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Smartphone photography underwent two major trends in 2023: the adoption of bigger sensors with megapixel counts stretching into the hundreds and the growing number of use cases for computational photography. Not to mention the mainstream adoption of triple cameras as well.

Two smartphones epitomize these trends and their different approaches to mobile photography. On the one hand, there’s the Xiaomi Mi Note 10 with its 108MP main sensor and quintuple rear camera configuration. On the other, the Google Pixel 4 offers a more modest dual rear camera configuration with just 12MP and 16MP of resolution each.

Of course, these two phones cater to two rather different price points. The Xiaomi Mi Note 10 is a much more affordable smartphone, while Google’s Pixel 4 and 4 XL come with flagship-tier price tags. However, both pride themselves on their photography capabilities and make great showcases for these two prevailing approaches to improving smartphone picture quality. If you want a rundown of the two phone’s camera specs, check out the table below.

See the full-res photos on Google Drive

108MP vs 12MP

We’ll get the really obvious and least interesting comparison out of the way first. On paper, the 108 megapixels of the Mi Note 10 offers vastly more detail capture than the 12MP main camera on the Pixel 4. Although when you consider than the Xiaomi handset defaults to 27MP through the use of pixel binning, the discrepancy isn’t as large as it first seems.

Our first sample reveals close to a 4x cropable zoom difference between the two cameras, thanks to Xiaomi’s massive resolution. However, closer inspection reveals that at 108MP the Mi Note 10’s images are heavily processed and don’t contain as much detail as we typically expect from a 100% crop. There’s a fair amount of noise in all the images captured at 108MP, making the files not worth their huge 22MP size.

In this lower-light shot, note how both phones are noisy and quite heavily processed. You can still crop in closer with the Xiaomi, but the fine details are mushed together due to the lack of light. The huge sensor still gives you a decent crop factor that well exceeds the Pixel 4, but there’s a reason the Mi Note 10 defaults to 27MP. In less than perfect conditions, you simply can’t max out the huge resolution.

Unfortunately, we can also see a few purple patches of chromatic aberration distortion on the tree trunks from the poor quality lens slip into the second image. Just as worryingly for Xiaomi’s sensor implementation, I was actually able to obtain superior distant detail using Google’s software zoom versus its 108MP sensor. Although both are much too ugly to want to use as a 100% crop.

108MP gives you more detail, but results are highly environment-dependent.

Overall, the Xiaomi Mi Note 10’s 108MP sensor is a bit of a disappointment when it comes to providing additional detail capture. You’ll gain some benefit, providing you’re in bright daylight, but nothing close to 108MP of actually usable detail. Better to stick to the 27MP pixel binned-mode.

In reality, we’re looking at something closer to a 27MP versus 12MP resolution difference. The image above of a 27MP vs 12MP shows the actual crop benefits you’ll get from Xiaomi’s camera. Just over a 2x free crop factor is notable, but not game-changing, given the prevalence of telephoto zoom capabilities.

The Mi Note 10 certainly captures more detail as the Pixel 4 and produces a smoother image in its 27MP mode. However, the results vary greatly. Hence why Xiaomi chose to include a wide range of zoom cameras too.

Detail at a distance

Both the Mi Note 10 and the Pixel 4 offer telephoto zoom capabilities. Google finally came around to the idea and implemented a 2x optical zoom camera. Xiaomi goes further, offering not only a 108MP sensor for digital crops but also 2x and 3.7x optical cameras too. The Mi Note 10 hits up to 5MP lossless zoom by cropping in on the 3.7x camera’s 8MP sensor. However, Google also implements a machine learning-based super-resolution zoom technology that obtains very decent results at long range as well.

At 2x, the optical zoom of both phones’ cameras, the Pixel 4 produces a much more natural, less processed look. It’s arguably a tad on the soft side but does a great job at capturing detail, exposure, and color. The Xiaomi Mi Note 10 provides a hefty dose of oversharpening that ruins the look of the image on closer inspection. Both pictures look decent at full frame, but the Pixel 4 presents the cleanest image.

At 3x, we see Google’s software implementation come into play. The image is again quite soft, but the bulk of the important details remain in the full-frame shot. Xiaomi’s small zoom sensor, by comparison, has the opposite problem. Although Xiaomi captures more fine detail, the crop reveals some noise that’s made worse by a sharpening pass. The image is also overexposed.

The best at low light

The Xiaomi Mi Note 10 and Google Pixel 4 offer two very different takes on low-light photography. Google continues to focus on its multiple exposure, HDR+, and Night Shot technologies. Meanwhile, Xiaomi’s 108MP sensor uses pixel binning technology to offer 27MP images with large 1.6µm sized pixels. That makes each pixel slightly larger than the Pixel 4’s 1.4µm and should, at least in theory, offer slightly better low light performance. So which will win out in low light: hardware or software?

This image showcases the typical differences between the two cameras in low light. The Mi Note 10’s larger sensor results in a better color balance and less noise than the Pixel 4. The Pixel 4’s reliance on multi-exposure software produces a more over-processed look with harsher edges. However, Google’s HDR+ does a better job at picking out details in low light. Take a look at the rock textures, for example.

This second example highlights the difference in noise capabilities. The Pixel 4 exhibits black crush and noise towards the left and bottom of this crop. Resulting in a loss of detail. There’s no such issue for the Mi Note 10 and its colors are also more vibrant and realistic. The phone does experience a larger lens flare problem than the Pixel 4, but both have issues here when shooting into the sun.

Bokeh hardware vs software

To create depth maps, Xiaomi uses a combination of its telephoto camera, 108MP sensor, and software algorithms. The bokeh is developed from the combination of the main sensor’s wide lens aperture and software techniques. The Pixel 4 uses a very similar approach with its two cameras, allowing Google to use camera perspective differences to obtain more accurate results than previous generations.

Both phones exhibit familiar bokeh issues, albeit to slightly different extents.  The Pixel 4 has a little more trouble with edges, while the Mi Note 10 is more so-so on foreground and background separation. Edge detection on both handsets is reasonably good, providing that you avoid complex textured backgrounds. Sadly, Xiaomi’s software pass removes far too much image detail and the quality of its software bokeh is not as good.

In the second example, the Mi Note 10 places parts of the skull and android in two different planes. This error bleeds some blur into the foreground prematurely, although other edges are detected very well. While the Pixel 4 identifies front and background planes more conclusively, it struggles with the glass edges and doesn’t blend into its bokeh blur as seamlessly. Furthermore, Google still doesn’t allow you to remap the focal point in post-processing, which remains a major bugbear of mine. Xiaomi has no problem with this, although its bokeh processing times are notably slower than Google’s.

Overall, the two perform admirably at bokeh edge detection but both are hit and miss, as is typical of all phones. However, the quality of Google’s blur effect is notably better than Xiaomi’s, resulting in nicer looking results in most scenarios.

Computational photography vs 108 megapixels: the verdict

I’m a big fan of Xiaomi’s color grading and white balance. If nothing else, the Mi Note 10 nails these points better than Google’s flagship Pixel 4. Both phones take great-looking photos in a variety of environments, demonstrating that there are still quite a few ways to achieve great-looking pictures.

However, the 108MP and quintuple camera arrangement in the Mi Note 10 is more hype than substance. The combined camera capabilities are certainly very flexible. However, the results are mixed. The 108MP sensor certainly offers more detail than the Pixel 4’s 12MP sensor, but it only shines in perfect daylight conditions. In lower light, the detail difference between these sensors is far less pronounced than the numbers suggest. Zoom-wise, Xiaomi’s cameras are passable but not quite as good as the best out there, and its software bokeh algorithm could be improved. Despite the Mi Note 10’s huge range of sensors, it doesn’t quite master any of them.

Computational photography helps the Pixel compete on flexibility with just two sensors.

The Pixel 4 proves that you can obtain similarly flexible and great-looking results with just a couple of cameras and very smart software. Of course, not everyone has made the computational photography investments that Google has. But this is where high-end phones can continue to add value over more affordable models.

Computational photography squeaks into first place in this shootout. However, Google’s next-gen Pixel could certainly learn a few tricks from Xiaomi. Most notably using a bigger sensor for even better low-light performance. Afterall, computational photography still benefits from better underlying hardware. Despite the verdict, the Xiaomi Mi Note 10 is an excellent shooter for its price point. It rivals much more expensive smartphones, like the Pixel 4, and should certainly be on your radar if you’re after a great camera phone on a budget.

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What Is Computational Photography And Why Does It Matter?

What is computational photography?

Robert Triggs / Android Authority

The term computational photography refers to software algorithms that enhance or process images taken from your smartphone’s camera.

You may have heard of computational photography by a different name. Some manufacturers like Xiaomi and HUAWEI call it “AI Camera”. Others, like Google and Apple, boast about their in-house HDR algorithms that kick into action as soon as you open the camera app. Regardless of what it’s called, though, you’re dealing with computational photography. In fact, most smartphones use the same underlying image processing techniques.

Techniques and examples of computational photography

With the basic explanation out of the way, here’s how computational photography influences your photos every time you hit the shutter button on your smartphone.

Portrait mode

Super resolution zoom / Space zoom

Night mode / Night Sight

Replace the whole sky

Here’s a fun application of computational photography. Using the AI Skyscaping tool in Xiaomi’s MIUI Gallery app, you can change the color of the sky after you capture a photo. From a starry night sky to a cloudy overcast day, the feature uses machine learning to automatically detect the sky and replace it with the mood of your choice. Of course, not every option will give you the most natural look (see the third photo above), but the fact that you can achieve such an edit with just a couple of taps is impressive in its own right.

Face and Photo Unblur

Action pan and long exposure

A brief history of computational photography

Even though you may have only recently heard about it, computational photography has been around for several decades. However, we’ll only focus on the smartphone aspect of the technology in this article.

In 2013, the Nexus 5 debuted with Google’s now-popular HDR+ feature. At the time, the company explained that the HDR+ mode captured a burst of intentionally over- and under-exposed images and combined them. The result was an image that retained detail in both, shadows and highlights, without the blurry results you’d often get from traditional HDR.

Machine learning enabled features like night mode, panoramas, and portrait mode.

Apple eventually followed through with its own machine learning and computational photography breakthroughs on the iPhone XS and 11 series. With Apple’s Photonic Engine and Deep Fusion, a modern iPhone shoots nine images at once and uses the SoC’s Neural Engine to determine how to best combine the shots for maximum detail and minimum noise.

We also saw computational photography bring new camera features to mainstream smartphones. The impressive low-light capabilities of the HUAWEI P20 Pro and Google Pixel 3, for instance, paved the way for night mode on other smartphones. Pixel binning, another technique, uses a high-resolution sensor to combine data from multiple pixels into one for better low-light capabilities. This means you will only get a 12MP effective photo from a 48MP sensor, but with much more detail.

Do all smartphones use computational photography?

Most smartphone makers, including Google, Apple, and Samsung, use computational photography. To understand how various implementations can vary, here’s a quick comparison.

On the left is a photo shot using a OnePlus 7 Pro using its default camera app. This image represents OnePlus’ color science and computational photography strengths. On the right is a photo of the same scene, but shot using an unofficial port of the Google Camera app on the same device. This second image broadly represents the software processing you’d get from a Pixel smartphone (if it had the same hardware as the OnePlus 7 Pro).

Right off the bat, we notice significant differences between the two images. In fact, it’s hard to believe we used the same smartphone for both photos.

Looking at the darker sections of the image, it’s evident that Google’s HDR+ algorithm prefers a more neutral look as compared to OnePlus, where the shadows are almost crushed. There’s more dynamic range overall in the GCam image and you can nearly peer into the shed. As for detail, both do a decent job but the OnePlus does veer a tad bit into over-sharpened territory. Finally, there’s a marked difference in contrast and saturation between the two images. This is common in the smartphone industry as some users prefer vivid, punchy images that look more appealing at a glance, even if it comes at the expense of accuracy.

Even with identical hardware, different computational photography methods will yield different results.

This comparison makes it easy to see how computational photography improves smartphone images. Today, this technology is no longer considered optional. Some would even argue that it’s downright essential to compete in a crowded market. From noise reduction to tone mapping depending on the scene, modern smartphones combine a range of software tricks to produce vivid and sharp images that rival much more expensive dedicated cameras. Of course, all this tech helps photos look great, but learning to improve your photography skills can go a long way too. To that end, check out our guide to smartphone photography tips that can instantly improve your experience.


No. Computational photography is a software-based technique used by smartphones to improve image quality. On the other hand, computer vision refers to using machine learning for detecting objects and faces through images. Self-driving cars, for example, use computer vision to see ahead.

Yes, iPhone embraced computational photography many years ago. With the iPhone XS and 11 series, Apple introduced the Smart HDR and Deep Fusion.

Malwarebytes Browser Guard Vs Opera: Which One Is Better?

Malwarebytes Browser Guard vs Opera: Which one is better? Become more knowledgeable about which one is the better choice.




This article will compare the security features of Malwarebytes Browser Guard vs. Opera browser.

You will also read our M

alwarebytes Browser Guard review in this software faceoff.

You will also find out if Malwarebytes Browser Guard is safe for your computer.

Our verdict took into consideration all the aspects and features of both solutions.

Struggling with various browser issues? Try a better option: Opera One

You deserve a better browser! Over 300 million people use Opera One daily, a fully-fledged navigation experience coming with various built-in packages, enhanced resource consumption, and great design.

Here’s what Opera One can do:

Optimize resource usage: Opera One uses your Ram more efficiently than Brave

AI and User Friendly: New feature directly accessible from the sidebar

Gaming friendly: Opera GX is the first and best browser for gamers

⇒ Get Opera One

There are many ways to protect your privacy online, and some users prefer using security extensions while others prefer privacy-focused browsers.

Today we’re going to compare one of the best security extensions, Malwarebytes Browser Guard, to the Opera web browser and see which offers users better security features.

Is it safe to install Malwarebytes browser Guard? Does Malwarebytes browser Guard track you?

Malwarebytes creators and developers state that they only collect data necessary for the software’s functionality or for the performance of providing the software to clients.

The team also mentioned that the Malwarebytes website uses trackers to monitor how readers engage but that they do not gather any personal information.

How do I choose between Malware Browser Guard and Opera? Opera

Opera is a web browser that offers various privacy and security features out of the box. This is why Opera is the browser of choice for many users worldwide.

What features does Opera have?

An incorporated VPN tool is also available, offering unlimited bandwidth, free of charge.

The battery saver feature provides your PC with an additional hour of battery life.

Opera is available on all primary desktop and mobile platforms and fully supports syncing your work across all of them via the Opera Flow feature.

Let’s take a look at the Opera’s best features:

Built-in ad blocker

Unlimited and free VPN

Customizable start page

Advanced tab management

Support for extensions


For guaranteed data protection while surfing online, try a complete browser such as Opera.

Download Visit website

Malwarebytes Browser Guard

Expert tip:

Malware Browser Guard is a browser extension that protects your privacy and security online. The extension is currently available for both Chrome and Firefox.

What features does Malwarebytes Browser Guard have?

Malwarebytes Browser Guard is designed to fight scammers, and it identifies any browser lockers, browser hijackers, and other tactics that scammers use and warn you about them accordingly.

The extension can also detect malicious websites, and it will even stop cryptocurrency miners from running in the background.

Let’s see what the best features for Malwarebytes Browser Guard are:

⇒ Download Malwarebytes Browser Guard

The final verdict: Opera vs. Malwarebytes Browser Guard

We’re sure you’re curious to find out the results of this Malwarebytes-Opera confrontation, so here’s where we draw the line.

While Malwarebytes Browser Guard offers some great features, it can’t compare to Opera regarding privacy and security.

Opera has all the features that Malwarebytes Browser Guard has, plus a free VPN to top of it all. Not to mention that Opera can be used as a fully-featured browser.

So, if you’re looking for a web browser that will protect your privacy without any extensions, Opera is the way to go.

Know that since the latest builds of Opera are based on the same Chromium source code as Chrome, you should be able to install the Chrome version of Malwarebytes Browser Guard without any issues.

That is, if you are looking for a Malwarebytes extension for your Opera browser.

What about you? What is your browser of choice? Are you using any security extensions in your browser?

Still experiencing issues?

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Ipad Vs Ipad Pro: Which One Is Right For You?

Oliver Cragg / Android Authority

There’s little denying that Apple is the undisputed tablet leader, thanks to the iPad. If you’re in the market for a new iPad, you have quite a few options ranging from the more modest iPad Mini to the impressive iPad Pro. Of course, you can always consider picking up the classic iPad. How does the 10th gen iPad compare to the high-end iPad Pro (M2)? Let’s take a look at this iPad vs iPad Pro comparison.

iPad vs iPad Pro: At a glance

Curious about how the iPad and iPad Pro compare? Here’s a quick summary of the key differences:

iPad Pro has a more powerful processor than the iPad

iPad Pro features Wifi 6e, vs the older Wi-fi 6 on the iPad

The iPad has a dual camera configuration, while the iPad has just one lens

The iPad has a fingerprint scanner for security, but the iPad Pro uses Face ID

The iPad Pro has a better speaker system than the iPad

The iPad Pro has more storage capacity options than the iPad

iPad vs iPad Pro: Specs

iPad vs iPad Pro: Size comparison

The design language remains consistent across the two devices, though the Pro has a different camera configuration and larger display options. The classic iPad also has more playful colors, while the Pro takes a more serious approach with only Space Gray and Silver options.

The iPad Pro is much larger and heavier than the iPad, especially if we’re talking about the 12.9 inch display variant. The iPad weighs just 277g, vs 466g and 641g on the 11 and 12.9 inch iPad Pro models.

Bottom line: the iPad and iPad Pro are both lookers, but the Pro feels a bit more polished.

iPad vs iPad Pro: Camera

Oliver Cragg / Android Authority

Let’s face it; you’re not buying an iPad to take photos. The main purpose of an iPad’s camera is for video conferencing or taking the occasional selfie. Both of these tablets are more than up for that job, but they handle it differently.

The iPad has a single rear camera, the same one found on the iPhone SE (2023). It can take a decent photo if the lighting is good, but again you won’t want to lug it around to take photos very often, so this is more for use in a pinch. I’ve done it before with my own iPad, and I can say it’s never a great experience, but it is better than nothing.

The iPad Pro opts for two rear lenses, a 12MP standard and 10MP ultrawide. This configuration was previously used in the original iPad Pro as well. It’s a solid camera, and the addition of ProRes capture is welcome. You won’t find a dedicated zoom lens or anything else too fancy, nor do you need it for a tablet.

Now let’s talk selfies. Interestingly, the iPad is the better setup here. You’ll find a 12MP shooter with f/2.4 aperture on both devices, but the iPad opts for a horizontally aligned position. This landscape-centered setup makes a lot more sense on an iPad. Unfortunately, the iPad Pro sticks to a vertical alignment which doesn’t make nearly as much sense for use cases like video conferencing.

iPad vs iPad Pro: Price

Apple iPad (64GB, Wi-Fi): $449

Apple iPad (64GB, Cellular): $599

Apple iPad (256GB, Wi-Fi): $599

Apple iPad (256GB, Cellular): $749

iPad Pro (M2, 11-inch, Wi-Fi): $799-$1,899

iPad Pro (M2, 11-inch, Cellular): $999-$2,099

iPad Pro (M2, 12.9-inch, Wi-Fi):  $1,099-$2,099

iPad Pro (M2, 12.9-inch, Cellular): $1,299-$2,399

The iPad and iPad Pro have been available since October 26, 2023, and can be found at most major retailers.

The cheapest iPad begins at just $449,  but 64GB is not enough for most of us. You’ll likely want to spring for the $599 256GB variant unless you are fine with having to manage your storage space aggressively. That’s still $200 cheaper than the iPad Pro’s base model with 128GB of storage.

iPad vs iPad Pro: Which should you buy?

Oliver Cragg / Android Authority

iPad Pro with keyboard

Objectively the iPad Pro is a much more powerful tablet than the iPad. If you want a better display, a more future-proof processor, and enough oomph for serious productivity, the iPad Pro is an easy recommendation.

The Pro is a bit overkill if you need an iPad for the basics. If you can afford it and don’t mind spending a few hundred more, it might be nice to have that much power if you ever need it. Like if your laptop breaks and you need to get something done in a pinch.

Would you rather buy the iPad or iPad Pro?

25 votes

Are you confident that the iPad will mostly be used for entertainment and maybe some light productivity once in a blue moon? If yes, you’re probably better off saving money and getting the classic iPad. Not impressed by the iPad and looking for a middle ground? The iPad Air ($599) could also make for a great choice, or even the iPad Mini ($500) if you want something smaller.

iPad vs iPad Pro: FAQ

The iPad Pro is a powerful option for those looking for something with true laptop class power in a more portable mobile package. The Pro is capable of entertainment but is geared towards productivity, whereas the iPad is better suited as an entertainment device or for light, occasional productivity.

While they won’t have access to traditional PC or Mac apps, yes it is possible to use an iPad or iPad Pro as a laptop. In fact there’s an accessory for the Pro called a Magic Keyboard that does just that. Meanwhile, the iPad has a magic keyboard folio case that comes pretty close to delivering a laptop experience.

Yes it is possible, though a laptop typically is better designed for this. Still, Apple supports programmers and even has its own app for just that, called Swift Playgrounds.

Unfortunately, no. It is possible to add an iPad case that will protect it from the water though.

Yes, the iPad Pro does have Face ID, but the same can’t be said for the classic iPad, which uses Touch ID.

No, not out of the box. It is possible to add the function with an adapter.

Headphone jacks are not available on either of these devices, sadly.

Chatgpt Vs Google Bard: What’S The Difference And Which One To Use?

Edgar Cervantes / Android Authority

We finally have our hands on Google’s long-awaited Bard chatbot. It takes aim at the increasingly popular ChatGPT and Bing Chat, both of which are based on the same foundation. Meanwhile, Google has developed its own large language model for Bard, codenamed LaMDA. This is our first encounter with Google’s chatbot, but we’ve already found some aspects that separate Bard vs ChatGPT.

So in this article, let’s pit these two rival chatbots against each other and find out once and for all which one you should use.

Google Bard vs ChatGPT: Knowledge and accuracy

But what if you don’t care about the bleeding edge or recent events? Can ChatGPT keep up with Google Bard, or vice-versa? Let’s take a look at another example.

ChatGPT vs Google Bard: Coding and software development

We already have a dedicated article on ChatGPT’s outstanding ability to write code, but how does Bard perform in the same context? Google hasn’t revealed much about its language model, but it likely had some programming languages included in its training data.

Let’s test it with a straightforward example. I asked both chatbots to write code for a website that shows the current trading price of the S&P 500 index.

ChatGPT is far more capable at writing code than Bard, at least for now.

Digging into Bard’s documentation, I found this snippet: “Bard can’t help you with coding just yet. [It] is still learning to code, and responses about code aren’t officially supported for now.”

That explains everything we need to know about using Bard for software development — it simply cannot do it. So you’d probably be better off using a ChatGPT alternative designed for coding like GitHub Copilot.

ChatGPT vs Google Bard: How and where to use them?

Edgar Cervantes / Android Authority

ChatGPT has gone through numerous updates since its release, while Bard didn’t release until much later. This is probably why Google has locked Bard behind a waitlist as it continues to test its accuracy. But not everyone can join the waitlist as for now, it’s only available in the US and UK. You could use a VPN app to circumvent this restriction, but proceed at your own risk.

We had to wait about a week to access Bard after signing up for the waitlist. However, some owners of Google Pixel phones and Nest products also got early access to the service.

ChatGPT vs Google Bard: Limitations and pricing

Edgar Cervantes / Android Authority

We already know Bard cannot write code. However, it also cannot generate text in languages other than US English, although Google says it’s working to lift both of those restrictions. On the other hand, even though English accounted for over 90% of ChatGPT’s training data, it supports many more languages. You can talk to ChatGPT in French or Chinese, for example, and it will even respond in that language.

Moving on, ChatGPT can hold multiple conversations in memory at once. You can return to past conversations via the history bar to the left of your screen. On the other hand, Bard can only keep track of one conversation at a time. And while both chatbots hold some context in a single conversation, Google has placed intentional limits on how much Bard can remember.

Which Is Better? Bitcoin Vs Ethereum

This article was published as a part of the Data Science Blogathon.

In this article, we will see the two main cryptocurrencies, . Let us learn about them. What differences do they have and which coin is best for investment and what makes that particular coin better. Nowadays cryptocurrencies are quite popular. It is important to learn about them.

Nowadays data science and blockchain are interrelated. Data scientists are using this blockchain technology for authentication purposes and also for tracking the data. Trading with cryptocurrency involves blockchain technology. In the future, this cryptocurrency will change our world and will become part of our life. There is no risk of fraud by using cryptocurrency. It makes transactions super safe. It gives full control to people over their money.

Let’s get started.


We basically use normal currencies like Rupee, Dollar, Pound, Won, and all. Cryptocurrency is also similar to that normal currency. It is a virtual currency. There is no physical currency here. Normal currency is controlled by the central authority. They are centralized whereas cryptocurrency is decentralized. It does not have any central authority. No third parties are involved in this.

For any transaction using cryptocurrency, that particular transaction is done only after a majority of people using the cryptocurrency agreed to it. It is a digital currency that acts as a medium of exchange just like normal currency. Cryptocurrencies use high standards of cryptography for secure transactions. Cryptocurrency uses blockchain technology. As we know, a blockchain is a chain of blocks and a block has a set of records.


Bitcoin is one of the cryptocurrencies and also a leading cryptocurrency among all that uses strong encryption techniques to send and receive money in a secured manner. Bitcoin uses the SHA256 algorithm which makes it more secure. It is a decentralized cryptocurrency. That means no Government or bank will control the working of bitcoin.

1. Payments done are secured by strong cryptography

2. Identities of the sender and the receiver are kept anonymous.

3. The transaction fee is also low and affordable.

Source: CNBC


Ethereum is also known as Ether in short. This Ether cryptocurrency is created in 2023. Ethereum provides Ether tokens to the users and these Ether tokens are used to build and deploy decentralized applications. Ethereum is used to pay for the services and transaction fees. Here the services include the computational power that is required before a block is added to the blockchain. Ethereum is also used for peer-to-peer payments just like bitcoin.

Source: CoinDesk

Bitcoin was the first cryptocurrency that was created and the bitcoin was released in 2009. Bitcoin was created by an unknown person and his name is Satoshi Nakamoto. This technology came into the concept of a blockchain that is very popular nowadays.

On the other side, Ethereum was released recently in 2023. Ethereum was created by Vitalik Buterin who is a researcher and a programmer. In the creation of Ethereum, Vitalik Buterin used the concepts of bitcoin and blockchain and improved them. He provided many more functionalities by creating the Ethereum platform for distributed applications and smart contracts. These smart contracts work in such a way that when a certain set of predefined rules are satisfied then only that particular output takes place. Ether can be used to create these kinds of smart contracts.

Comparison between Uses of Bitcoin and Ethereum

As we know bitcoin enables peer-to-peer transactions. Here bitcoin just acts like normal currency like how we use our normal currency when we need to buy anything from the supermarket. similarly, when any transaction is to be done, bitcoin is used for the transaction between the peers.

On the other side, Ethereum also provides peer-to-peer transactions and along with it, ether also provides the users to create and execute smart contracts on Blockchain We had already discussed smart contracts. Smart contracts allow the users to exchange anything of value like some kind of contracts, shares, money, real estate, and many more.

Validation Process

In bitcoin, transactions are validated by using something known as proof of work. Similarly, Ethereum transactions are also validated by using proof of work. In blockchain transactions are validated by miners. This proof of work involves miners around the world trying to solve a complicated mathematical puzzle to be the first one to add a block to the blockchain. Soon the Ethereum may switch to something known as proof of stake. What exactly proof of stake is, in proof of stake the validator can validate the transactions in the block based on how many coins the person owns. More the number of coins then more the mining power.

Source: Coincu News


When it comes to the rewards for miners, the reward for mining in the case of bitcoin is 12.5 BTC per block. And this reward will become half the original for every 210,000 blocks. When it comes to Ethereum, the miner will get 3 ether every time hen the block is added to the blockchain.

For the bitcoin transaction, the transaction fee is very low and also it is optional. You can pay how much you want in order to get more attention from miners towards your transaction. But in the case of Ethereum, it is not optional. You have to pay 3 ether every time when the block is added to the blockchain. Later this transaction fee is converted into the gas. And then this converted gas will drive the computation that allows your transaction to be added to the blockchain.

To add a block to the blockchain, bitcoin takes about 10 minutes. But in the case of Ethereum, it takes on an average of 12 to 15 seconds only.

These cryptocurrencies use strong hashing algorithms to make them more secure. Bitcoin uses the SHA256 hashing algorithm. Whereas Ethereum uses the Ethash algorithm.

In the market, there are about 17 million bitcoins and 101 million ether coins. Bitcoin has a market capitalization of 110 Billion USD whereas Ethereum’s market capitalization is 28 Billion USD. Even though there are more ether coins than bitcoins, the market value of ether cannot reach the market value of bitcoin. On average, there will be around 219,345 bitcoin transactions every day and 659,051 ether transactions every day. The block size of bitcoin is 628.286 KB whereas the block size of ether is 25.134 KB.

Which one is better?

The major question that arises is between bitcoin and Ethereum which cryptocurrency is better. So far we have discussed two main uses called peer-to-peer transactions and smart contracts. Here definitely Ethereum is the best option.


That’s all about bitcoin and Ethereum which are two leading cryptocurrencies in the market nowadays. These transactions are very secure in that these algorithms are strongly encrypted cryptographic algorithms.

Overall in this article, we have seen about cryptocurrency, and some cryptocurrencies bitcoin, and Ethereum which use blockchain technology. And then we have compared these two coins in several aspects. Finally concluded by understanding which coin is better.

Hope you found this article useful.

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