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Chatbots are taking the world by storm.

SEO pros, writers, agencies, developers, and even teachers are discussing the changes that this technology will cause in society and how we work in our day-to-day lives.

ChatGPT’s release on November 30, 2023 led to a cascade of competition, including Bard and Bing, although the latter runs on OpenAI’s technology.

If you want to search for information, need help fixing bugs in your CSS, or want to create something as simple as a chúng tôi file, chatbots may be able to help.

They’re also wonderful for topic ideation, allowing you to draft more interesting emails, newsletters, blog posts, and more.

But which chatbot should you use and learn to master? Which platform provides accurate, concise information?

Let’s find out.

What Is The Difference Between ChatGPT, Google Bard, And Bing Chat?

ChatGPT Bard Bing Pricing ChatGPT’s original version remains free to users. ChatGPT Plus is available for $20/month. Free for users who joined the waitlist and are accepted. Free for users who are accepted after joining the waitlist. API Yes, but on a waitlist. N/A N/A Developer OpenAI Alphabet/Google OpenAI Technology GPT-4 LaMDA GPT-4 Information Access Training data with a cutoff date of 2023. The chatbot does state that it has been trained beyond this year, although it won’t include that information. Real-time access to the data Google collects from search. Real-time access to Bing’s search data.

Wait! What Is GPT? What Is LaMDA?

ChatGPT uses GPT technology, and Bard uses LaMDA, meaning they’re different “under the hood.” This is why there’s some backlash against Bard. People expect Bard to be GPT, but that’s not the intent of the product.

Also, although Bing has chosen to collaborate with OpenAI, it uses fine-tuning, which allows it to tune responses for the end user.

Since Bing and Bard are both available on such a wide scale, they have to tune the responses to maintain their brand image and adhere to internal policies that aren’t as restrictive in ChatGPT – at the moment.

GPT: Chat Generative Pre-trained Transformer

GPTs are trained on tons of data using a two-phase concept called “unsupervised pre-training and then fine-tuning.” Imagine consuming billions of data points, and then someone comes along after you gain all of this knowledge to fine-tune it. That’s what is happening behind the scenes when you prompt ChatGPT.

ChatGPT had 175 billion parameters that it has used and learned from, including:





While ChatGPT is limited in its datasets, OpenAI has announced a browser plugin that can use real-time data from websites when responding back to you. There are also other neat plugins that amplify the power of the bot.

LaMDA Stands For Language Model For Dialogue Applications

Google’s team decided to follow a LaMDA model for its neural network because it is a more natural way to respond to questions. The goal of the team was to provide conversational responses to queries.

The platform is trained on conversations and human dialog, but it is also apparent that Google uses search data to provide real-time data.

Google uses an Infiniset of data, which are datasets that we really don’t know much about at this point, as Google has kept this information private.

Since these bots are learning from sources worldwide, they also have a tendency to provide false information.

Hallucinations Can Happen

Chatbots can hallucinate, but they’re also very convincing in their responses. It’s important to heed the warning of the developers.

Google tells us:

Bing also tells us:

If you’re using chatbots for anything that requires facts and studies, be sure to crosscheck your work and verify that the facts and events actually happened.

There have been times when these hallucinations are apparent and other times when non-experts would easily be fooled by the response they receive.

Since chatbots learn from information, such as websites, they’re only as accurate as the information they receive – for now.

With all of these cautions in mind, let’s start prompting each bot to see which provides the best answers.

ChatGPT Vs. Bard Vs. Bing: Prompt Testing And Examples

Since technical SEO is an area I am passionate about, I wanted to see what the chatbots have to say when I put the following prompt in each:

What Are The Top 3 Technical SEO Factors I Can Use To Optimize My Site? ChatGPT’s Response

ChatGPT provides a coherent, well-structured response to this query. The response does touch on three important areas of optimization:

Site speed.

Mobile responsiveness.

Site architecture.

When prompted to provide more information on site speed, we receive a lot of great information that you can use to begin optimizing your site.

If you’ve ever tried to optimize your site’s speed before, you know just how important all of these factors are for improving your site speed.

ChatGPT mentions browser caching, but what about server-side caching?

When site speed is impacted by slow responses for database queries, server-side caching can store these queries and make the site much faster – beyond a browser cache.

Bard’s Response

Bard’s responses are faster than ChatGPT, and I do like that you can view other “drafts” from Bard if you like. I went with the first draft, which you can see below.

The information is solid, and I do appreciate that Google uses more formatting and bolds parts of the responses to make them easier to read.

Structured data was a nice addition to the list, and Bard even mentions chúng tôi in its response.

To try and keep things similar, I asked Bard, “Can you elaborate on site speed?”

You can certainly find similarities between ChatGPT’s and Bard’s responses about optimization, but some information is a bit off. For example:

“A caching plugin stores static files on the user’s computer, which can improve load time.”

Caching plugins, often installed on your content management system (CMS), will store files on your server, a content delivery network (CDN), in memory, and so on.

However, the response from Bard indicates that the plugin will store static files on the user’s computer, which isn’t entirely wrong, but it’s odd.

Browsers will cache files automatically on their own, and you can certainly manipulate the cache with a Cache-Control or Expires header.

However, caching plugins can do so much more to improve site speed. I think Bard misses the mark a bit, as well as ChatGPT.

Bing’s Response

Bing is so hard to like because, for years, it has missed the mark in search. Is Chat any better? As an SEO and content creator, I love the fact that Bing provides sources in its responses.

I think for content creators that have relied on traffic from search for so long, citing sources is important. Also, when I want to verify a claim, these citations provide clarity that ChatGPT and Google Bard cannot.

The answers are similar to Bard and GPT, but let’s see what it produces when we ask for it to elaborate a little more:

Bing elaborated less than ChatGPT and Bard, providing just three points in its response. But can you spot the overlap between this response and the one from ChatGPT?

Bing: You should compress your images and use the correct file format (JPEG for photographs, PNG for graphics).

ChatGPT: You can compress them, reduce their file sizes, and use the correct file format (e.g., JPEG for photos, PNG for graphics).

The responses are going to be very similar for this type of answer, but neither mentioned using a format like WebP. They both seem to be lacking in this regard. Perhaps there’s just more data for optimizing JPEG and PNG files, but will this change?

Let’s move on to website caching. Bing’s response is a little more in-depth, explaining what caching can help you achieve, such as a lower time to first byte (TTFB).

Winner: Bing. I thought ChatGPT would win this query, but it turns out Bing provides a little more information on caching and wins out in the “technical” arena. Bard and ChatGPT did provide more solutions for improving your site speed.

Who Is Ludwig Makhyan?

All chatbots knew a little something about technical SEO, but how about me? Let’s see what happens when I ask them about myself:

ChatGPT’s Response

ChatGPT couldn’t find any information about me, which is understandable. I’m not Elon Musk or a famous person, but I did publish a few articles on this very blog you’re reading now before the data cutoff date of ChatGPT.

I have a feeling that Bing and Bard will do a little better for this query.

Bard’s Response

Hmm. The first sentence seems a bit familiar. It came directly from my Search Engine Journal bio, word-for-word. The last sentence in the first paragraph also comes word-for-word from another publication that I write for: “He is the co-founder at MAZELESS, an enterprise SEO agency.”

I’m also not the author of either of these books, although I’ve talked about these topics in great detail before.

Unfortunately, pulling full sentences from sources and providing false information means Bard failed this test. You could argue that there are a few ways to rephrase those sentences, but the response could certainly be better.

Bing’s Response

Bing also took my profile information directly, and most of the other information is the same, too. Bing does provide a much shorter response and links to the sources.

Advanced Prompt: I Want To Become An Authority In SEO. What Steps Should I Take To Reach This Goal? ChatGPT’s Response Bard’s Response Bing’s Response

ChatGPT provides me with more “light bulb” moments, explaining that I should learn things like keyword research, on-page optimization, and link building.

Knowledge seemed to be the core of the recommendations from ChatGPT, but it would have been nice if it mentioned anything about getting published.

Overall, these tips are very similar, but ChatGPT was my favorite. Let’s try putting these chatbots to work on some tasks that I’m sure they can perform.

Advanced Prompt: Create A chúng tôi File Where I Block Google Search Bot, Hide My “Private” Folder, And Block The Following IP Address “” ChatGPT’s Response

ChatGPT listened to my directions, reiterated them to me, showed me a makefile for the chúng tôi and then explained the parameters to use. I’m impressed.

Bard’s Response

Google! Are you assuming that you’re the only search bot in the world because you’re blocking everyone? Unfortunately, Bard uses the “*” as an agent, meaning every search engine is blocked from going to my site – not just Google.

Bing’s Response

Bing tries hard, and I appreciate the explanation that it provides. However, it’s a bit strange. We’re disallowing all bots using “/” and then allowing using “/$,” which allows them to crawl the homepage and nothing else and then denying a certain IP address.

ChatGPT wins this test because it provides a clean and easy way to make your chúng tôi file. The other two examples need some fine-tuning and will have undesired consequences if you simply copy and paste them into your chúng tôi file.

Advanced Prompt: What Are The Top 3 Destinations In Italy To Visit, And What Should I Know Before Visiting Them? ChatGPT’s Response

ChatGPT does a nice job with its recommended places and provides useful tips for each that are on the same point. I also like how “St. Mark’s Square” was used, showing the bot being able to discern that “Piazza San Marco” is called “St. Mark’s Square” in English.

As a follow-up question, I asked what sunglasses to wear in Italy during my trip, and the response was:

This was a long shot, as the AI doesn’t know my facial shape, likes and dislikes, or interests in fashion. But it did recommend some of the popular eyewear, like the world-famous Ray-Ban Aviators.

Bard’s Response

Bard did really well here, and I actually like the recommendations that it provides.

Reading this, I know that Rome is crowded and expensive, and if I want to learn about Italian art, I can go to the Uffizi Gallery when I’m in Florence.

Just out of curiosity, I looked at the second draft from Bard, and it was even better than the first.

This is the “things to know” section, which is certainly more insightful than the first response. I learned that the cities are walkable, public transport is available, and pickpocketing is a problem (I was waiting for this to be mentioned).

The third draft was much like the first, but I’m learning something about Bard throughout all of this.

Bard seems to have answers with great insights, but it’s not always the first draft or response that the bot gives. If Google corrects this issue, it might provide even better answers than Bing and ChatGPT.

When I asked about sunglasses to wear, it came up with similar answers as ChatGPT, but even more specific models. Again Bard doesn’t know much about me personally:

Bing’s Response

Bing did very well with its response, but it’s curious that it says, “According to 1,” because it would be much nicer to put the site or publication’s name in the place of the number one. The responses are all accurate, albeit very short.

Bard wins this query because it provides more in-depth, meaningful answers. The bot even recommended some very good places to visit in each area, which Bing failed to do. ChatGPT did do well here, too, but the win goes to Bard.

And for the sunglasses query, you be the judge. Some of the recommendations in the list may be out of range for many travelers:

But I did notice the same Aviator sunglasses in the summary.

Which Chatbot Is Better At This Stage?

Each tool has its own strengths and weaknesses.

It’s clear that Bard lacks in its initial response, although it’s quick and provides decent answers. Bard has a nice UI, and I believe it has the answers. But I also think it has some “brain fog,” or should we call it “bit fog?”

Bing’s sources are a nice touch and something I hope all of these chatbots eventually incorporate.

Gain priority in what information is displayed?

Cause misinformation? For example, would the top pizza place be paid ad from a place with horrible reviews instead of the top-rated pizzeria?

ChatGPT, Bard, and Bing are all interesting tools, but what does the future hold for publishers and users? That’s something I cannot answer. No one can yet.

And There’s Also The Major Question: Is AI “Out Of Control?”

Elon Musk, Steve Wozniak, and over a thousand other leaders in tech, AI, ethics, and more are calling for a six-month pause on AI beyond GPT-4.

The pause is not to hinder progress but to allow time to understand the “profound risks to society and humanity.”

These leaders are asking for time to develop and implement measures to ensure that AI tools are safe and are asking governments to create a moratorium to address the issues.

What are your thoughts on these AI tools? Should we pause anything beyond GPT-4 until new measures are in place?

More Resources:

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Bard Vs Chatgpt: Pros & Cons, Differences & More!

Google has taken an important next step on the AI journey by introducing “Bard” as a competitor to ChatGPT. So, the Bard vs ChatGPT debate is genuine, hence, we mentioned a couple of things you should know about both tech titans.

Bard AI vs ChatGPT: Synopsis

Bard AI is a new innovation in the stream of Artificial Intelligence by tech titan Google.

On the other hand, ChatGPT is already exploiting the AI paradigm which is developed by OpenAI.

Here’s a short summary of the bard vs chatgpt debate.

Basis Bard AI ChatGPT

Innovators Google OpenAI

Release Date 7 February 2023 30 November 2023

Language model Build on Google’s LaMDA Build on OpenAI’s GPT-3

Accessibility Limited accessibility Free to the public

Uses Explain complex concepts, provide ideas, assist in basic search functions, etc. Explanation and language translation along with what was not imagined.

What Is Google Bard AI?

Bard AI is Google’s newly beta-released AI language model that is designed to generate high-quality, human-like text based on a given prompt.

Yes, that’s pretty parallel to ChatGPT.

Bard AI uses next-generation and improved Google’s Language Model for Dialogue Applications (LaMDA) to draw responses.

In straightforward, Bard AI is an experimental conversational AI service, powered by LaMDA.

Features of Bard:

Since the algorithm incorporates state-of-the-art language model, it has several notable features, including:

Human-like-text generation

Fast interference speed

Integration with google cloud

Pre-training on diverse data

Customization and fine-tuning

Pros and Cons of Bard AI:

Pros Cons

Fast response Lags in accuracy

Trained on diverse data Limited size compared to ChatGPT

Customization and fine-tuning May require additional resources for fine-tuning

Uses less computing power

Bard is currently in beta testing which means modifications and enhancements are in the works. In the meantime, let’s read about ChatGPT.

What Is OpenAI ChatGPT?

ChatGPT is Microsoft’s new generational AI tool developed by the OpenAI community which uses machine learning to answer queries specifically – that’s in human-like-speech conversational dialogue.

It uses the GPT-3 language model of which its data is trained on more than 2 billion parameters to retrieve information and formulate responses to users’ queries.

Features of ChatGPT:

Natural language processing

Question answering

Language translation

Conversation and summarization

Sentimental analysis

Pros and Cons of ChatGPT:

Pros Cons

Speedy response Bias in training data

Access to vast knowledge No emotions


Lack of context

Super easy to use

ChatGPT is strikingly impressive but it lacks access to the full context of a conversation or situation. However, the service is new and it has been just three months since its launch, so it is learning and evolving from time to time.

Bard vs ChatGPT: What We Have Learned So Far?

Bard was launched in February 2023 whereas ChatGPT was released in November 2023. Reportedly, ChatGPT’s knowledge is limited as it has access to data till 2023, while Bard will have access to the latest information.

Here’s more things we know between bard vs chatgpt.

Common things between Bard AI and ChatGPT


Both OpenAI’s and Google’s language models share several common features, including:

Natural language generation: Both models are designed to generate high-quality, human-like text based on a given prompt.

Pre-training: Both models are pre-trained on large datasets to learn the patterns and relationships between words, phrases, and sentences.

Transfer learning: Both models can be fine-tuned for specific tasks and domains, allowing for more specialized and personalized responses.

These are some of the common features between OpenAI’s and Google’s language models.

Both bard vs chatgpt have the potential to revolutionize the way that businesses and organizations use and interact with AI, and both are examples of the exciting developments taking place in the field of AI.

Core differences between Bard and ChatGPT


Some of the key differences between OpenAI’s language models and Google’s language models:

Size: OpenAI’s language models, such as GPT-3, are among the largest AI models developed to date, with billions of parameters. Google’s language models, such as Bard, are smaller in comparison, but are still capable of generating high-quality text.

Training Data: OpenAI’s models are trained on a diverse range of texts from the internet, including websites, articles, and social media posts. Google’s models are trained on a similar, but slightly different, range of texts, which can result in differences in the type and quality of responses generated by each model.

Performance: OpenAI’s models have been shown to perform well on tasks that require a high degree of understanding and context, such as question-answering and summarization. Google’s models, while still capable of generating high-quality text, may have a slightly faster inference speed and lower latency, making them more suitable for real-time applications.

Accessibility: OpenAI’s models are available through the OpenAI API, which provides access to the models for a fee. Google’s models, on the other hand, are integrated into Google’s cloud platform, which provides easier access and a more integrated experience for users.

These are some of the key differences between bard vs chatgpt.

It’s worth noting that both models are constantly evolving, and new models and updates are being developed all the time.

Future scope of AI-generated content, Bard vs ChatGPT

ChatGPT, which has crossed 1 million users in the first five days since launched, engrossed several users across the globe.

This insight potentially adorns that people are using ChatGPT for everything related to findings and solutions, even beyond.

And, with the latest launch of Bard, Google indulges into the war with ChatGPT, making the field of AI most catastrophic and hypothetical.

Presently, AI-generated content is being used in various contexts. Some of which are briefed underneath.

Product description

Blog post

Email drafts

Writing codes

Simple explanation of complex topic

Summaries of transcripts, meetings, and podcasts

Jokes, memes, and social media posts

The future of AI-generated content is very promising, with many potential applications across a range of industries and fields.

When Will Google’s Bard AI Available?

If you ask, is Google bard available? We would say that it is not publicly available yet.

Google unveiled “Bard” on 7 February 2023 to compete with OpenAI’s renowned language model ChatGPT v3.

The access is currently given to the developers and testers and will soon be available for public release from the competition’s perspective.

How To Use Google Bard AI?

Simply, Google Bard will be easy to use like ChatGPT.

If you’re a beta tester, you would be able to use the Google AI chatbot from the Google app on your smartphone. Tap on the chatbot icon, enter your prompt, and hit enter.

You can begin a conversation by asking a complex question or fun fact about anything or making requests.

ChatGPT vs Google Bard: Which Is The Best AI Chatbot?

Considering the present scenarios where people are using ChatGPT every minute. It would not be wrong to say that ChatGPT is the best AI chatbot to date.

Talking about Google Bard, it is not released yet. Besides, Google’s AI chatbot Bard makes a factual error in the first demo that triggered the company (Alphabet) losing over $1 billion.

— The Next Tech (@TheNextTech2024) February 9, 2023

But, this does not mean that Bard is lacking or unworthy in the field of AI conversational chatbots.

The final verdict is that ChatGPT is popular to date, engrossing millions of users in a day.

Let’s see where the Bard will be in the limelight.

Frequently Asked Questions Is bard a competitor to chatgpt?

Reportedly, in an event live-streamed from Paris on Wednesday, Google unveiled Bard as an alternative to ChatGPT that does more than answer users’ queries.

Is bard better than chatgpt?

Reportedly, ChatGPT’s knowledge is limited as it has access to data till 2023, while Bard will have access to the latest information.

What is the bard AI launch date?

The first glimpse of Bard has been marked by people in an event live-streamed from Paris on 7 February 2023.

Can I use Google bard AI right now?

As of now, Google bard is not publicly available. Only a few chosen testers and developers can access Google Bard.

Github Copilot Vs Chatgpt: Basic Differences To Know

What to know

GitHub Copilot is a paid tool recommended for professional developers due to its ability to learn from habits and suggest lines of code accordingly.

ChatGPT is free and a generalized solution that can help generate code with explanations, making it recommended for beginners and users learning to code.

ChatGPT can help generate code and follow up on it in a particular conversation, but once the conversation is lost, it cannot continue without a special prompt.

GitHub Copilot uses Machine Learning to constantly learn from code and behavior, improving suggestions over time.

In 2023, the prevailing trend has been the utilization of AI tools, such as ChatGPT, Dall-E, Notion AI, and others, which offer a range of capabilities for generating images, text, content, and more, depending on your specific requirements. ChatGPT is an impressive AI chatbot that can undertake a variety of tasks, including producing executable code, prompting developers to compare its effectiveness against the widely-used GitHub Copilot.

As a developer in search of the right AI assistant, this article will provide you with all the information you need to make an informed decision about these two AI assistants.

What is GitHub Copilot

Copilot is an AI-powered assistant developed by GitHub that uses machine learning to auto-complete your code in the current project. GitHub Copilot has been developed using OpenAI and supports Visual Studio Code, Visual Studio, Neovim, and IDEs. This allows you to start a project and then use GitHub Copilot to generate further code depending on your needs and requirements.

Copilot uses Machine Learning to intelligently analyze your code and generate further suggestions to complete it. Copilot can help streamline repetitive code, which can help you focus on the project at hand. Copilot supports the following programming languages, which makes it a versatile tool for most users.















This is not a comprehensive list, as GitHub is constantly improving Copilot and adding more and more languages to the AI assistant. This list can change in the future and include more languages.

What is ChatGPT

ChatGPT is an AI-powered chatbot from the house of OpenAI. It uses OpenAI’s popular large language models (LLMs), GPT-3.5, and GPT-4, to generate text and content based on provided prompts. The chatbot can perform various tasks, including generating content, code, scripts, articles, research papers, and more.

You can also prompt the chatbot to assume different roles and then respond to your messages accordingly. This makes ChatGPT a versatile tool not only for developers but other professionals as well that are looking to automate mundane and repetitive tasks. Here are the programming languages supported by ChatGPT.














ChatGPT vs Copilot

When comparing both tools, GitHub Copilot is the recommended AI assistant for professional developers. This is because Copilot can learn from your habits over time and then suggest lines of code accordingly. Copilot provides improved suggestions over time as it learns from your habits, making it invaluable once you have been using it for a while. 

ChatGPT, on the other hand, is a generalized solution that can also help generate code with explanations. It is recommended for beginners and users learning to code, as the chatbot can help explain the suggested code as well as make corrections based on your feedback. 

Another factor that separates these two AI assistants is the cost. GitHub Copilot requires a paid subscription while offering a 60-day trial period. ChatGPT, on the other hand, is completely free to use, making it a great choice for users just starting out. On the other hand, Copilot is thus recommended for professionals looking to invest in an AI assistant that helps automate their daily tasks so that they can focus on the current projects and meet deadlines easily. 

Lastly, ChatGPT can help you generate code and follow up on it in a particular conversation. Once the conversation is lost or deleted, you won’t be able to continue on the project unless you create a special prompt in the previous conversation so that ChatGPT can remember and follow up on the project.

On the other hand, GitHub Copilot uses Machine Learning to constantly learn from your code and behavior so that it improves over time. As time passes, Copilot will improve its suggestions and get exceptionally good at its responses and suggestions.

Google Assistant Smart Displays Vs. Amazon Echo Show: What Are The Differences And Similarities

This year’s Consumer Electronics Show was dominantly a battle between Amazon and Google for the most part, with the latter unveiling a bevy of new smart display devices in a move to take on the former’s smart speaker with a built-in screen announced in May last year. But the Mountain View, the California-based internet giant isn’t just settling with one smart display, but four, thanks to its partnership with Lenovo, Harman-owned JBL, LG, and Sony.

The alliance between those tech giants has given Google Assistant a new face literally, bringing the virtual assistant from your phone and from smart speakers to the bigger screen. The Lenovo Smart Display from the Chinese OEM, for example, is powered by Google’s voice-enabled personal assistant. The same is true with JBL’s Link View (8-inch and 10-inch variants), the LG ThinQ, and Sony’s as yet unnamed smart display.

Echo Show vs. Lenovo Smart Display vs. JBL Link View vs LG ThinQ

But how exactly do these Google Assistant-powered smart displays differ from the Echo Show? While details about the smart display offerings from Lenovo, JBL, and LG have been made already, no word yet about Sony’s bet. In this post, therefore, we’re limiting our comparison to the Echo Show, Lenovo Smart Display, JBL Link View, and LG ThinQ.


In terms of design, the four smart displays we’ve seen so far vary slightly in a number of ways. Let’s discuss the dimensions first. The Echo Show measures 187 x 187 x 90mm while the Lenovo Smart Display has a dimension of 311.37 x 173.87 x 136.02mm for the 10-inch variant. The JBL Link View, on the other hand, measures 330 x 150 x 100mm, making it the biggest in the competition, thanks to its oval shape.

Speaking of shape, the Echo Show has a trapezoid shape on the back that helps the device lean backward. It has a square face as well, which the same to that of the Lenovo Smart Display. The LG ThinQ has a rectangular face, meanwhile.

Additionally, the speaker grilles on the Echo Show sit under the landscape display while those of the Lenovo Smart Display are found at the left corner of the screen. When considering which smart display to choose once they go on sale, keep in mind that the JBL Link View includes an IPX4 rating, so it has the upper hand over the others.


When it comes to screen sizes, the Lenovo Smart Display comes in two variants as mentioned above, so there’s a couple of options for you, with the 10-inch variant sporting a full HD IPS display and a resolution of 1920 x 1080 pixels. The 8-inch version has a slightly lower resolution of 1280 x 720 pixels. On the other hand, the Echo Show sports a 7-inch touchscreen that you can use for a wide variety of voice-assisted tasks. It has a resolution of 1024 x 600 pixels.

The JBL Link View comes with an 8-inch high-definition touchscreen with a built-in camera and the LG ThinQ has the same screen size as JBL’s. However, resolutions of these smart displays are not immediately known at present, so it’s safe to assume that the Lenovo Smart Display is a better option if you wish to watch a video or sift through your photo album using voice command.

New Android Go phones to be available soon


The Lenovo Smart Display is using Qualcomm’s new Home Hub Platform powered by Snapdragon 624 while the Echo Show is fueled by an Intel Atom x5-Z8350 processor. No word yet on what’s fueling the JBL Link View and the LG ThinQ, but Google recently confirmed that the latter is running on Qualcomm’s SD624 Home Hub Platform while Qualcomm previously announced that Harman is using its platform. Nonetheless, there’s really no telling what hardware performances better until all of the Smart Display contenders are subjected to actual testing.

Additionally, the JBL Link View includes a pair of 10W front-firing stereo speakers and is equipped with a rear passive radiator while the Lenovo Smart Display has a pair of 10W speakers with dual passive radiators. The LG ThinQ, on the other hand, has a pair of “Tuned by Meridian Audio” speakers flanking the device while the Echo Show boasts a pair of 2-inch stereo speakers in the front, promising a great sound experience overall. Guessing from the aforementioned specs, we expect the Echo Show to take the lead in this respect.


At its core, the JBL Link View, Lenovo Smart Display, LG ThinQ and Sony use a modified version of Google Assistant, offering a new type of experience for a fresh type of screen with a simpler interface since it’s a whole lot different from the Google Assistant installed on your smartphone. However, the overall experience doesn’t vary much from that of Google Home or your Google Assistant-equipped smartphone, except that you can’t install Android apps to these smart displays since they’re not another Android device. Nonetheless, you can still use them to ask for directions from Google Maps displayed on the screen in addition to switching off your lights.

The Echo Show provides a basically similar experience. You can ask for calendar entries or a list of ingredients for your dinner using your voice and see them on a visual display. This is thanks to Alexa, which offers a full suite of features to let you control all sorts of smart home devices, play games, or listen to music, among others.

Upcoming Android Go phones


The Echo Show has the lead over the other smart displays since it’s already out on the market for $229, though Google Assistant seems to be smarter than Alexa when accepting commands. Nonetheless, if you wish to get your hands on a smart display at an affordable price right now, Amazon’s bet is your only option, though that may change soon.

Data Science Vs Big Data: Key Differences

Data Science vs BigData: The key difference is in areas of focus, data size, tools, technologies used, and applications

Data Science and Big data are two interrelated concepts that have gained significant importance in recent years. Data science vs Big data is a trending topic. In the data analytics field, both play a vital role in leveraging data for decision-making, innovation, and gaining a competitive edge in today’s data-driven world.

The growth trend in the data segment of the industry suggests that data science and Big data analytics are the future. Data Science and Big data are two related but distinct concepts in the data analytics field. Data Science focuses on the application of statistical and machine learning techniques to extract insights from data and solve complex problems. It encompasses data acquisition, cleaning, exploration, and interpretation. Whereas, Big data refers to large, complex datasets that exceed the capacity of traditional data processing methods. Applications are in real-time processing and analysis fields like fraud detection, sentiment analysis, internet traffic analysis, etc.

Let’s delve into the key differences between Data Science and Big Data: Key Concept and Characteristics

Data Science is a multidisciplinary field combining scientific methods, algorithms, and systems for extracting valuable insights from structured and unstructured data. It emphasizes the use of data as the primary resource for analysis, decision-making, etc. To do so, they employ statistical techniques and ML algorithms. These data analysis techniques aim to solve real-world problems.

Scope and Methodology

Data science includes statistical analysis, ML, data visualization, and exploratory data analysis. These are employed to understand the patterns of data, make predictions and solve problems.

In big data, large datasets are handled using technologies and infrastructure. It involves distributed storage and processing frameworks like Hadoop and Spark. To manage vast volumes and high velocities of data, it enables parallel processing, scalability, etc.


The primary goal of data science is to gain insights, extract valuable knowledge, and solve complex problems using data.

The main objective of big data is to store, process and analyze massive volumes of data efficiently.


Data Science is extensively used in business intelligence to analyze customer behavior, market trends, and sales data. In healthcare, it plays a crucial role in analyzing patient data for diagnosing diseases and treatment outcome prediction. It also aids in clinical decision support, personalized medicine, and identifying patterns for disease outbreaks. Data science is utilized in financial institutions for fraud detection, risk modeling, algorithm trading, and making informed investment decisions. They are applied to analyze the human language that enables applications like chatbots, voice assistants, and machine translation.

Big data analyze customer preference, behavior, and purchasing patterns to improve product recommendation, inventory management, pricing strategies, and personalized marketing campaigns. It handles massive amounts of data generated by IoT devices such as wearables and sensors. These technologies are employed to analyze social media data including user interactions, sentiment analysis, and trending topics.


Data science helps organizations to make informed decisions by extracting meaningful insights from data. This is done through statistical analysis, ML techniques, and data visualization techniques. The wide range of applications including in finance, healthcare, business, etc. Efficient data management and analysis in data science offer significant cost savings.

Data science requires skilled professionals in the field. Due to the need for preprocessing and data cleaning, this technique is time-consuming and needs more resources. Since it deals with sensitive data, ethical concerns may be a problem.

Big data need skill and expertise in the field. Security and privacy are a concern when handling sensitive data. It can sometimes be expensive due to the need for specialized infrastructure and software.


Data science uses tools like Apche Hadoop, DataRovit, Tableau, QlikView, Microsoft HD Insights, TensorFlow, Jupyter Notebooks to effectively handle and analyze huge data.

Google Vs Bing: Is One Search Engine Really Much Better Than The Other?

Rita El Khoury / Android Authority

When it comes to searching the internet, your mind probably jumps to Google. But what about Microsoft’s search engine — Bing? It isn’t as popular or commonplace, but it’s certainly a viable alternative to Google and offers a handful of exclusive features to sweeten the pot. The latter includes a new ChatGPT-like chatbot that can assist you with complex search queries. But what else separates Google vs Bing and which search engine comes out on top? Here’s everything you need to know.

Google vs Bing usage: Which search engine has the most market share?


Bing captured a third of US searches at one point.

Neither Google nor Microsoft discloses the exact number of searches or active users they serve each day, but third-parties paint a clear picture of who is in the lead. Broadly speaking, nine in every ten searches take place on Google.

According to Statista, Google enjoys an 84% market share in the desktop search engine race and the lead extends to 95% in the mobile market. Bing puts up an admirable fight with a nearly 9% market share in the PC space, but it doesn’t even break past the one percent market share mark on mobile. While these numbers may seem bleak, it’s worth keeping in mind that Bing gets over 12 billion searches every single month.

Google vs. Bing: Functionality and quality of results

It’s difficult to gauge the quality of results for the billions of possible search terms out there. Generally speaking, though, Google and Bing will both meet the needs of the average user. Both search engines allow you to search for text, videos, images, news, and even popular shopping websites.

In our use, we found that both search engines delivered reasonably accurate results. Both offer a list of links to relevant web pages as you’d expect from a search engine. In fact, the result pages don’t look that different from each other too. Bing and Google will sometimes pull snippets of text from trusted sources like Wikipedia. Finally, Bing will often also provide a visually rich infographic alongside the search results, as shown in the above screenshot.

Does Bing or Google have the better AI chatbot?

In 2023, Microsoft announced Bing Chat — a conversational chatbot that makes searches seem more personalized and interactive. It’s based on the same technology as ChatGPT, which Microsoft has poured over ten billion dollars into so far.

AI chatbots like Bing Chat shine when you need answers to complex questions. Some examples include planning a holiday or picking out a gift for a close one. Here’s a sampling of Bing Chat in action on mobile:

The difference between ChatGPT and Bing Chat is that Microsoft allows its chatbot to search for live information on the internet. This makes it incredibly powerful in practice — you can use it to find matching pieces of furniture or compare various products from a certain standpoint. With traditional search, you’d need to perform multiple individual searches and do your own research.

Google does have a rival in the form of its Bard AI chatbot, but you cannot use it yet. Even though we saw the company demo this technology a couple of years ago, we’re still waiting for it to make its way to the broader public. Even when Google’s chatbot does arrive, it’s unclear how it will compete vs Bing Chat or ChatGPT. The latter’s underlying GPT-3 model benefitted from years of fine-tuning, both publicly and behind the scenes.

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