Main types of Windows and the way to choose the suitable one for your computer

Information technology has been changed day by day. Windows is one of the most convenient inventions of humans. Belows are some information you should know about Windows versions.

Currently, there are many different versions of Windows for users to choose; however, many people wonder which Windows is the best and most suitable for their laptop and computer. Each version has its advantages and disadvantages. Let’s consider some factors and have the best choice.

Popular versions of Windows today

Windows XP

Window XP was first launched with the 32-bit version in October 2011. Then, the 64-bit version was introduced four years later. Windows XP has many versions, including XP Starter, Home, Professional, XP 64 Edition, and Fundamentals for Legacy PCs.

Windows Vista

Vista was officially introduced in the market on January 30th, 2007 with 5 versions: Home Basic, Home Premium, Vista Business, Vista Enterprise, and Ultimate Vista.

Windows 7

In 2009, Windows 7 was launched with many breakthroughs. It includes 6 versions: Home Basic, Home Premium, Professional, Enterprise, Ultimate, and Thin PC. Windows 7 has a good support platform. Users can install almost all applications for their computers with high compatibility.

Windows 7 is one of the most popular versions of Windows.

Moreover, the security system of Windows 7 is relatively good. Users can use Windows Defender which is integrated into Microsoft operating system to check viruses. However, the computer which uses Windows 7 will takes time to start. Some drivers must be manually installed, which makes it difficult for users to install.

Windows 8

Windows 8 with the new Metro interface was introduced in 2012 with 4 versions: Windows 8, Windows 8 Pro, Windows 8 OEM, and Windows 8 Enterprise.

Windows 8 can supports laptops with touch screens. However, there are not many applications that are supported. The new Metro interface makes it very difficult for users to get used to and use. Currently, not many users have chosen this version as the new Windows 10 has many advantages over Windows 8.

Windows 10

Windows 10 was released in July 2015 by Microsoft with many different versions. It includes Windows 10 Home, Pro, Enterprise, Enterprise LTSB, Education, Windows 10 IoT Core, and Windows 110 loT Enterprise.

Windows 10 has many advanced improvements in graphics, a friendly interface, high security, and integrated with virtual assistant Cortana help to increase searching speed. Windows 10 supports up to DirectX 12, so it is compatible with many graphics applications and emulator games.

However, unlike the previous versions of Windows, Windows 10 has very few options to control Windows Updates. You cannot select the updates to download and install because everything will be downloaded and installed automatically.

Choose suitable Windows for your computer

Currently, a lot of users have chosen Windows 7 because it supports all current applications. Besides, Windows 10 is encouraged to install by Microsoft and is almost always integrated into its products in the form of copyright.

If you like stability, simple and easy – to –use interface which is compatible with specialized software for work, Windows 7 is an appropriate choice. However, keep in mind that Windows XP is the most popular generation at the time but still could not exist under Microsoft’s innovation rule.

Choosing suitable Windows version is an important step.

On the other hand, if you are into new things, high security and customization, cross-platform support, Windows 10 is a good choice. A lot of experts suggest using Windows 10 because this is a big improvement in Microsoft. It not only takes advantage of the later versions to improve but also has many new features to serve users.

Some people thought that the higher the operating system, the stronger the computer should be. But in fact, laptop or computer does not need a high configuration to install Windows 10. Even older computer still works well with Windows 10. The following is the basic requirements of configuration for installing Windows 10:

CPU: minimum processor speed of 1 GHz.

RAM: 1 GB for 32-bit or 2GB for 64-bit.

Hard disk space: 16GB for 32-bit Windows and 20GB for 64-bit versions, at least 5GB of free space for the system drive.

VGA: Supports DirectX 9 with WDDM 1.0 compatible driver.

Screen: Minimum resolution of 1024×600 pixels.

Actually, choosing the suitable Windows version for your computer is a very important step as it directly affects your work performance. So, do not forget to consider carefully the advantages, disadvantages of each Windows version, check your configuration before selecting the best Windows for your computer.

What did you know about Windows NT?

Have you ever heard of the Windows NT operating system? What did you know about this operating system? Find out about it in the following article.

Surely everyone knows a lot about the famous Windows operating systems such as Windows 7, Windows 8, Windows XP and Windows 10 today. However, have you ever learned about the Windows NT operating system? What did you know about this operating system of Windows? Join us to discover about Windows NT right now.

What is Windows NT?

Windows NT is a family of operating systems manufactured by Microsoft with the first version released on July 27, 1993. This is a multitasking, multi-user operating system and independent processor.

Source: devianart.com

Meaning of the name “NT”:

It has been suggested that Dave Cutler originally intended to name it WNT but the project was intended to be a sequel to OS/2 and called NT OS/2 before acquiring the Windows brand.

Mark Lucovsky – one of the NT developers, claimed that the name was taken from the original Intel i860 target processor, codenamed N10 (“N-Ten”). However, in a Q&A with Bill Gates in 1998, he revealed that “NT” stands for “New Technology” but no longer has any specific meaning.

And “NT” has disappeared in the name of releases since Windows 2000, although Microsoft described the product as built on NT Technology (the following versions of Microsoft operating systems were developed based on NT technology).

Windows NT development process:

Microsoft decided to create a mobile operating system, compatible with OS / 2 and POSIX, to support multitasking in October 1988. In November 1989, Windows NT was known as OS / 2 3.0, the third version of the operating system jointly developed by Microsoft and IBM.

To ensure portability, developers initially used the Intel i860XR RISC processor, but later switched to the MIPS R3000 processor in late 1989 and then the Intel i386 in 1990.

Windows uses few resources and is based on DOS, leading to the introduction of Windows 3.0 in May 1990. Windows 3 was so successful that Microsoft decided to change the main application programming interface for the unreleased NT OS/2 version (from the extended API OS/2 to the extended Windows API).

This decision has caused a lot of debate between Microsoft and IBM, leading to the termination of cooperation. IBM continued to develop OS/2 while Microsoft continued to work with the newly renamed Windows NT. Although neither of these operating systems was as immediately popular as Microsoft’s MS-DOS or Windows products, Windows NT was still more successful than OS/2.

Microsoft hired a group of developers from Digital Equipment Corporation, run by Dave Cutler, to build Windows NT. They also synthesized many elements of product design and took advantage of Cutler’s previous DEC experience.

Source: fanpop.com

The API sets in Windows NT are implemented as subsystems on top of the “native” API that is not publicly documented, resulting in late adoption of the Windows API (on the Win32 subsystem). Windows NT was one of the earliest operating systems to use Unicode.

Programming language:

Windows NT is written in C and C ++ and uses a few low-level languages. The C language is mainly used for kernel code while C ++ is heavily used for user-mode code.

Key features of Windows NT:

  • The main design goal of NT is the mobility of hardware and software. Different versions of the NT operating system have been released for many processor architectures, initially IA-32, MIPS and DEC Alpha. PowerPC, Itanium, x86-64 and ARM are supported in the following versions.
  • Windows NT 3.1 was the first version of Windows to use 32-bit virtual memory addresses on 32-bit processors. Its companion product, Windows 3.1, used segmented addresses and switched from 16-bit to 32-bit addresses.
  • Windows NT 3.1 has a core kernel that provides a system API, running in supervisor mode (Ring O in x86; referred to in Windows NT as “kernel mode” on all platforms).
  • One thing worth noting is that in Windows NT 3.x, some I/O driver subsystems like video and print are user-mode subsystems.
  • In Windows NT 4, the printer spooler, video and server subsystem is switched to kernel mode. The first graphical user interface of Windows NT was strongly influenced and programmatically compatible with the Windows 3.1 interface.
  • The interface of Windows NT 4 has been redesigned to accommodate the new Windows 95, marking the transition from Program Manager design to Windows shell.
  • Windows NT has its driver model and is not compatible with older driver frameworks. With Windows 2000, the Windows NT driver model was upgraded to the Windows Driver Model and was first introduced in Windows 98 but based on the NT driver model.

You have just been provided with all the most detailed information about Microsoft’s Windows NT operating system. We hope that this article has been helpful to you.

 

 

 

 

Things you need to know to own your computer

Computers are one of the tools that help people a lot in life. To fully own it, what do you need to know?

Like most things, the more you know about computers, the easier it will be to use them. Especially in this era of high technology, computers play an important and indispensable role for each person. Whether you are a normal computer user or someone with a lot of experience in computer use, you will surely find extremely useful tools through this article.

Learn how to use the command line

The actual use of the command line is not as exciting or easy as we see in Hollywood movies. However, learning how to use the command line is really helpful. Smart users often like to use the command line because they can do complex tasks with just a few simple keys.

There are many different types of keyboard shortcuts/Ph.dienmayxanh

There are many different types of keyboard shortcuts that we cannot address in this article. However, if you want to study more about using commands as a proficient computer user to save time, you can search deeper.

Learn more about other features

Computer addicts will always come up with something other than the well-known fixings, especially when they find new features for applications they already use. Most programs are used for a variety of purposes besides basic ones. For example, the DropBox file sync application can be used to manage your home computer, download torrent files, or even print remotely. Alternatively, you can also use Gmail to check who has stolen your phone.

Know when it’s “excessive”

When your computer starts to slow down, you need to find the problem that is causing the problem. Normally, an application will slow down your computer so need to find it and close it as quickly as possible. Tools that can help you find the cause and solve it: Rainmeter (for Windows) and MenuMeter (for Mac).

Know the hidden features of OS operating system

Each operating system (OS) has its own features and tricks underneath the interface. System tools like OnyX for Mac and Ultimate Window Tweaker are great for finding out secret features. If you are a Windows operating system user, you can learn how to hide data in a file, move window by window, or redo the move a file in the wrong place. For Mac users, look for ways to generate search codes when searching for a file, manage an app’s personal settings, or automatically restart your computer when it crashes.

Learn how to crack passwords

By studying how to gain access to a computer, you will definitely feel much more confident. Most people only know how to create secure passwords, only hackers know how to get the data they want to retrieve. This is also a useful exercise because you will learn how to protect cyber criminals in the future.

Some of the most famous hackers in the world are hired by government organizations and international projects to guard against cyber attacks. Of course, we don’t tolerate hacking, but it does provide one step in advance against cyber attacks.

Use periodic assignments

Sometimes things get better if you manually stop all the processes that are happening on your computer. Building recurring tasks will allow you to run whatever task you want, whether it’s reorganizing data, uploading photos, reminders or even alarms.

Use the keyboard more

Learn the most common keyboard shortcuts for Word, Gmail, Photoshop/Ph.Shopee

A true computer enthusiast will surely know all the basic keyboard shortcuts, such as “Ctrl-C or Ctrl-V”. Learn the most common keyboard shortcuts for Word, Gmail, Photoshop and other programs you use on a regular basis. After only a few months, you’ll be able to switch between input boxes and menus at an unbelievably accurate speed.

Learn the new operating system

If you want to impress your friends, you should try to learn more about Windows, Mac and Linux. Because each operating system has its advantages and disadvantages, it is not difficult to learn more about each system. Interestingly, there are a lot of software available today that allow you to install other operating systems on your computer, so you can switch between them as needed.

Data protection

Hide your valuable information in a text file and hide it in a secret location on your computer. Don’t forget to “Empty” Recycle Bin or Trash on your computer when you send unwanted files or data into it, this will ensure that nothing can be retrieved by any guests.  Any suspicious person can access your computer.

Computers are one of the very important technological tools. It is very important to know a lot about it in order to fully own it. Hopefully, with my share above, it will help you understand something about what you need to know to own the best computer.

How do computers affect human life?

Today, computers are a commonly used tool associated with the work of so many people. Let’s take a look at some of the benefits of computers in everyday life.

Computers have come into our lives quite long and sustainably, making fundamental changes to the world and our capabilities. Computers make our lives easier. Every question, every question, instead of having to go through all the documents to find the answer, we simply need to type some keywords into GOOGLE. The ability of computers is not limited to any field: medicine uses it to make diagnoses about the body, with fashion designers, architects, computers opening horizons new, in production, it is the computer that controls the other machines, and the people just watch. But we all know it has both positive and negative effects. Let’s take a look at the effects of computers on human life.

Improve understanding

The Internet gives people the opportunity to receive the latest breaking news, rumors, and information about the issues we care about. Allow us to play exciting and engaging online games.

Video conference makes it possible for people to conduct meetings, exchange information, and solve important issues without leaving their working positions, saving their facilities and time.

The Internet gives people the opportunity to receive the latest breaking news/Ph.Jo-78

Computers have become a very effective working tool, effectively serving us, it replaces the old typewriter, replacing both notebooks and giving us modern tools, making us. It’s become much more convenient and simple.

Searching for jobs and businesses

Also on the Internet, we can find high-paying jobs that bring satisfaction to us. Can quickly deliver, receive documents, quickly exchange information for the job.

Buying and selling online is also easier: the price is usually cheaper than in stores, you can carefully read the product description, view photos of goods, check product feedback other customers. You can buy and sell cars, search tours, buy toys for children, or buy items that are half way around the world.

Connecting people

Internet is also a means of connecting with friends, helping us keep the seemingly forgotten relationships of our peers, of sympathetic people who know each other by chance.

And it should not forget its important role for the disabled, who do not have the opportunity to directly contact with the world.

For all of us, the Internet opens the way to other cultures and histories, providing a tremendous opportunity for education, a vast source of knowledge that no other library can match.

Impact on health

With the use of computers, many people raise their awareness, but many also have health problems. Gradually we forget about physical exercise and physical activity. Many people (especially pupils and students) prefer to sit for hours at a computer, play games or surf the web, live in a virtual world rather than going outside to breathe the air, they do not expect to work harm they bring to themselves.

The main factors are harmful to the health of people working with computers: sitting posture for a long time; electromagnetic radiation of computer screens; eyestrain; overload of knuckles; reliance on computers.

Sitting: It seems like we are comfortable sitting on our computer, but in reality it is a forced and uncomfortable posture for the body: neck, head, hands and shoulders pulled. This strain leads to an overload of the spine, cartilage degeneration in adults and scoliosis in children.

Electromagnetic radiation: Modern computer screens have been designed with protective layers to reduce this harm, but of course only reduce, not eliminate.

Dependence on computers

Perhaps this is the hottest issue for the modern world, especially for teenagers of our time. This is when computers were no longer just a source of information and a tool to serve human needs, but it began to replace the world around them. Gradually, people spend more and more time on computers, immersing themselves in games or communicating on the Internet, forgetting real life as well as real communication. In particular, for children, psychology is not strong enough, some games or information on the Internet can change the worldview as well as the concept of their moral standards. In some serious cases can lead to psychological disorders.

There is no denying the benefits of computers and its practical role in the modern world. But everything has its downside, here are some things that computers affect your life. You need to be careful when making friends with this technology device to be able to exploit its benefits and limit the harm it causes.

Top 7 most powerful supercomputers in the world you should know

Computers are one of the most important tools in life today. Computers for work, communication, data storage. Do you know supercomputers?

In today’s modern life, computers are one of the important operational tools, playing an essential role in serving all activities. The current technological world has given birth to many advanced products for people, from smartphones, tablets, laptops… But those products are personal, the world needs more powerful machines for the macroscopic problems that need to be solved. Supercomputers are the main causes that can solve these urgent problems. The following is a list of supercomputers in the world.

Tianhe-1A (China)

Translated into Vietnamese means “Galaxy 1”, Tianhe-1A is one of the few petascale-type supercomputers currently operating in the world. Accordingly, Tianhe-1A is capable of running at a speed of 2.6 petaflops (2.6 billion calculations per second). This supercomputer operates on an Linux-based operating system and it takes advantage of the combined power of Intel Xeon CPU and Nvidia GPU throughout 183.368 processor cores. The Tianhe-1A supercomputer is currently located at the National Supercomputing Center in Tianjin, China, which is responsible for processing calculations for oil and gas exploration and space industry design.

SuperMUC (Germany)

SuperMUC is the name of the latest supercomputer of Leibniz Supercomputing Center, Germany. SuperMUC is currently based on IBM iDataPlex server system with 300TB of RAM and InfiniBand hyperlink technology to ensure 147,456 processor cores can operate consistently and reach 2.9 petaflops. It is known that to ensure minimal operating costs, the engineers here have used a special cooling method for SuperMUC. Specifically, they reduced the supercomputer’s heat by directly using water at a temperature of about 40 degrees Celsius.

Vulcan (United States)

Housed at the Lawrence Livermore National Research Laboratory, California, Vulcan was created to serve the activities of government, national industries and university research. Vulcan possesses the power of 393. 216 cores and processors with a speed of 4.3 petaflops. This supercomputer was developed based on IBM Blue Gene/Q technology, it consists of 24 shelves and 24 576 separate computer points.

Juqueen (Germany)

As the next generation of Jugene supercomputer, Juqueen was developed based on Blue Gene/Q technology with a speed of 5 petaflops. Juqueen has the main task of performing complex calculations in the fields of neuroscience, biology algorithms, energy, climate research and quantum physics. With 458.752 processor cores and power consumption of 2.301 kilowatts, Juqueen is the world’s most energy efficient supercomputer system.

Stampede (United States)

Operated by the University of Texas’ Advanced Computing Center, Stampede leverages the power of Xeon processors and InfiniBand multi-link technology with an estimated speed of about 5.2 petaflops. Since its inception, this supercomputer has successfully performed about 450,000 complex calculations on issues such as seismic maps, ice modeling to study climate change and improve quality pictures of tumors in the brain…

Mira (United States)

Mira is a petascale supercomputer developed on Blue Gene/Q technology/Ph.hpcwwire

Also known as “IBM Mira”, Mira is a petascale supercomputer developed on Blue Gene/Q technology. It has 787.432 times the speed of 8.6 petaflops. Mira was born to serve research in the fields of materials science, seismology, climate and chemistry. This supercomputer is the answer of the US before the introduction of Chinese computer Tianhe-1A with the development cost estimated at about 180 million USD.

K Computer (Japan)

K Computer is a supercomputer from the land of the rising sun, it operates based on a memory distribution system consisting of more than 80,000 separate computers, the speed reaches 10.8 petaflops, 705.024 Sparc cores  and Tofu six-way interconnection technology. K Computer primarily serves for calculating energy, sustainability, health care, climate change, and space research challenges…

Supercomputers or supercomputers are High Performance Computers (HPCs) – high-performance computers, with superior computing power, far beyond what you might think. They “plow” hard at the universities, laboratories and other large, important institutions around the world.

Supercomputers play an important role in the field of computational science, and are used for a variety of complex computational tasks in many fields, including quantum mechanics, weather forecasting, and research climate studies, petroleum exploration, molecular modeling (calculating structures and properties of chemical compounds, biological macromolecules, polymers, crystals), and physical simulations (such as  simulating the early moments of the universe, aerodynamics of aircraft, spacecraft, the explosion of nuclear weapons, nuclear fusion). These are the top 7 supercomputers I want to send to you!

Microsoft Azure Front Door Gets a Security Upgrade

New SKUs in Standard and Premium preview beef up the security of the content delivery network platform.

Microsoft today is launching Azure Front Door Standard and Premium in preview with two new SKUs that add threat detection, application security, and additional security protections to the content delivery network (CDN).

These updates stem from Microsoft’s efforts to bring zero-trust principles to businesses using Azure network security tools, says Ann Johnson, Microsoft’s corporate vice president of Security, Compliance, and Identity (SCI) Business Development. Its zero-trust strategy has underpinned several initiatives as it believes this is how companies will become more secure.Azure already offers two edge networking tools: Azure Front Door, which focuses on global load-balancing and site acceleration, and Azure CDN Standard, which offers static content caching and acceleration. The new Azure Front Door brings together security with CDN technology for a cloud-based CDN with threat protection and additional capabilities. 

Johnson uses three principles to describe zero trust, the first of which involves adopting explicit verification for every transaction during a session: “So not just verifying the human, but the device, the data, the location, if it’s an IoT device, the application – everything that happens in the session should be verified and anomalous behavior should be flagged,” she explains.

The second principle is ensuring least privilege access. Many organizations still provide too much privileged access to employees, Johnson says. One of the steps Microsoft is taking with its content and application delivery is implementing more controls around access. 

The third principle: “Then, finally, assume you’ve been breached,” she says. Assumed breach is a topic the security industry has discussed for years, but with zero trust, they have to assume they have been breached, and that anything within the organization could potentially be breached.

These principles have grown essential as application-delivery networks undergo a massive transformation to the cloud, Johnson explains. The new capabilities in Azure Front Door aim to provide organizations with one platform that meets availability, scalability, and security needs.

The new Azure Front Door SKU offers both static and dynamic content acceleration, global load-balancing, SSL offload, domain and certificate management, improved traffic analytics, and basic security capabilities, Microsoft writes in a blog post. The Azure Front Door Premium SKU builds on these with more security capabilities: Web application firewall (WAF), bot protection, private link support, and integration with Microsoft threat intelligence and security analytics.

In addition to supporting all the features available via Azure CDN Standard, Azure Front Door, and Azure Web Application Firewall, the new standard and premium SKUs bring a few new capabilities, Microsoft officials write in a blog post. These include a simplified user experience, simplified management experience, and TLS certificate management: both standard and premium SKUs offer Azure managed TLS certificates by default for all custom domains at no additional cost. More details on the capabilities of standard and premium can be found here. 

“I’m encouraging our customers to encrypt all their communication channels across the cloud and hybrid networks,” says Johnson. “This means they would need to secure user to app, and site to site, and we have leading encryption capabilities such as TLS within our VPN.” 

A Proactive Approach

She notes today’s updates are not a reaction to attacker activity, but a proactive step given how businesses have transitioned to the cloud in recent years; especially in 2020. As Microsoft CEO Satya Nadella said last April, “We’ve seen two years’ worth of digital transformation in two months.”

“They’re moving a ton of apps … and they need to deliver them globally, at scale, and we want to make sure we can do that from an app delivery standpoint, and an API standpoint, or even a website standpoint in a secure manner.” The ability of Azure Front Door to combine security and CDN creates an opportunity to improve the way businesses deploy and secure content. 

COVID-19 has created a new IT paradigm in the enterprise – and a new level of cybersecurity risk.

Brought to you by CyberGRX

While there are cloud network security vendors with “a range of maturity in their solutions,” Johnson notes that everyone is playing “just a little bit of catchup” because businesses are moving to the cloud faster than many network security capabilities can be built. Some Microsoft customers say that even after the pandemic slows, they will keep roughly half of their employees at home, Johnson says.

“That just means they’re going to continue to operate in the way that they do,” she continues. “And that need to move so many applications so quickly to the cloud … really drove the need to improve solutioning in this space.”

Businesses that already subscribe to Microsoft’s network security capabilities, depending on which they have, will automatically be able to try the SKUs in preview. Those who don’t use Microsoft for CDN and some of these capabilities will need to subscribe, Johnson says.

Interesting things about computers that you may not know

What makes computers so versatile to work on so many other devices? How can they become so unusually useful? And how can it work exactly like that? Please read the information below!

In the 1940s, Thomas Watson – Chairman of a multinational computer technology group based in Armonk, New York, USA, predicted that: The world will not need more than “five computers”. Sixty years later, the number of computer users in the world increased to one billion!. Clearly, computers have changed a lot in that time. In the 1940s, computers were a strange scientific phenomenon and major military support authorized by the government, each worth up to millions of dollars. Even today most computers are used in everyday appliances from microwaves to mobile phones and digital radios.

What is a computer?

Computers are electronic devices used to process information – in other words, information processors. The computer carries hard information (or data) at one end, stores the information until it is ready to operate, types and processes the information, and then quickly delivers the result to the other end. All of these processes have a unique name: the place to get information is called input, storage information is memory (or storage), information processing and Putting the result out is called an output.

– Input: For example, the keyboard and mouse are input units – places that receive information into a computer that needs processing. If you use a microphone and speech recognition software, it is a different type of input.

– Memory storage: The computer can store all your documents and files on a hard drive: very large storage memory. Smaller devices that resemble computers such as digital cameras and mobile phones that use other types of storage such as memory cards.

– Processor: The computer microprocessor (known as a pre-set programmed data processing circuit) is a deeply embedded microchip. It works extremely strong and heats up during processing. That’s why there’s a cooling fan inside the computer – so the computer doesn’t get too hot!

– Output: The computer has an LCD screen that displays high-resolution images (details) and speakers for audio output. You can also equip a color inkjet printer on the table to print document.

Source: Youtube.com

 

About computer program

Today, most computer users rely on pre-written programs such as Microsoft Word and Excel or download applications for tablets and phones without having to do many things like before. Today, almost no one writes such programs anymore, which is a pity, because it is really very interesting and useful. Everyone sees computers as a tool to help them work, not just the complex electronic devices that need to have the program installed in advance. Some people will find it more useful because we can do much better than computer programs. Once again, if we all rely on the computer programs and applications available, someone will have to write them down and that skill needs to be retained. Fortunately, there are many people who are interested in computer programs recently. “Coding” (the official name of a program, sometimes called “code”) is used to teach in schools as easy to use programming languages ​​as Scratch. Interest-based development is related to personal gadgets like the Pi Raspberry and Arduino. And the Code Clubs is a place where volunteers teach children how to code, and they are everywhere in the world.

Typical structure of a computer

That is the basic structure behind an operating system: the main software in the computer (necessary) controls the basic tasks at the input, the output, the storage and the processor. You can think of the operating system as the “base” of software on the computer on which other programs (called applications) are built. The operating system based on the basic program components on a computer is called the Basic Input / Output System (BIOS), which is the relation between the software operating system and the hardware operating system.

Different from the operating system, the basic Input / Output system is usually the same, the BIOS does not change from one computer to another according to hardware configuration and it is usually written by hardware manufacturers. The BIOS is not a hardware but a software: it is a semi-permanent program that is stored on one of the main chips of a computer – known as the firmware (usually designed to may update regularly).

Graph-Based AI Enters the Enterprise Mainstream

Graph AI is becoming fundamental to anti-fraud, sentiment monitoring, market segmentation, and other applications where complex patterns must be rapidly identified.

Artificial intelligence (AI) is one of the most ambitious, amorphous, and comprehensive visions in the history of automated information systems.

Fundamentally, AI’s core approach is to model intelligence — or represent knowledge — so that it can be executed algorithmically in general-purpose or specialized computing architectures. AI developers typically build applications through an iterative process of constructing and testing knowledge-representation models to optimize them for specific outcomes.

Image: DIgilife - stock.adobe.com

AI’s advances move in broad historical waves of innovation, and we’re on the cusp of yet another. Starting in the late 1950s, the first generation of AI was predominantly anchored in deterministic rules for a limited range of expert systems applications in well-defined solution domains. In the early years of this century, AI’s next generation came to the forefront, grounded in statistical models — especially machine learning (ML) and deep learning (DL) — that infer intelligence from correlations, anomalies, and other patterns in complex data sets.

Graph data is a key pillar of the post-pandemic “new normal”

Building on but not replacing these first two waves, AI’s future focuses on graph modeling. Graphs encode intelligence in the form of models that describe the linked contexts within which intelligent decisions are executed. They can illuminate the shifting relationships among users, nodes, applications, edge devices and other entities.

Graph-shaped data forms the backbone of our “new normal” existence. Graph-shaped business problems encompass any scenario in which one is more concerned with relationships among entities than with the entities in isolation. Graph modeling is best suited to complex relationships that are flattened, federated, and distributed, rather than hierarchically patterned.

Graph AI is becoming fundamental to anti-fraud, influence analysis, sentiment monitoring, market segmentation, engagement optimization, and other applications where complex patterns must be rapidly identified.

We find applications of graph-based AI anywhere there are data sets that are intricately connected and context-sensitive. Common examples include:

  • Mobility data, for which graphs can map the “intelligent edge” of shifting relationships among linked users, devices, apps, and distributed resources;
  • Social network data, for which graphs can illuminate connections among people, groups, and other shared content and resources;
  • Customer transaction data, for which graphs can show interactions between customers and items for the purpose of recommending products of interest, as well as detect shifting influence patterns among families, friends, and other affinity groups;
  • Network and system log data, for which connections between source and destination IP addresses are best visualized and processed as graph structures, making this technology very useful for anti-fraud, intrusion detection, and other cybersecurity applications;
  • Enterprise content management data, for which semantic graphs and associated metadata can capture and manage knowledge among distributed virtual teams;
  • Scientific data, for which graphs can represent the physical laws, molecular structures, biochemical interactions, metallurgic properties, and other patterns to be used in engineering intelligent and adaptive robotics;
  • The Internet of Things (IoT), for which graphs can describe how the “things” themselves — such as sensor-equipped endpoints for consumer, industrial, and other uses — are configured in nonhierarchical grids of incredible complexity.

Graph AI is coming fast to enterprise data analytics

The motivation behind cyberattacks is becoming more varied, with disinformation and disruption joining the regulars: data theft, extortion, and vandalism.

Brought to you by Ivanti

Graphs enable great expressiveness in modeling, but also entail considerable computational complexity and resource consumption. We’re seeing more enterprise data analytics environments that are designed and optimized to support extreme-scale graph analysis.

Graph databases are a key pillar of this new order. They provide APIs, languages, and other tools that facilitate the modeling, querying, and writing of graph-based data relationships. And they have been coming into enterprise cloud architecture over the past two to three years, especially since AWS launched Neptune and Microsoft Azure launched Cosmos DB, respectively, each of which introduced graph-based data analytics to their cloud customer bases.

Riding on the adoption of graph databases, graph neural networks (GNN) are an emerging approach that leverages statistical algorithms to process graph-shaped data sets. Nevertheless, GNNs are not entirely new, from an R&D standpoint. Research in this area has been ongoing since the early ‘90s, focused on fundamental data science applications in natural language processing and other fields with complex, recursive, branching data structures.

GNNs are not to be confused with the computational graphs, sometimes known as “tensors,” of which ML/DL algorithms are composed. In a fascinating trend under which AI is helping to build AI, ML/DL tools such as neural architecture search and reinforcement learning are increasingly being used to optimize computational graphs for deployment on edge devices and other target platforms. Indeed, it’s probably a matter of time before GNNs are themselves used to optimize GNNs’ structures, weights, and hyperparameters in order to drive more accurate, speedy, and efficient inferencing over graph data.

In the new cloud-to-edge world, AI platforms will increasingly be engineered for GNN workloads that are massively parallel, distributed, in-memory, and real-time. Already, GNNs are driving some powerful commercial applications.

For example, Alibaba has deployed GNNs to automate product recommendations and personalized searches in its e-commerce platform. Apple, Amazon, Twitter, and other tech firms apply ML/DL to knowledge graph data for question answering and semantic search. Google’s PageRank models facilitate contextual relevance searches across collections of linked webpages that are modeled as graphs. And Google’s DeepMind unit is using GNNs to enable computer vision applications to predict what will happen over an extended time given a few frames of a video scene, without needing to code the laws of physics.

A key recent milestone in the mainstreaming of GNNs was AWS’ December 2020 release of Neptune ML. This new cloud service automates modeling, training, and deployment of artificial neural networks on graph-shaped data sets. It automatically selects and trains the best ML model for the workload, enabling developers to expedite the generation of ML-based predictions on graph data. Sparing developers from needing to have ML expertise, Neptune ML supports easy development of inferencing models for classifying and predicting nodes and links in graph-shaped data.

Neptune ML is designed to accelerate GNN workloads while achieving high predictive accuracy, even when processing graph data sets incorporating billions of relationships. It uses Deep Graph Library (DGL), an open-source library that AWS launched in December 2019 in conjunction with its SageMaker data-science pipeline cloud platform. First released on Github in December 2018, the DGL is a Python open source library for fast modeling, training, and evaluation of GNNs on graph-shaped datasets.

When using Neptune ML, AWS customers pay only for cloud resources used, such as the Amazon SageMaker data science platform, Amazon Neptune graph database, Amazon CloudWatch application and infrastructure monitoring tool, and Amazon S3 cloud storage service.

Graph AI will demand an increasing share of cloud computing resources

Graph analysis is still outside the core scope of traditional analytic databases and even beyond the ability of many Hadoop and NoSQL databases. Graph databases are a young but potentially huge segment of enterprise big data analytics architectures.

However, that doesn’t mean you have to acquire a new database in order to do graph analysis. You can, to varying degrees, execute graph models on a wide range of existing enterprise databases. That’s an important reason why enterprises can begin to play with GNNs now without having to shift right away to an all-new cloud computing or database architecture. Or they can trial AWS’ Neptune ML and other GNN solutions that we expect other cloud computing powerhouses to roll out this year.

If you’re a developer of traditional ML/DL, GNNs can be an exciting but challenging new approach to work in. Fortunately, ongoing advances in network architectures, parallel computation, and optimization techniques, as evidenced by AWS’ evolution of its Neptune offerings, are bringing GNNs more fully into the enterprise cloud AI mainstream.

Over the coming two to three years, GNNs will become a standard feature of most enterprise AI frameworks and DevOps pipelines. Bear in mind, though, that as graph-based AI is adopted by enterprises everywhere for their most challenging initiatives, it will prove to be a resource hog par excellence.

GNNs already operate at a massive scale. Depending on the amount of data, the complexity of models, and the range of applications, GNNs can easily become huge consumers of processing, storage, I/O bandwidth, and other big-data platform resources. If you’re driving the results of graph processing into real-time applications, such as anti-fraud, you’ll need an end-to-end low-latency graph database.

GNN sizes are sure to grow by leaps and bounds. That’s because enterprise graph AI initiatives will undoubtedly become increasingly complex, the range of graph data sources will continually expand, workloads will jump by orders of magnitude, and low-latency requirements will become more stringent.

If you’re serious about evolving your enterprise AI into the age of graphs, you’re going to need to scale your cloud computing environment on every front. Before long, it will become common for GNNs to execute graphs consisting of trillions of nodes and edges. All-in-memory massively parallel graph-database architectures will be de rigeur for graph AI applications. Cloud database architectures will evolve to enable faster, more efficient discovery, processing, querying, and analysis of an ever-widening range of graph data types and formats.

Questions to Ask About DevOps Strategy On-Prem vs. the Cloud

Not every company can or wants to go cloud native but that does not mean they are completely cut off from the advantages of DevOps.

Organizations with predominantly on-prem IT and data environments might feel left out from conversations about DevOps because such talk leans heavily on the cloud — but are there ways for such companies to benefit from this strategic approach to faster app development? Experts from the DevOps Institute and Perforce Software offer some insight on how DevOps might be approached under such ecosystems, including if they later pursue cloud migration plans.

In many ways, the DevOps approach to app development is linked to digital transformation. “DevOps was really born out of migration to the cloud,” says Jayne Groll, CEO of the DevOps Institute. She says there was an early belief among some that DevOps could not be done on-prem because it drew upon having an elastic infrastructure, cloud native tools, and containers. “DevOps was intended always to be about faster flow of software from developers into production,” Groll says.

Image: WrightStudio - stock.Adobe.com

While being in the cloud facilitates the automation DevOps calls for, she says there are still ways for hybrid cloud environments to support DevOps, including with continuous delivery. Groll says it is also possible to manage DevOps-related apps in on-prem situations.

Even for companies that sought to remain on-prem, she says the pandemic drove many to change their structure and operations. That may have influenced their approach to DevOps as well. “Some organizations that had to pivot very quickly to work remotely still had on-prem datacenters,” Groll says. “Last year pushed us into the future faster than we were prepared for.”

Though newer, cloud native companies might wonder why anyone would pursue DevOps on-prem, it can make sense for some to adopt such a development strategy, says Johan Karlsson, senior consultant with Perforce Software, a developer of app development tools.

Legacy organizations, he says, might still be slow to migrate to the cloud for a variety reasons even if their IT represents a cost center. “For them to move to the cloud it’s a cultural journey,” Karlsson says. A company might need to do a bit of soul searching before embracing DevOps in the cloud if the organization is very used to an in-house strategy. “On-prem is often associated with a slow IT department, filing requests, and getting access to your hardware,” he says. “All of that is a tedious process with a lot of internal approval steps.”

IT bureaucracy aside, there may be performance needs that drive organizations to stick with on-prem for DevOps and other needs, Karlsson says. “Certain computers may want to be close to certain other computers to get things done fast,” he says. “Putting things on a machine somewhere else may not immediately give you the performance you are looking for.”

That may have been the case pre-pandemic, Karlsson says, for offices that were not near a datacenter. Keeping resources on-prem also retains full control over the IT environment, he says. There also may be regulatory pressures such as working with government entities that preclude operating in the cloud, Karlsson says, where data can cross national borders. Data privacy regulations might also restrict what information can be moved to the cloud or be seen on networks. “In medical device development, there’s a reason why they need to be 100% sure where the data is all times and that’s the reason why they stay on-prem,” he says.

Nondomestic organizations may have additional considerations to make, Karlsson says, about how their DevOps strategy might play out in the cloud given that the major cloud providers are American companies with very US and Western European-centric services. Users in Eastern Europe, Australia, Asia, and other locals might feel disconnected, he says. “If you’re developing products that are typically distributed around the world or you’re located outside of Silicon Valley, there may be a strong need to have things closer to you because it’s too far away and doesn’t comply with local regulations,” Karlsson says.

Overcoming Digital Transformation Challenges With The Cloud

Here’s how cloud computing can enable the future of work, accelerate data strategies, integrate AI and cyber strategies, and innovate for social good.

Digital transformation remains a top priority for this year, with remote work, digital transactions, customer interactions, and business collaboration all requiring flexible, personalized solutions. Cloud is the essential orchestrator and backbone behind everything digital.     

As cloud providers see continued growth and cloud migration projects abound, we should stop to ask —why?

Image: krass99 - stock.adobe.com

Yes, the cloud can scale infrastructure, applications, and data services at speed as demand shifts. We don’t think about cloud powering our digital apps, teleconferencing, collaboration tools, remote work and education, video streaming, telehealth, and more (until there’s an outage) — but it does.

As organizations innovate their business strategies and implement their 2021 technology roadmaps, a cohesive cloud strategy can address four major challenges facing organizations — digital work, data modernization, integrated business solutions (e.g., AI), and social impact.   

1. Cloud and the future of work

During 2020, organizations embraced a work from anywhere (WFA) model that accelerated the use of cloud collaboration tools, video conferencing, cloud applications, and cloud infrastructure to support work. Where in January 2020, only 3% of full-time employees worked remotely, by April 2020 that number increased to 64%, according to SHRM — with 81% of the global labor force impacted by May 2020 according to the International Labor Organization.  In response, one cloud collaboration platform vendor reported it almost quadrupled its active daily users for that period.  As organizations and the workforce embrace the digital workplace, the future of work will be powered by the cloud.

Additionally, organizations have realized on-premise data centers require access to the “workplace,” which will remain a challenge in 2021 that can be solved by cloud data centers. Those with essential workers have embraced innovative cloud native digital solutions to protect workers and advance the HR technology strategy.

2. Cloud data platforms and ecosystems

The cloud can enhance information sharing and collaboration across data platforms and digital ecosystems. Deloitte research shows 84% of physicians expect secure, efficient sharing of patient data integrated into care in the next five to 10 years. Real world evidence will be critically important in enhancing digital healthcare with historical patient data, real-time diagnostics, and personalized care. Organizations can leverage the cloud for greater collaboration, data standardization, and interoperability across their ecosystem. Research shows digital business ecosystems using cloud experience greater customer satisfaction rates, with 96% of organizations surveyed saying their brand is perceived better and saw improved revenue growth — with leaders reporting 6.7% average annual revenue growth (vs. 4.9% reported by others).

As businesses scrambled to adapt to the unprecedented level of disruption due to the COVID-19 pandemic, it became clear that the increased use of cloud resources was the key to maintaining business operations.

Brought to you by InformationWeek

3. Cloud for integrated business applications

New Cloud ML approaches for developers and data scientists have become available. These include Cloud AI platforms where organizations bring their existing AI models into the cloud; Cloud ML services where organizations can tap into pretrained models, frameworks, and general-purpose algorithms; and AutoML services to augment their AI teams. In the retail sector, organizations have embraced cloud ML to create digital businesses and predict shifting customer demands. Financial services organizations have used the cloud to modernize legacy lending applications for small businesses during the crisis. And, in the technology, media, and telecommunications sector, the cloud is powering your favorite video streaming service.

As organizations rely on the cloud, cloud security becomes increasingly important for data integrity and workload and network security. Information leakage, cloud misconfiguration, and supply chain risk are the top concerns for organizations. A federated security model, zero trust approach, and robust cloud security controls can help to remediate these risks, increase business agility, and improve trust.

4. Cloud innovation and social impact

Finally, organizations are innovating new “intelligent edge” computing architectures by combining cloud, edge, AI, AR/VR and digital twin technologies that tap into the potential of the spatial web. The innovation and social impact potential are tremendous. Smart buildings have the potential to better report on energy consumption across a smart grid network with the cloud. Farms can benefit from precision agriculture solutions. The potential to use cloud to innovate for business and social impact is a rapidly maturing opportunity for the social enterprise.