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Understanding The Differences Between Machine Learning, Deep Learning and Statistical Pattern Recognition

Brian Geary

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From artificial intelligence to artificial neural networks, from machine learning to deep learning and from computer vision to statistical pattern recognition, the nearly endless array of artificial intelligence terminology and – some might argue – buzzwords, is nothing but the inevitable side-effect of a highly accelerated advancement of this field.

But these aren’t just silly buzzwords we use to sound cool (well, not always), and while to the average Joe, all these terms tend to sound alike, it’s simply because many of them have been used more or less interchangeably in the popular press. However, there are subtle and not so subtle differences, and in this article, I’ll untangle and demystify some of these concepts for you.

Machine Learning

Machine learning is an umbrella term that covers all technologies in which a machine is able to “learn” on its own, without having that knowledge explicitly programmed into it. Most types of machine learning are iterative in nature and become better over time at whatever task they are being asked to perform.

To understand the difference between machine learning and other forms of artificial intelligence, consider two game-playing computers: IBM’s Deep Blue, which defeated world champion Garry Kasparov at chess, and Google’s AlphaGo, which defeated world-champion Go player Lee Sedol.

Deep Blue didn’t “learn” the best moves to make; instead, it performed a sophisticated search during every one of its moves, evaluating every possible move for the current board position, the possible moves after that, and so on. From this analysis, Deep Blue selected the one move most likely to result in victory. It then repeated the process at its next turn.

By contrast, AlphaGo learned the best moves by playing thousands of matches against other computerized Go players and other instances of itself. Its proficiency increased with experience.

Deep Learning

Deep learning is a special case of machine learning and is a type of artificial neural network. Artificial neural networks attempt to mimic, on an extremely limited scale, the workings of a biological brain. An artificial neural network is a collection of software objects, or “neurons,” each of which produces an output value according to a formula that accounts for the number of input signals and the strength of each.

When an artificial neural network “learns,” it starts with a set of training data that a human has already annotated; for example, a set of images that are re-classified as “dog” or “not dog.” An artificial neural network identifies patterns in the images, and, without human intervention, tweaks the formulas of its neurons until it settles on a set of formulas that takes the input images and reliably outputs a “dog” or “not dog” value.

In a deep learning system, the neurons are organized into sets called layers: usually an input layer, an output layer, and one or more “hidden” layers.

Neurons in one layer typically are connected only to neurons in an adjacent layer; they don’t “skip” layers or communicate with other neurons in their own layer. However, depending on the design, signals can either travel in only one direction (input to output) or travel both forward and back.

Statistical Pattern Recognition

Statistical pattern recognition has more to do with the task a machine learning system is trying to accomplish. As with humans, one way that a machine “learns” is by recognizing patterns. These can be visual patterns in images, patterns in sound or other types of signals, or patterns in text, financial data, weather data, or anything else where every example of a thing is different but they all possess certain similarities.

A machine learning system can be configured to recognize patterns using sophisticated statistical analysis to classify the data objects (images, transactions, or what have you). The results might be in the form of a likelihood value or probability percentage, rather than a strict “yes” or “no.”

At first, this approach might result in many “false positives” and “false negatives,” but over time and with additional training, those percentages should increase.

As might be expected, a human performs pattern recognition much more quickly and efficiently than a computer. Show a child three pictures of different dogs and she will immediately and reliably be able to classify pictures she has never seen before as “dog” or “not dog.”

Computers achieve this level of proficiency only after examining thousands of pictures, taking a stupendous amount of time and computing power to do so.

Machine learning and all of its types and variations are still in their infancy, and can only tackle very narrowly defined tasks. Yet, given the tremendous strides made in recent years, it is only a matter of time before practical machine learning systems are available for the average PC, laptop, or smartphone devices.

Brian is a senior account manager and a true believer in the Agile process. In addition to his technical background, Brian brings 10+ years of design, marketing and account management experience to AndPlus.

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Fast Charging for iPhone and Android Smartphones

Steven Sanders

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Fast charging for our portable devices is becoming a more important thing to use. Smartphones are evolving, they’re becoming a lot more powerful, and therefore they burn into their battery power even faster. To offset this problem, companies have made the batteries that go into their phones larger.

This can cause a problem though, as larger batteries need a longer time to recharge fully. That’s where the fast charging tech, such as Power Delivery and Quick Charge come in. Both of these charging technologies are among the most used with smartphones, and we’re going to be going over chargers that make use of both of them.

That’s because most Android smartphones are compatible with Quick Charge, they’re also able to fast charge with a  USB-C Power Delivery port, too. Whereas, the iPhone X, iPhone 8, and the iPhone XS are not Quick Charge compatible, but they are Power Delivery compatible and can be charged with a Type-C port with a C to Lightning cable.

RAVPower USB-C Power Delivery Wall Charger with Quick Charge

Starting off very simple, this wall charger has a single USB-C Power Delivery port and a Quick Charge port. When it comes to fast charging for a Power Delivery port, you have to make sure that the port has an 18W charging speed or higher. Which is what this wall charger has.

Even though this wall charger does have both fast charging technologies, the negative part is that it has a max output of 18W, too. So you can use the full power of a single port only once at a time.

However, the lack of power is made up with the form factor of the charger, as it has a retractable AC adapter that makes the charger into a cube.

Satechi Power Delivery Desktop Charger with Quick Charge

Then there are desktop chargers, which are practically wall chargers, but they have more charging ports, and they use a power cord, instead of a built-in AC adapter. Some might think that the use of a power cord can be cumbersome, but it allows you to place the charger closer to where you want to charge your devices.

This Satechi charger has a very powerful USB-C Power Delivery port with a 60Watt charging speed. You’re definitely able to fast charge an iPhone or Android smartphone with the Type-C port, but it doesn’t just stop there. No, you can actually charge USB-C laptops with this Satechi charger, too, as there’s so much PD charging to use.

The other three ports on this charger are a Quick Charge port and two 12W ports.

To top it all off, the charger has a light sensor, and it dims its LED power light when the charger is in a dark room and the light brightens up when the charger is in a bright room.

AIDEAZ 20,000mAh Power Delivery Quick Charge Wireless Charging Power Bank


One charging product that basically everyone should own is a portable charger. It happens all the time, you know when you’re out and about and then you suddenly get the message that your phone is low on battery power. Panic sets in and then your phone is useless with a dead battery.

All that anxiety can practically be erased with the use of a portable charger, which can charge your smartphone while you’re on the move.

The power bank above isn’t some sort of fancy title that we gave, the AIDEAZ power bank is actually capable of those three things. So the charger does have a Power Delivery port with an 18W charging speed, a Quick Charge port, and yes, you can even place your Qi-compatible phone on top of the power bank and it’ll charge.

One other very cool part of this power bank is its use of an LCD display. The display shows how much power is remaining and what charging method is being used.

Aukey 10,000mAh Quick Charge Power Delivery Slim Power Bank


On the lower capacity side, this is Aukey’s Power Delivery portable charger with Quick Charge. The charger has a 10,000mAh power capacity that can be used to charge most smartphones to full power about two times.

What’s most notable about this power bank is recharging it. That’s because it has three input ports that can be used to recharge it. There’s a Micro-USB input, a USB-C input (which is also the USB-C Power Delivery output), and there’s also a Lightning input port, too. Not many portable chargers make use of a Lightning input port, but it’s a huge plus for iPhone users as they can make use of it a lot more easily.

A charger like this Aukey one is one of the best portable chargers to get, as you have so many options to recharge it.

Aukey Power Delivery Car Charger with Quick Charge


One other charging product that many people should consider using more often are car chargers. The reason that car chargers are so helpful is that you’re not using your phone and the screen is off. When that’s happening, your phone is able to charge at its fast charging rate.

This Aukey charger has a Type-C Power Delivery port, and a Quick Charge USB-A port. The most notable part of the charger though, is that it has a flush fit form factor. Therefore the entirety of the charger is able to fit into a 12Volt outlet and not get in the way and it’s super low-profile.

Anker PowerWave Wireless Charging Stand


Then to top it all off, there are wireless chargers. If you’ve got an Apple iPhone that is Qi compatible, meaning any iPhone that came after the iPhone X, then you’re able to wirelessly charge your iPhone. On the Android side, if you have a Samsung smartphone, having a wireless charger is even better, too, as Samsung wireless charging smartphones are fast charging compatible, too.

The same is true for iPhones.

iPhones are able to have fast wireless charging speed of 7.5W, while Samsung phones are able to charge at a 10W charging speed. The main thing to remember though is that there are select chargers that are able to provide “Fast Wireless Charging”.

The Anker Powerwave Wireless Charging stand above is able to fast charge Samsung smartphones at a 10W charging speed and iPhones at a 7.5W speed. Along with that, you get the stand form factor that makes it easier to use your smartphone while it charges on it. You can also place your phone horizontally as the charger has two coils, one at the top and one at the bottom.

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Console vs. Mobile vs. PC: Three Kinds of Gaming

Steven Sanders

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Video games have come a long way since Pong, and we now have a variety of different genres to play across a range of platforms. Gamers will always debate amongst themselves about the strengths and weaknesses of each platform, but they will nearly always show some form of bias for their preferred gaming system.

Over the course of this article, we’ll be covering the three primary types of game systems in this day and age. We’ll take a look at highly portable mobile platforms, available game consoles, and powerful gaming PCs, comparing each of them so that you can see exactly how they differ from each other.

PC

PC gaming is often seen as the most cutting-edge way to play your games, and it makes sense. A gaming PC is a lot easier to keep updated than a console since you can replace the components as soon as they come out. Console gamers instead have to wait until the next iteration of their system comes out.

Of course, a PC is also much more versatile than a console, as you can custom-make one that isn’t constrained by whether or not it will be feasible on the market. Keep in mind that gaming PCs pay for their impressive performance and graphics when it comes to stability, with the quality of releases depending on their degree of optimization.

Console

Console gaming is often seen as the more convenient alternative to PC gaming, and there is significant overlap between the games that are available on both types of systems. Console games will typically run at a lower frame rate and a lower resolution than PC games due to the inherent limitations of the systems.

Since a game console has to be reasonably priced, then there is a limit to the performance they can output, and yet they provide immense value for money. You would be hard pressed to find a gaming PC complete with a keyboard, mouse, operating system, and monitor for the price of a console.

Mobile

Finally, mobile gaming takes up a huge percentage of the global gaming market, and that’s what makes it so attractive for game development services. Whenever you have a bit of downtime, you can simply take out your smartphone and start playing a game, and the massive number of ads rakes in a tidy profit.

While there are some games (like Fortnite) that are available on mobile, console, and PC, you’ll find that the majority of mobile games are not available on the other systems due to their simplicity. Mobile games usually have simple control schemes due to the difficulty of adapting them to a touchscreen.

Conclusion

There is no “best” way to play video games, so don’t let anyone discourage you based on your preferred platform. We hope that this guide has summarized the differences between each of these kinds of game systems.

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The Pros and Cons Behind DevOps as a Service

Steven Sanders

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It seems as though every component of business computing is being used as a service, including DevOps. The advantages of using devops as a service are obvious: You are able to rent computing resources instead of having to buy and manage them on your own.

However, is it possible to outsource each aspect of business operation? Can DevOps as service work for your organization? Does the cloud collaboration between operations and developments help speed up projects, or does it mean that your company will lose control of business-centric applications?

Before discovering the arguments supporting and refuting devops as a service, it’s good to define the meaning behind DevOps?

What is DevOps as a Service?

The term DevOps comes from the creation of operations and development, two different disciplines. Some traditional companies have departmental silos that make it difficult for IT professionals to work on creating business automation software.

DevOps creates an environment needed for the rapid testing and development of custom business software. Making a DevOps-based collaborative environment is easier for security specialists, IT engineers, QA engineers, and other teammates to ensure that there is synchronization, integration, and synergy between workflows.

To ensure that your DevOps environment is successful, your team will need to use agile software methodologies. The more difficult the project, the more enterprise components you’ll need to ensure that your team works properly.

DevOps as a service allows you to relocate those enterprise resources towards the cloud. Rather than using basic software development tools, DevOps as a service collects the development tools towards a platform that’s hosted in the cloud.

Advantages Behind DevOps as a Service

Here are some reasons why companies are starting to use DevOps as a service:

  • DevOps as a service hides the complexity of information and data flow, which means your DevOps team members can focus on their team specific tools without having to know the entire toolchain. For instance, a software developer can conduct tests through source code management tools, and IT operators can make changes with configuration management tools.
  • DevOps allows users to collaborate as it places tools on the cloud. This allows users anywhere to work together and complete projects.
  • Using cloud-based services is a data-driven process where everyone has the same data set. This leads to better quality control and documentation.

Disadvantages Behind DevOps as a Service

Here are the disadvantages that exist when using DevOps for your IT team:

  • Security is always a huge concern. Your security team isn’t always apart of DevOps and the DevOps teams usually choose speed over security when creating software. With DevOps cloud services, you can create unnecessary exposure and risks, especially if its the transport layer that’s left unsecured.
  • Outsourcing DevOps infrastructure will require some level of software development expertise, including having an understanding of orchestrating a workflow, infrastructure, and integration. You’ll need experts and tools of DevOps as a Service in order to be successful.

Conclusion

When you’re using DevOps as a service, you’re increasing your IT teams’ productivity. And if you’re thinking about making a new DevOps strategy, DevOps as a Service will help shorten the time to deploy apps and will give you versatility as you create new business process applications.

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