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Around 60-75% of users surveyed reported satisfaction with using Copilot, feeling less frustrated while using Copilot


Copilot isn’t yet a be all end all solution for smart programming

Generative AI models including Copilot have been at the center of debate over their efficiency and, ie., if they will put content generators and coders at peril. Cutting through the din of the noise, GitHub has attempted to quantify Copilot’s influence in improving a programmer’s productivity and happiness. Copilot , a pair programmer has predictive code functionalities to assist programmers with appropriate code suggestions similar to IntelliSense/IntelliCode of Microsoft, though it digs deeper beyond those offerings, thanks to Codex to let turn typed commands into actual code. “Because AI-assisted development is a relatively new field, as researchers we have little prior research to draw upon,” said GitHub’s Eirini Kalliamvakou in a blog post. After early observations and interviews with users, they surveyed more than 2,000 developers to assess their experience with programming using Copilot in three dimensions: holistic measurement of productivity, the perspective of the developer, and assessing the co-pilot’s effect in everyday programming scenarios. They feel it is more important to take a holistic view and a developer’s perspective into account, because as per a 2023 study, developer productivity may take different meanings, from staying focused on the task at hand, and making meaningful progress to feeling good at end of the day. The survey results came out exactly to the above statement. GitHub concluded from its review that it gives developers a starting point and saves time looking for coding bits over the internet. As it allows for designating smaller, repetitive and insignificant parts of code to Copilot, developers can focus on the important part of programming. From the survey, it was found that Copilot’s benefits go beyond improving speed in coding. For example, it was found that Copilot has been immensely successful in improving coder satisfaction. Around 60-75% of users surveyed reported satisfaction with using Copilot and feeling less frustrated while using Copilot. While around 73% of the developers said Copilot helped them stay in the flow, 87% of them said they could focus on larger tasks, saving them from the trauma of doing repetitive tasks. In the paper “Evaluating the usability of code generation tools powered by large language models ”, they cited, “We found that, while Copilot did not necessarily improve the task completion time or success rate, most participants preferred to use Copilot in daily programming tasks, since Copilot often provided a useful starting point and saved the effort of searching online. However, participants did face difficulties in understanding, editing, and debugging code snippets generated by Copilot, which significantly hindered their task-solving effectiveness.”This particular study is an addendum to the earlier study by Kalliamvakou but focuses on coding speed with Copilot and otherwise. Around 95 developers were involved in the study of which half of them found coding time reduced to half compared to those who didn’t use Copilot, improving the speed to almost 55%. However, given the limited nature of the study – with only JavaScript programming involved in the experiment – it is hard to say if the results reflect reality. “It was certainly a fun experiment to do. These controlled experiments are quite time-consuming as we try to make them bigger or more comprehensive, but I’d like to explore testing for other languages in the future,” she said in an interview with ZNet.

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Best Ai Tools For Digital Marketing

Artificial Intelligence (AI) is impacting every industry we can think of. It is the same with digital marketing. There are some great tools that can help digital marketers in laying out their digital marketing strategies and make the most out of these AI tools in less time. Digital marketers can benefit a lot from using AI tools by saving time and automating repetitive tasks. In this guide, we show you the Best AI tools for Digital Marketing.

Best AI tools for Digital Marketing

If you are a digital marketer and want to make it more productive, you can use the following AI tools to optimize your profession.





Let’s get into the details of each tool and know how to use them.

1] HelloScribe

HelloScribe is an AI writing and brainstorming assistant that can help PR and marketing professionals work smarter and faster without creative blocks or wasted time. You just need to input what you want and HelloScribe can generate endless original ideas and content related to your specific request. You can pick the best of the generated ideas, edit them, implement them in your strategy and publish them on your social media. HelloScribe has tools for creative brainstorming, Brand messaging, Press releases, Headlines, news hooks, media pitches, social media copy, interview questions, etc. You can get more done faster using HelloScribe. You can try HelloScribe for free for 7 days without any credit card and then buy a paid plan if you like its services.

2] Flair

3] Looka

Looka is a great AI tool to design logos for your brand and your clients. On Looka, you can use AI to design the best possible logos for your brand in a few minutes. You do not require any design skills. All you need is a vision of how you want your logo to look. Looka can generate endless options and tweak designs to get exactly what you want. Looka services do not stop with generating a logo, you can also build your brand identity using the brand kit and branded marketing materials that Looka generates. You can choose from 300+ templates that can match your vision and identity. You can customize the design in the easy-to-use editor. To sum up, Looka is a personal designer that can help you design logos and branded content for your clients.

4] is an AI tool that can help you interact with customers and the user community to make your brand more accessible to people. It is the easiest way to connect with the community and look clever, funny, and professional on social media. You can appear smarter and grow your audience with 10x less effort. It is an easy-to-use AI replies generator with extremely simple functionality. You can use chúng tôi on Twitter and LinkedIn and start from a blank page and go to the best content. It also helps you grow better and easier. chúng tôi can help you interact, generate icebreakers for tweets, create viral jokes, and custom reactions. You can try chúng tôi for free using the free plan.

Read: Best AI tools for Content Writing

5] tiledesk

Read: Best Graphic Design Tools and Software for beginners

These are the different tools a digital marketer can implement on their client projects or own projects and make the most out of them.

How AI is used in digital marketing?

AI has different uses in digital marketing. From generating content to interacting with people on social media, and websites, AI can benefit digital marketing easily. All you need is the right tool that suits your need. Even the strategies can be generated by AI tools like HelloScribe. AI can help you get more clients if you are a digital marketer.

What type of AI is used in marketing?

From chatbots to replying to customers to interacting with the community on social media, AI can be used in many ways in marketing. There are many great tools to write marketing copies that convert. You just need to have an idea of how your marketing should be. The rest will be taken care of by the AI.

Related read: 10 Online jobs that you can do from Home.

Ai Vs. Coronavirus: Impact Of Coronavirus On Us And Technology

The world is becoming a technology crystal ball. The internet is bound to everything, including our homes, schools and workplaces. It also connects us all to the restaurants we love to eat every weekend.

Artificial Intelligence (AI), the Internet of Things, and other technologies allow us to see smart tools and automation technologies almost every day. AI facilitates us at home, and it also helps healthcare workers do their jobs.

Smart devices were installed in ambulances and hospitals, and healthcare workers used these technologies.

Technology Needs to Peak With COVID

The pandemic struck us hard. These technologies were needed most acutely during the coronavirus. Frontline workers must be able to assist patients without compromising their social isolation or health.

By default, AI is the top choice. AI can be used to select better vaccine options, but IoT, specifically the Internet of Medical Things, offers better ways to aid and treat patients.

We are currently studying the impact of COVID-19 and how AI and IoT can facilitate the healthcare industry.

You can also see Artificial Intelligence is Neutral Technology: How Social Media Can Help Healthcare

The impact of Coronavirus on us, technology

Coronavirus was a complete stop in an ever-changing world. It took millions of lives worldwide, but it also opened the door to new healthcare technologies.

COVID established a new standard of social distancing and gadgets were created to assist authorities in monitoring it. Corona Virus brought to light the controversy surrounding anti-maskers.

Every store has a different opinion on the freedom to not wear a mask when customers are anti-masker. AI and computer vision are now able to create devices that can stop anti-masker customers without arguing. AI allowed us to have digital access, even though we were unable to access the rest of the world due to the pandemic.

Broad Reach of COVIDs

This novel virus had a lasting impact on every corner. It also brought about a new technology. These technologies were indirectly used to help the healthcare industry combat the coronavirus. These technologies do not only provide indirect assistance.

We are now open to the possibility that other pandemics could occur in the future. It also set us on a path that allowed us to use technology in healthcare more often than ever before. AI is used by healthcare workers and hospitals to diagnose a disease or administer dosages.

Technology is affecting COVID-19, but it can also be the reverse.

AI helps to fight Coronavirus

AI and IoT have proven to be intelligent solutions to the pandemic since the beginning of COVID-19.

AI aids frontliner in combating coronavirus by introducing new devices and using existing inventions. Many researchers also came up with innovative solutions to combat COVID.

Healthcare uses a variety of AI-powered devices and solutions to monitor, diagnose, and treat patients. They also transport aid, enable social distancing, provide financial services, and can even be used for diagnosis and treatment.

Six examples of AI’s many applications are shown below. They are helping healthcare workers fight COVID-19.

1. Social Distancing Solutions

Despite the huge death toll from the coronavirus, there are still people who don’t follow social distancing guidelines. Although it may not seem like an issue for healthcare workers but the increase in COVID cases is a result of social distancing laws being broken. This is why managing this issue is an important weapon in the fight against COVID-19.

Also read: 5 Best Resource Capacity Planning Tools for Teams

2. Automated Initial Test

Healthcare workers can benefit from IoT by automating initial COVID testing. Researchers have been working hard to find ways to speed up test results since the beginning of the pandemic. There are many automated tests available, including predictive pathology and lung scan testing.

These AI solutions can quickly test for COVID and reduce the chance of healthcare workers contracting the disease. This technology allows healthcare professionals around the world to test COVID faster and with fewer cases, without putting lives at risk.

3. Fast Diagnosis and Safer Treatment

Also read: Top 5 Automation Tools to Streamline Workflows for Busy IT Teams

4. Automation in the Medicine Supply Chain

The healthcare industry also faces the challenge of managing its supplies manually. COVID-19 caused a shortage of medical equipment due to an increase in its use. There was no global monitoring of the supply of medical equipment.

Black-market looters were also a problem. IoT/AI once more proved to be the best solution as automation became a necessity in supply and supply chain management. Predictive analytics and optimization of healthcare supply chain costs gave control over existing equipment and enabled the healthcare industry to automate the ordering process.

5. AI to Vaccine Solutions

AI goes beyond automation. It can be used in nearly every field of prediction. AI offers pioneering solutions for predictive analysis, including the ability to predict weather and human behavior. It can be used in the same way that AI is used to predict people’s behavior via social media.

AI-based predictive analytics can be used to create and perfect vaccines not only for COVID-19, but also for any future pandemic. This requires years of research but can lead to a path for treatment of a large number of diseases.

6. Predicting and Governing Virus Status

Also read: The 15 Best E-Commerce Marketing Tools


COVID-19 had a major impact on our lives but also gave us the ability to be proactive and ready for similar problems in the future. We have made our tools and technologies compatible with these issues and are now able to adapt to them. Just as COVID has an impact on technologies, IoT and AI are helping to fight this pandemic.

COVID-19 has imposed many challenges on the healthcare industry. But it is not just the healthcare industry that must face them. Everything was affected by the pandemic, from education to businesses. Similar to AI and IoT helping healthcare, AI and IoT also help other fields.

AI-based solutions form the foundation and part of almost every future technology. Algoscale assists industries in incorporating these AI solutions into their business models. Algoscale provides AI solutions for startups and enterprises, from prediction to automation.

We hope you found this article useful. Algoscale strives to provide you with knowledge on a wide range of subjects. Keep reading to learn more and keep up-to-date. Happy Learning!

Top 10 Ai Tools For Academic Research

Following is a list of the top 10 AI tools for academic research helpful for researchers

Scholars and Students have devoted countless hours to academic research and writing throughout history. Even though researchers now have access to more information and AI tools than ever before thanks to technology and the internet, it can be challenging to find the right AI tools for research.

Scholars and researchers require assistance sorting through and organizing sources due to the abundance of information available today. In addition, scholars and researchers must write informative, engaging, and well-written articles and reports due to the ongoing pressure to publish. Here is the list of AI tools for academic research.

1. Consensus: 2. ChatPDF:

Users can converse with a PDF document through the AI application ChatPDF. Without signing in, users can interact with any PDF they own, such as books, research papers, manuals, articles, and legal documents. To comprehend the content of PDF files and provide pertinent responses, ChatPDF makes use of a next-generation AI model comparable to ChatGPT.

3. Scite:

Scite’s Assistant, an AI-powered research tool, lets users work together on essays and research papers, find evidence to back up their claims and find evidence to refute them. Clients might enter straightforward questions to get reactions in light of the total texts of exploration distributions. The application can be used by users to find reliable information, search through millions of research articles, and create grant proposals or essay drafts.

4. Elicit:

Elicit, a machine learning tool, is used by the AI research assistant to help automate research procedures. Without specific keyword matches, it can locate relevant articles and extract important information. Inspire may likewise give different exploration exercises, including conceptualizing, summing up, and text-order, as well as summing up central issues from the report that are pertinent to the client’s request.

5. Trinka:

Online sentence structure checker and language proofreader Trinka artificial intelligence was made for specialized and scholastic composition. It is made to catch errors that other grammar checkers miss, like issues with subject-verb agreement, syntax, word choices, the use of pronouns and articles, and technical spelling. In addition, it incorporates a professional tone, the use of technical words, conciseness that goes beyond grammar and spelling, and style guides.

6. Scholarcy:

The online summarizing tool Scholarcy is a simple way to quickly examine and evaluate the significance of documents like articles, reports, and book chapters. Any Word or PDF document can be used to create summary flashcards that are displayed in an organized and easy-to-understand manner.

7. Academic Semantics:

The vast majority know about Google Researcher, which uses Google’s web search tool ability to list academic distributions. But if you’re doing any kind of scientific research, you should try Semantic Scholar. This AI-powered search and discovery tool, made available by publisher partnerships, data suppliers, and web crawls, enables you to keep up with more than 200 million academic publications.


Utilizing the internet to find information is a blessing. The amount of data that is accessible and the fact that it can be found in a variety of formats, such as blogs, essays, films, infographics, and images, present two challenges. Finding and organizing all of the data related to your study’s many areas might take a lot of effort.

9. SciSpace:

SciSpace is a platform driven by AI that lets people read, understand, and submit scientific articles. Its extensive searchable database contains more than 270 million articles, authors, subjects, journals, and conferences. It also offers a variety of paper template choices, a variety of pricing options, and additional services to speed up the printing process.

10. OpenRead:

Ten Tools To Help You Spend Less Time On Email

Emailing isn’t something you can easily get away from if you want to take part in 21st century life. But you definitely don’t want to spend too much time managing your inbox—there are far better and exciting ways to pass your time.

If you dig a little deeper into that email app of yours, you’ll discover quite a few features for streamlining your workflow, so you can spend less time sending and receiving messages and more time living your life.

Some of these features may not be available in every email app out there, but most of them are—though with different names and paths. We’ve included one example for each to make sure you find something new.

1. Email templates

If there’s a particular email you send a lot (like “Thank you for the job application” or “Sorry I was so late for our meeting this morning”), just set up a template for it. That way, you can load it up and tweak it where necessary (names, specific events, etc.) rather than starting from scratch every time.

2. Automatic responses

Using an automatic response is like having a virtual assistant. You just have to be creative and give it the right instructions. David Nield

Most email apps come with some kind of “out of office” auto response you can set up for when you’re away on vacation. But there are some other cool uses for this feature, too. Maybe you’re switching to a new email address, retiring, or spending the day out of the office somewhere with a spotty reception. This tool can be deployed anytime you need to put your inbox on pause, or to send the same message automatically to a lot of people at once.

Apple Mail on macOS handles this well: go to Mail, Preferences, Rules, and then Add Rule to get started. First, you’ll have to set the criteria that triggers the auto response. It can be anything—from simply getting any message, to getting only messages from a particular recipient or that include certain words in the title. To finish, pick Reply to Message as the resulting action, and compose your text.

3. Combined inboxes

Most email apps are able to manage more than one email address at once, which means you won’t have to jump between apps (or even computers) to check your messages. The best part is that adding new email accounts is usually pretty straightforward.

4. Email aliases

Many email providers now let you set up email aliases—alternative email addresses that are still managed through your main account. You could set one up solely for email newsletters to protect your privacy, or one that only your family knows about.

This comes in handy because it means you can filter messages more efficiently—emails sent to your “newsletter” address can be automatically moved to a dedicated folder so they don’t clog your main inbox, for example, while those sent to your “family” address can be automatically starred and given a higher priority (or not).

5. Archive emails

You don’t need all your subscription platforms’ newsletters to invade your inbox, but if you still want to keep them, archiving is the way to go. David Nield

Filtering messages as they come in is one of the most effective ways to reduce the time you spend looking at your emails. One of the best filters to set up is one that automatically archives less-important messages or marks them as read—what qualifies as “less important” is up to you.

6. Smarter replies

Smart replies use machine learning to suggest quick responses to incoming messages based on the text in them, and can even evolve to more naturally match your writing style. They’re one of the quickest ways to power through your inbox, but you’ll only find them in Gmail for now.

7. Smarter emails

If you want to go one step further, you can use Smart Compose to get Gmail’s help with writing your entire email. As with Smart Reply, it uses artificial intelligence, and suggests what you might want to say next in a sentence based on training models of human language.

You’ll find the toggle switch for enabling or disabling Smart Compose in Gmail settings, whether you’re on the web, Android, or iOS. If it’s enabled, you’ll see suggestions in gray as you type. Press Tab (on the web) or swipe across (on mobile) to accept a suggestion.

8. Email previews 9. Swipe gestures

If you’re using an email app on your phone, try swiping across messages from the left or the right—most apps let you do this to quickly deal with large numbers of messages. You can also usually customize what the swipes do, with options usually being to archive, delete, or mark as read.

You can do this on Gmail’s mobile platform by tapping the menu button (three lines, top left), and going to Settings and General settings. Then, go to Swipe actions to determine what you want to do each time you swipe. The options range from snoozing emails to deleting them.

10. Email signatures

Whether you’re already accustomed to using email signatures or not, they can help you spend less time emailing. You can use them to automatically tell your contacts about the hours you’ll be available, or warn them you’re on a mobile device and can’t compose a lengthy message.

In other words, signatures can give those people you correspond with any kind of useful information that you would otherwise have to type out each time. Most email apps support signatures—to set one on Apple Mail on iOS, for example, choose Mail, then Signature from the iOS Settings screen.

What Are The Pros And Cons Of Using Python Vs. Java?

In this article, we will learn the pros and cons of using Python vs. Java.

Pros of Java

Simple − Java is a must-know programming language due of its simplicity. Because it is C++-based and uses automated garbage collection, we don’t have to worry about freeing up memory for things that are no longer being used. To further simplify Java for both reading and writing, features such as explicit pointers and operator overloading have been removed.

Object-Oriented − As an Object-Oriented Programming Language, Java has many useful features such as Data Encapsulation, Inheritance, Data Hiding, and so on. As a result, Java is a good language for mapping real-world entities into objects and solving real-world issues.

Platform Independent − The compilation of code in Java is not platform-specific, but rather occurs as platform-independent bytecode. After that, the Java Virtual Machine (JVM) interprets it. There is no OS needed for running the software. This guarantees that your code will operate on Mac, Windows, Linux, and any other platform that supports the Java Virtual Machine. As a consequence, we can reach more people. It follows the Write once, run anywhere principle.

Secure − It assists developers in creating safe and tamper-proof code by utilizing public-key encryption.

Robust − Strong memory management is one of the reasons Java is such a stable programming language. Java code may also be used to deal with errors. To further strengthen our code’s safety, we may additionally use type-checking. Since it does not make use of explicit pointers, programs cannot do direct memory access.

Distributed Computing − Java’s support for distributed computing stems from the language’s inclusion of many APIs for establishing connections to external resources, such as CORBA and RMI.

Cons of Using Java Memory management

Java’s built-in support for managing memory helps to speed up the development process. The efficiency and precision of garbage collection may likely drop to the point where it is equal to human work. Because of this, Java applications rely heavily on in-memory processing and manipulation.

Code readability

Java applications are subject to being lengthy because of the complexity of their extensive code courses. If the developer has not given sufficient documentation and notes, understanding and analysing the system may take some time.


When compared to other languages, Java necessitates a large amount of memory space.

As there are high memory and processing requirements, so does the cost of hardware increase.


Every time Java code is executed, it is interpreted by the Java Virtual Machine (JVM). Consequently, productivity falls. Data processing in real-time is currently not possible with Java.

Garbage collection

When it comes to garbage collection, Java enables automated garbage collection over which the programmer has no say. Memory-freeing methods like delete() and free() are not included. Java’s merits, which include being platform-independent, secure, and robust, have helped to keep it one of the most popular programming languages despite these drawbacks.

Pros of Python

Easy and short Syntax − The syntax is simple and thus easily picked up by programmers.

Expressive Language − Small snippets of code can be used to finish large lines of code.

Cross-Platform Language − Works across all operating systems.

Smooth Learning Curve − Python is a very accessible programming language that is typically introduced to students as a first programming language course. This tool lets you put a limit on the way a developer thinks by forcing them to concentrate on the most basic principles and building blocks of their skill.

Free and Open Source − Python is a free and open-source programming language that may be accessed from anywhere worldwide.

Vast Standard Library − The offerings of these libraries, such as MatPlotLib, Pandas, Request, NumPy, and others, are vast and make the task of a developer quite simple.

Flexible with other languages and tools − Python is a versatile programming language that can be readily integrated with a wide range of tools and frameworks to handle a wide range of problems.

Versatility combined with a vast toolkit for practically anything − Python can be used for a wide range of jobs, including data automation, data scientists, data engineers, QA engineers, and DevOps specialists.

High Speed of Development − When it comes to studying and creating Python-based software, the straightforward syntax greatly reduces complexity and increases productivity. Using pre-coded components saves time and effort by providing reusable building blocks for new software projects.

Cons of Using Python

Less Speed − It is slower because it is an interpreted language. Despite Python’s incredible development speed, Java and C++ still dominate it in terms of execution speed. Program execution is slowed down by the interpreter used to inspect and assign variables.

No Multithreading − The Global Interpreter Lock, or GIL, mechanism lies at the core of Python. It only allows the execution of one set of bytecode instructions at once. While limiting the performance of multi-threaded systems created to run numerous workflows simultaneously, GIL enhances the performance of single-threaded programs.

High Memory Consumption − The Python garbage collector delays returning system resources once an item is no longer in use. This causes Python’s memory problems to occur often.

Challenges with front-end and mobile development − Not a single smartphone platform supports the Python programming language. Java is used only for Android app development, whereas Swift and Objective C are used exclusively for iOS app development. Therefore, Python can’t keep up with the growing mobile market and sustain its popularity.

Because of its limitations in mobile computing, it is not employed in app development.

Python’s mobile computing features are weak. As a result, it is not commonly utilized in application development.

Since Python is dynamic, mistakes are displayed at run time. Because no errors are generated at compile time, developers running large chunks of code may lose time.

There is no commercial support.


There are several ways in which Python and Java are equivalent to one another. However, there are a few key areas of variation between the two, including execution speed and constraints, the usage of classes during programming, and a few more.

The functioning and selection of either language are determined by the user’s preferences as well as their accessibility. Although gathering knowledge on your own can be difficult.

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