Asia-Pacific Economic Cooperation’s (Apec) Cross-Border Privacy Rules (CBPR), and the US’ Clarifying Lawful Overseas Use of Data (CLOUD) Act.

What Skills and Competencies Do You Need to Be an IT Analyst?

IT analysts design, implement, and modify information systems to improve business processes. Know the skills and competencies needed to work as an IT analyst.

A system or an IT analyst designs, analyzes, and implements information systems that are used in solving business problems. Other than that, organizations use system analysis to gather information in the existing system in order to determine its shortcomings and upgrade the systems progressively with help of IT analysts. Since effective solving of business problems is the need of the hour, careers in IT or system analysis have good career prospects. However, there are certain skills and a degree in computer domains that are necessary in order to pursue a career in it.

Education Needed to Be an IT Analyst:
To be an IT analyst, you need a Bachelor’s degree or a diploma in either of the given field, viz., information technology, computer science, or computer engineering. A Bachelor’s degree or a diploma can land you an entry-level job, but for a specific profile, the recruiter may prefer candidates with a Master’s degree or with relevant work experience.