Home > Resources > Articles > A Complete Guide on Getting Started with Deep Learning in Python

A Complete Guide on Getting Started with Deep Learning in Python

October 10, 2019 | 17 views

You seem to come across the term ‘Deep Learning’ everywhere these days. It’s all pervasive and seems to be at the heart of all AI related research. It has even spawned new and never-thought-of-before innovations! But how can you learn it? There are way too many resources out there, spread in a very unstructured and not a very beginner friendly manner. You complete a course on one platform, move to another course on a different platform, and so on. You learn, but not in any logical or sequential manner. That’s a bad idea.

Spotlight

QBurst

QBurst is a global product development and consulting company with proven experience in developing mobile, web, cloud, and analytics solutions. For over a decade, we have been delivering customized, cost-effective, enterprise-grade products and services for startups, mid-size businesses, and large enterprises.

OTHER ARTICLES
AI TECH

Is Progressive Web Apps the Way of the Future for Mobile?

Article | July 11, 2022

Progressive Web Apps (PWAs) enable cross-platform interoperability by giving users access to open web technologies. PWAs give your users an app-like experience that's tailored to their particular device. PWA development is a collection of best software development practices for making a web application behave like a mobile or desktop app. PWAs work similarly to mobile apps providing push notifications and a home screen icon. Progressive web applications, on the other hand, are more straightforward and faster than standard mobile apps, and they can be shared via a URL. According to Statista, there are around 3.5 billion smartphone users globally who utilize a variety of devices with various connection speeds and constantly changing conditions. Web App Vs. Progressive Web App The number of mobile users has expanded dramatically in recent years, necessitating the development of a better mobile web experience. Smartphones are utilized for a variety of purposes, such as reserving a cab or finding the nearest restaurant. Users expect a positive experience with their mobile devices in order to complete these tasks quickly. However, traditional websites are unable to give that experience for a variety of reasons, ranging from poor loading speeds to ambiguous user interfaces. Here's where web apps come in, which provide a better user experience regardless of the device or browser you're using. A typical web app is a website that can be accessed using a URL. Furthermore, these web apps contain several features that give them the appearance and feel of native apps, but they cannot be installed on any device. A progressive web app is the next step that can be installed on a device and appears and feels like a native app. You don't need to use a URL; just install a PWA on your device and run it like any other native app by clicking its icon on the home screen. Case Study Pinterest Pinterest built its new mobile web experience from the ground up as a PWA, with an eye toward worldwide expansion. However, due to poor mobile performance, the social network discovered that only 1% of its mobile users converted into sign-ups, logins, or app installs. Realizing that there was a big chance to boost conversion, they rebuilt the mobile web utilizing PWA technology, which resulted in a number of excellent outcomes: when compared to the prior mobile web, time spent is up 40%, user-generated ad income is up 44%, and core engagements are up 60%. Ali Baba Users of Alibaba's app were dissatisfied with their experience and refused to download or install the app. As a result, Alibaba had to make a progressive web application to make the experience much better for both first-time users and regular customers. As a result, seasoned users were re-engaged thanks to a significantly better experience for first-timers, push alerts, and home screen shortcuts. Alibaba could swiftly improve its re-engagement rate to match that of its native apps. To Sum It Up Developers may create the most excellent progressive apps using standard frameworks like React, Angular, Vue, Polymer, Ionic, and others, which have several advantages over native mobile apps and regular web pages in terms of functionality, user offline experience, and device space usage. Because of their superiority to native desktop and mobile apps in recent years, Progressive Web Programs have emerged as a wonderful alternative to those apps. PWAs take up less space on consumers' smartphones than native apps, encouraging people to install them. Because of caching capabilities, PWAs can work offline because some content is cached during the first visit to the app. Developing a great progressive web app necessitates a strong working relationship with a technical partner. Larger companies can also tap into the PWA industry by giving their users limited access to a PWA and then letting them pick how they want to continue. Overall, you should invest in PWA in 2022 since user experience is critical in this competitive market.

Read More
SOFTWARE

What Are The Best Programming Languages To Develop AI Solution

Article | July 13, 2022

As Artificial Intelligence becomes more popular, it’s essential to know the best programming languages AI uses. If you’re trying to code an AI software solution and don’t know which programming language(s) to use, it can hinder – even hurt – your development process. However, there are a lot of choices when it comes to programming languages you could use to develop an AI solution. So if you’re wondering what the best programming languages for AI are, you’re at the right place! Top 12 The Best Artificial Intelligence Programming Languages 1. Python Python development is one of the most popular programming languages globally and a top choice for AI developers. It’s easy to learn, runs on multiple platforms, and provides an interactive environment that allows you to quickly test ideas and make changes without waiting for a compile or deployment phase. Python development is also one of the fastest-growing languages in popularity and employment opportunities. You can use Python development in various AI applications, including natural language processing (NLP), machine learning, deep learning, and robotics. Python development has also been used in data science applications such as web scraping, web crawling, and scraping data from websites. 2. LISP LISP stands for List Processing Language or LISt Processor. It is a functional programming language that makes it easy to create functions that can manipulate lists of data items. John McCarthy created this language at MIT in 1958. It remains in use today because it is still an excellent vehicle for research in logic programming and because of its continued wide use in artificial intelligence applications such as natural language processing for semantic web applications. LISP is also great for creating neural networks because it can easily manipulate the network’s weights, which is usually the most challenging part of building a neural network. 3. R R is a free software environment for statistical computing and graphics that runs on multiple platforms, including Windows, Unix, macOS X, and Linux operating systems. Ross Ihaka created R and Robert Gentleman at the University of Auckland, New Zealand, in 1993, originally under the name “S.” R provides different analysis methods such as linear regression, generalized linear models, time series analysis, classification, and clustering. The main advantage of using R is that it allows users to develop complex algorithms without having to write complicated code or spend time debugging the code. Its popularity has increased significantly over time due to its ease of use and flexibility from simple linear regressions to multi-level modeling approaches. 4. C++ It is one of the most popular and widely used programming languages for developing AI solutions. It is a general-purpose language used to create software applications, operating systems, and other programs. Bjarne Stroustrup originally developed C++ to enhance C with object-oriented features. Its popularity has increased due to its ability to support multiple paradigms, including object-oriented programming (OOP), imperative and procedural programming techniques, generic programming, and others. 5. JavaScript Netscape Communications Corporation developed JavaScript in 1995, but the standardization of JavaScript only began in 1997 when Ecma International adopted it as ECMAScript. JavaScript is a programming language used by over 65% of developers to create interactive web pages. It is prevalent because you can run it on all modern browsers without installing plug-ins or additional software. You can use JavaScript to create web pages and applications on web browsers and mobile devices like smartphones and tablets. JavaScript also has an object-oriented structure, making it easy for programmers to build complex programs using multiple objects. 6. Java Java is one of the most popular programming languages in the world. As a platform, it has excellent support for AI development. You can use Java for developing machine learning algorithms, deep learning frameworks, and other tools. Many of the most popular libraries and frameworks are written in Java, including Hadoop and TensorFlow. Java is also very popular with enterprises because it has excellent performance, scalability, and portability across different operating systems and hardware platforms. 7. Haskell Haskell is an excellent choice for AI development because it allows for the use of a functional programming paradigm. It means that it will enable you to write your code in a way that focuses on composing functions together instead of focusing on variables and data structures. While this may not seem like a big deal, it makes it easier to reason about your code and make changes without introducing errors. Haskell also has strong type inference capabilities, which allow you to focus on what your program does rather than how it does it. It also makes writing tests and ensuring that your code works as expected without manually testing every possible case. 8. Julia Julia is a high-level, high-performance programming language that makes coding fast and efficient. It’s great for AI development because it’s flexible and easy to learn. Julia combines the speed of C with the usability of Python, making it ideal for numerical computing. Julia is a multi-paradigm programming language that allows you to write code in numerous styles – from functional to imperative, object-oriented to metaprogramming – all within the same program. You can hire an AI developer to take advantage of the best tools for each task instead of forcing everyone down a single path. 9. Prolog One of the most popular programming languages for developing AI solutions is Prolog. It was developed in 1972 and used for decades as a powerful logic programming language. Prolog uses an underlying theory called predicate logic based on facts, rules, and inference. Prolog became popular due to its ability to represent knowledge in a form that can be queried and reasoned about. It makes it ideal for solving problems that require reasoning about the world. Another reason Prolog is so famous for developing AI solutions is because it allows you to hire AI developers to combine logic programming with declarative programming through pattern matching and unification. 10. Scala Scala is a general-purpose programming language that runs on the Java virtual machine. It can be used in distributed and parallel systems, developing scalable software applications. Scala is easy to learn because it integrates object-oriented languages with functional programming features. It was developed by Martin Odersky in 2001 at École Polytechnique Fédérale de Lausanne in Switzerland as an academic research project. Many companies have used Scala to develop AI applications. It has an advantage over other programming languages because it allows to hire AI developers to get the best of both worlds, i.e., object-oriented and functional programming paradigms. Scala is statically typed and uses JVM for execution. You can use Scala for building web applications and big data applications. 11. RUST The Rust programming language is one of the most popular languages for developing AI solutions. It was developed by Mozilla and was released in 2010. The main goal of Rust is to provide a safe, fast, productive, and memory-safe language. Performance is one of the main features of the rust programming language because it can work on a low level with C/C++ and other systems programming languages. Rust is also suitable for machine learning because you can use it to write efficient code without sacrificing safety or performance. 12. Wolfram Wolfram is a programming language and environment for technical computing, data science, and machine learning. Students, teachers, researchers, and commercial developers worldwide develop applications that range from technical and scientific to financial analysis, music generation, and art creation. Wolfram is a great place to start if you’re new to programming because it has a clean syntax that makes it easier to understand than other languages. It’s also inherently visual – you can build your code by dragging blocks together on a canvas. So you don’t need to spend time learning how to write code from scratch before getting started.

Read More
SOFTWARE

Web 3.0: New Horizon of Internet

Article | July 14, 2022

Web 3.0, or as it is commonly known as Web3, is the future avatar of the world of the internet and it is based on decentralization. The present-day internet, or Web 2.0 as it should correctly be referred to, has contributed a lot more to transforming the way we live than any other tool in the universe. Web2 has been a key part of building the digital world we live in today, from Snapchat and Instagram filters to using Augmented Reality (AR) to catch Pokémon. Web3 and Metaverse are the most popular buzzwords today. With the decentralized network, Web 3.0 means that instead of having a few large companies control all the data, users will have equal access to control their data. Web3 also promises to enhance data and network privacy. What does Web 3.0 Mean for Businesses? Web 3.0 presents enormous opportunities for businesses. Let’s explore some of the ways in which Web3 will benefit from this new technology. Enhance Transparency and Trust Web 3.0 technology may help organizations and their consumers boost transparency and trust. Blockchain technology, for instance, can contribute to the creation of a tamper-proof record of transactions. This would help businesses increase customer trust by giving customers a clear picture of how they do business. Increased Security Presently, in Web 2.0, all of your data is saved in one spot in a centralized system. As a result, it is prone to exploitation. However, nothing is more crucial to a company than data security. Web 3.0 technologies decentralizes your data and assists in increasing its security. Deeper Customer Insights Web 3.0 can also help organizations acquire customer insights. How? Web 3.0 brings in data anonymization that allows businesses acquire customer data without fetching their personal data. It also helps businesses scale consumer data at large without any compromise on privacy. The data then gathered through customer insights can be utilized to enhance products and services. Finer Data Searchability Businesses can also deploy Web 3.0 technology to improve the searchability of their data. Using technologies for the semantic web can help make a data web that is easy for machines to search. This would make it easy for companies to get the information they need quickly and without wasting money or time on manual data searches. Better User Experience (UX) By offering a more customized web, Web 3.0 technologies can assist in enhancing the user experience. Artificial intelligence and machine learning algorithms can assist in giving each user a personalized experience that is suited to their specific requirements. As a result, consumer satisfaction and loyalty will rise. Web 3.0 Possible Business Applications Some of the most common possible areas where Web3 will definitely have an effect are: Social Media Web 3.0 transforms how app developers create social media apps. It returns ownership of data from platforms to end-users, making story-spinning and data exploitation impossible, as in the Facebook Cambridge Analytics Scandal. Currency Exchange Service Centralization fails in money exchange. Mt. Gox's $460 million bitcoin hack is a failure. Decentralized exchanges prevent hacker breeding grounds. Web 3.0 will see decentralized exchanges gain popularity for smooth user trades without hackers or lack of transparency. Messaging Platforms Messaging has always played an essential role in our lives. At work, Slack and Telegram replace Facebook Messenger and WhatsApp. Unsafe message transmission and centralized solutions make messaging systems exploitable. Web 3.0 messaging applications like ySign, Obsidian, e-Chat, etc., leverage Blockchain to protect users' privacy and security. Summing-up The Internet's evolution has been substantial, and this trend will undoubtedly continue. Web 3.0 will revolutionize the way we engage with the digital world, and the transition will affect more than just individuals. This will lead to more honest and transparent use of customer data, from tailored search results to cross-platform development tools and 3D graphics. A much more immersive and engaging web is on the way. The new Internet will be around very soon! Let's welcome Web 3.0 with open arms!

Read More
SOFTWARE

Natural Language Processing: An Advanced Implementation of AI

Article | June 1, 2022

Natural Language Processing, also known as computational linguistics or NLP, is a branch of Artificial Intelligence (AI), Machine Learning (ML), and linguistics. It is a subfield of AI that enables computers or machines to understand, manipulate, and interpret human language. Simply put, natural language is the natural method by which humans communicate with one another. We have now trained computers to interpret natural language. Communicating with computers has become simpler with voice queries such as "Alexa, what's the news today?" or "Ok Google, play my favorite songs." Similarly, when you ask Siri, Apple's voice assistant, "What is the cheapest flight to New York later today?" It instantly searches airline and travel websites for flights from the user's location to New York. It also compares the prices and lists the one with the lowest fare first. So, even without specifying a date or the "lowest fare", Siri understands the inquiry and returns accurate results. This is the result of NLP in action. Natural Language Processing: Business Applications Natural language processing has a variety of applications, some of them are listed below. Summarize text blocks to extract the most relevant and core concepts while excluding unnecessary information. Develop a chatbot that makes use of Point-of-Speech tagging to enhance customer support. Chatbots are AI systems that use NLP to engage with people through text or voice. Determine the type of extracted entity, such as a person, location, or organization. Sentiment Analysis can be used to recognize the sentiment or emotions of a text string, ranging from highly negative to neutral to very positive. HR teams can utilize NLP-based solutions to scan resumes based on keyword synonyms and swiftly shortlist candidates from a pile of resumes. Extracting Text data from the data storage allows in extracting specific information from text. Text can be broken down into tokens, or words can be reduced to their root or stem. Topic categorization helps users organize unstructured text. It's a great way for businesses to obtain insights from customer feedback. How Can Businesses Prepare for the NLP-Powered Future? NLP has evolved tremendously, and has benefited both companies and consumers. NLP technologies are assisting businesses to better understand how consumers perceive them through channels such as emails, product reviews, social media postings, surveys, and more. AI technologies can be used not just to analyze online interactions and how people speak about companies but also to automate tedious and time-consuming operations, enhance productivity, and free up staff to concentrate on more meaningful duties. When it comes to NLP the sky is the limit. As NLP technology is becoming more prevalent and greater advancements in ability are explored, the future will witness enormous shifts. Here are some of the ways in which businesses can prepare for the future of NLP. Analyze your company's text data assets and evaluate how the most recent techniques can be used to add value. Understand how you can use AI-powered language technology to make wiser decisions or rearrange your skilled labor. Start implementing new language-based AI tools for a range of jobs in order to better understand their potential. Prepare now to capitalize on transformative AI and to make sure that advanced AI contributes to society fairly. Closing Note Thanks to natural language processing technology, conversational commands and everything related to conversational AI in businesses have become faster and better. Natural language processing helps large businesses make flexible choices by revealing consumer moods and market movements. Smart companies now make decisions based not only on data but also on the intelligence derived from NLP-powered system data.

Read More
AI TECH

AI's Impact on Improving Customer Experience

Article | July 11, 2022

Progressive Web Apps (PWAs) enable cross-platform interoperability by giving users access to open web technologies. PWAs give your users an app-like experience that's tailored to their particular device. PWA development is a collection of best software development practices for making a web application behave like a mobile or desktop app. PWAs work similarly to mobile apps providing push notifications and a home screen icon. Progressive web applications, on the other hand, are more straightforward and faster than standard mobile apps, and they can be shared via a URL. According to Statista, there are around 3.5 billion smartphone users globally who utilize a variety of devices with various connection speeds and constantly changing conditions. Web App Vs. Progressive Web App The number of mobile users has expanded dramatically in recent years, necessitating the development of a better mobile web experience. Smartphones are utilized for a variety of purposes, such as reserving a cab or finding the nearest restaurant. Users expect a positive experience with their mobile devices in order to complete these tasks quickly. However, traditional websites are unable to give that experience for a variety of reasons, ranging from poor loading speeds to ambiguous user interfaces. Here's where web apps come in, which provide a better user experience regardless of the device or browser you're using. A typical web app is a website that can be accessed using a URL. Furthermore, these web apps contain several features that give them the appearance and feel of native apps, but they cannot be installed on any device. A progressive web app is the next step that can be installed on a device and appears and feels like a native app. You don't need to use a URL; just install a PWA on your device and run it like any other native app by clicking its icon on the home screen. Case Study Pinterest Pinterest built its new mobile web experience from the ground up as a PWA, with an eye toward worldwide expansion. However, due to poor mobile performance, the social network discovered that only 1% of its mobile users converted into sign-ups, logins, or app installs. Realizing that there was a big chance to boost conversion, they rebuilt the mobile web utilizing PWA technology, which resulted in a number of excellent outcomes: when compared to the prior mobile web, time spent is up 40%, user-generated ad income is up 44%, and core engagements are up 60%. Ali Baba Users of Alibaba's app were dissatisfied with their experience and refused to download or install the app. As a result, Alibaba had to make a progressive web application to make the experience much better for both first-time users and regular customers. As a result, seasoned users were re-engaged thanks to a significantly better experience for first-timers, push alerts, and home screen shortcuts. Alibaba could swiftly improve its re-engagement rate to match that of its native apps. To Sum It Up Developers may create the most excellent progressive apps using standard frameworks like React, Angular, Vue, Polymer, Ionic, and others, which have several advantages over native mobile apps and regular web pages in terms of functionality, user offline experience, and device space usage. Because of their superiority to native desktop and mobile apps in recent years, Progressive Web Programs have emerged as a wonderful alternative to those apps. PWAs take up less space on consumers' smartphones than native apps, encouraging people to install them. Because of caching capabilities, PWAs can work offline because some content is cached during the first visit to the app. Developing a great progressive web app necessitates a strong working relationship with a technical partner. Larger companies can also tap into the PWA industry by giving their users limited access to a PWA and then letting them pick how they want to continue. Overall, you should invest in PWA in 2022 since user experience is critical in this competitive market.

Read More
SOFTWARE

The Impact of VR and AR on the Automotive Industry

Article | July 13, 2022

As Artificial Intelligence becomes more popular, it’s essential to know the best programming languages AI uses. If you’re trying to code an AI software solution and don’t know which programming language(s) to use, it can hinder – even hurt – your development process. However, there are a lot of choices when it comes to programming languages you could use to develop an AI solution. So if you’re wondering what the best programming languages for AI are, you’re at the right place! Top 12 The Best Artificial Intelligence Programming Languages 1. Python Python development is one of the most popular programming languages globally and a top choice for AI developers. It’s easy to learn, runs on multiple platforms, and provides an interactive environment that allows you to quickly test ideas and make changes without waiting for a compile or deployment phase. Python development is also one of the fastest-growing languages in popularity and employment opportunities. You can use Python development in various AI applications, including natural language processing (NLP), machine learning, deep learning, and robotics. Python development has also been used in data science applications such as web scraping, web crawling, and scraping data from websites. 2. LISP LISP stands for List Processing Language or LISt Processor. It is a functional programming language that makes it easy to create functions that can manipulate lists of data items. John McCarthy created this language at MIT in 1958. It remains in use today because it is still an excellent vehicle for research in logic programming and because of its continued wide use in artificial intelligence applications such as natural language processing for semantic web applications. LISP is also great for creating neural networks because it can easily manipulate the network’s weights, which is usually the most challenging part of building a neural network. 3. R R is a free software environment for statistical computing and graphics that runs on multiple platforms, including Windows, Unix, macOS X, and Linux operating systems. Ross Ihaka created R and Robert Gentleman at the University of Auckland, New Zealand, in 1993, originally under the name “S.” R provides different analysis methods such as linear regression, generalized linear models, time series analysis, classification, and clustering. The main advantage of using R is that it allows users to develop complex algorithms without having to write complicated code or spend time debugging the code. Its popularity has increased significantly over time due to its ease of use and flexibility from simple linear regressions to multi-level modeling approaches. 4. C++ It is one of the most popular and widely used programming languages for developing AI solutions. It is a general-purpose language used to create software applications, operating systems, and other programs. Bjarne Stroustrup originally developed C++ to enhance C with object-oriented features. Its popularity has increased due to its ability to support multiple paradigms, including object-oriented programming (OOP), imperative and procedural programming techniques, generic programming, and others. 5. JavaScript Netscape Communications Corporation developed JavaScript in 1995, but the standardization of JavaScript only began in 1997 when Ecma International adopted it as ECMAScript. JavaScript is a programming language used by over 65% of developers to create interactive web pages. It is prevalent because you can run it on all modern browsers without installing plug-ins or additional software. You can use JavaScript to create web pages and applications on web browsers and mobile devices like smartphones and tablets. JavaScript also has an object-oriented structure, making it easy for programmers to build complex programs using multiple objects. 6. Java Java is one of the most popular programming languages in the world. As a platform, it has excellent support for AI development. You can use Java for developing machine learning algorithms, deep learning frameworks, and other tools. Many of the most popular libraries and frameworks are written in Java, including Hadoop and TensorFlow. Java is also very popular with enterprises because it has excellent performance, scalability, and portability across different operating systems and hardware platforms. 7. Haskell Haskell is an excellent choice for AI development because it allows for the use of a functional programming paradigm. It means that it will enable you to write your code in a way that focuses on composing functions together instead of focusing on variables and data structures. While this may not seem like a big deal, it makes it easier to reason about your code and make changes without introducing errors. Haskell also has strong type inference capabilities, which allow you to focus on what your program does rather than how it does it. It also makes writing tests and ensuring that your code works as expected without manually testing every possible case. 8. Julia Julia is a high-level, high-performance programming language that makes coding fast and efficient. It’s great for AI development because it’s flexible and easy to learn. Julia combines the speed of C with the usability of Python, making it ideal for numerical computing. Julia is a multi-paradigm programming language that allows you to write code in numerous styles – from functional to imperative, object-oriented to metaprogramming – all within the same program. You can hire an AI developer to take advantage of the best tools for each task instead of forcing everyone down a single path. 9. Prolog One of the most popular programming languages for developing AI solutions is Prolog. It was developed in 1972 and used for decades as a powerful logic programming language. Prolog uses an underlying theory called predicate logic based on facts, rules, and inference. Prolog became popular due to its ability to represent knowledge in a form that can be queried and reasoned about. It makes it ideal for solving problems that require reasoning about the world. Another reason Prolog is so famous for developing AI solutions is because it allows you to hire AI developers to combine logic programming with declarative programming through pattern matching and unification. 10. Scala Scala is a general-purpose programming language that runs on the Java virtual machine. It can be used in distributed and parallel systems, developing scalable software applications. Scala is easy to learn because it integrates object-oriented languages with functional programming features. It was developed by Martin Odersky in 2001 at École Polytechnique Fédérale de Lausanne in Switzerland as an academic research project. Many companies have used Scala to develop AI applications. It has an advantage over other programming languages because it allows to hire AI developers to get the best of both worlds, i.e., object-oriented and functional programming paradigms. Scala is statically typed and uses JVM for execution. You can use Scala for building web applications and big data applications. 11. RUST The Rust programming language is one of the most popular languages for developing AI solutions. It was developed by Mozilla and was released in 2010. The main goal of Rust is to provide a safe, fast, productive, and memory-safe language. Performance is one of the main features of the rust programming language because it can work on a low level with C/C++ and other systems programming languages. Rust is also suitable for machine learning because you can use it to write efficient code without sacrificing safety or performance. 12. Wolfram Wolfram is a programming language and environment for technical computing, data science, and machine learning. Students, teachers, researchers, and commercial developers worldwide develop applications that range from technical and scientific to financial analysis, music generation, and art creation. Wolfram is a great place to start if you’re new to programming because it has a clean syntax that makes it easier to understand than other languages. It’s also inherently visual – you can build your code by dragging blocks together on a canvas. So you don’t need to spend time learning how to write code from scratch before getting started.

Read More
SOFTWARE

Unearthing the Potential of Quantum Computing

Article | July 14, 2022

Web 3.0, or as it is commonly known as Web3, is the future avatar of the world of the internet and it is based on decentralization. The present-day internet, or Web 2.0 as it should correctly be referred to, has contributed a lot more to transforming the way we live than any other tool in the universe. Web2 has been a key part of building the digital world we live in today, from Snapchat and Instagram filters to using Augmented Reality (AR) to catch Pokémon. Web3 and Metaverse are the most popular buzzwords today. With the decentralized network, Web 3.0 means that instead of having a few large companies control all the data, users will have equal access to control their data. Web3 also promises to enhance data and network privacy. What does Web 3.0 Mean for Businesses? Web 3.0 presents enormous opportunities for businesses. Let’s explore some of the ways in which Web3 will benefit from this new technology. Enhance Transparency and Trust Web 3.0 technology may help organizations and their consumers boost transparency and trust. Blockchain technology, for instance, can contribute to the creation of a tamper-proof record of transactions. This would help businesses increase customer trust by giving customers a clear picture of how they do business. Increased Security Presently, in Web 2.0, all of your data is saved in one spot in a centralized system. As a result, it is prone to exploitation. However, nothing is more crucial to a company than data security. Web 3.0 technologies decentralizes your data and assists in increasing its security. Deeper Customer Insights Web 3.0 can also help organizations acquire customer insights. How? Web 3.0 brings in data anonymization that allows businesses acquire customer data without fetching their personal data. It also helps businesses scale consumer data at large without any compromise on privacy. The data then gathered through customer insights can be utilized to enhance products and services. Finer Data Searchability Businesses can also deploy Web 3.0 technology to improve the searchability of their data. Using technologies for the semantic web can help make a data web that is easy for machines to search. This would make it easy for companies to get the information they need quickly and without wasting money or time on manual data searches. Better User Experience (UX) By offering a more customized web, Web 3.0 technologies can assist in enhancing the user experience. Artificial intelligence and machine learning algorithms can assist in giving each user a personalized experience that is suited to their specific requirements. As a result, consumer satisfaction and loyalty will rise. Web 3.0 Possible Business Applications Some of the most common possible areas where Web3 will definitely have an effect are: Social Media Web 3.0 transforms how app developers create social media apps. It returns ownership of data from platforms to end-users, making story-spinning and data exploitation impossible, as in the Facebook Cambridge Analytics Scandal. Currency Exchange Service Centralization fails in money exchange. Mt. Gox's $460 million bitcoin hack is a failure. Decentralized exchanges prevent hacker breeding grounds. Web 3.0 will see decentralized exchanges gain popularity for smooth user trades without hackers or lack of transparency. Messaging Platforms Messaging has always played an essential role in our lives. At work, Slack and Telegram replace Facebook Messenger and WhatsApp. Unsafe message transmission and centralized solutions make messaging systems exploitable. Web 3.0 messaging applications like ySign, Obsidian, e-Chat, etc., leverage Blockchain to protect users' privacy and security. Summing-up The Internet's evolution has been substantial, and this trend will undoubtedly continue. Web 3.0 will revolutionize the way we engage with the digital world, and the transition will affect more than just individuals. This will lead to more honest and transparent use of customer data, from tailored search results to cross-platform development tools and 3D graphics. A much more immersive and engaging web is on the way. The new Internet will be around very soon! Let's welcome Web 3.0 with open arms!

Read More
SOFTWARE

Natural Language Processing: An Advanced Implementation of AI

Article | June 1, 2022

Natural Language Processing, also known as computational linguistics or NLP, is a branch of Artificial Intelligence (AI), Machine Learning (ML), and linguistics. It is a subfield of AI that enables computers or machines to understand, manipulate, and interpret human language. Simply put, natural language is the natural method by which humans communicate with one another. We have now trained computers to interpret natural language. Communicating with computers has become simpler with voice queries such as "Alexa, what's the news today?" or "Ok Google, play my favorite songs." Similarly, when you ask Siri, Apple's voice assistant, "What is the cheapest flight to New York later today?" It instantly searches airline and travel websites for flights from the user's location to New York. It also compares the prices and lists the one with the lowest fare first. So, even without specifying a date or the "lowest fare", Siri understands the inquiry and returns accurate results. This is the result of NLP in action. Natural Language Processing: Business Applications Natural language processing has a variety of applications, some of them are listed below. Summarize text blocks to extract the most relevant and core concepts while excluding unnecessary information. Develop a chatbot that makes use of Point-of-Speech tagging to enhance customer support. Chatbots are AI systems that use NLP to engage with people through text or voice. Determine the type of extracted entity, such as a person, location, or organization. Sentiment Analysis can be used to recognize the sentiment or emotions of a text string, ranging from highly negative to neutral to very positive. HR teams can utilize NLP-based solutions to scan resumes based on keyword synonyms and swiftly shortlist candidates from a pile of resumes. Extracting Text data from the data storage allows in extracting specific information from text. Text can be broken down into tokens, or words can be reduced to their root or stem. Topic categorization helps users organize unstructured text. It's a great way for businesses to obtain insights from customer feedback. How Can Businesses Prepare for the NLP-Powered Future? NLP has evolved tremendously, and has benefited both companies and consumers. NLP technologies are assisting businesses to better understand how consumers perceive them through channels such as emails, product reviews, social media postings, surveys, and more. AI technologies can be used not just to analyze online interactions and how people speak about companies but also to automate tedious and time-consuming operations, enhance productivity, and free up staff to concentrate on more meaningful duties. When it comes to NLP the sky is the limit. As NLP technology is becoming more prevalent and greater advancements in ability are explored, the future will witness enormous shifts. Here are some of the ways in which businesses can prepare for the future of NLP. Analyze your company's text data assets and evaluate how the most recent techniques can be used to add value. Understand how you can use AI-powered language technology to make wiser decisions or rearrange your skilled labor. Start implementing new language-based AI tools for a range of jobs in order to better understand their potential. Prepare now to capitalize on transformative AI and to make sure that advanced AI contributes to society fairly. Closing Note Thanks to natural language processing technology, conversational commands and everything related to conversational AI in businesses have become faster and better. Natural language processing helps large businesses make flexible choices by revealing consumer moods and market movements. Smart companies now make decisions based not only on data but also on the intelligence derived from NLP-powered system data.

Read More
MORE ARTICLES

Spotlight

QBurst

QBurst is a global product development and consulting company with proven experience in developing mobile, web, cloud, and analytics solutions. For over a decade, we have been delivering customized, cost-effective, enterprise-grade products and services for startups, mid-size businesses, and large enterprises.

Related News

SOFTWARE

Workato joins AWS ISV Accelerate Program and AWS Marketplace

Workato | August 12, 2022

Workato, a leading enterprise automation platform, has announced today that it has been accepted into the Amazon Web Services (AWS) Independent Software Vendor (ISV) Accelerate Program, a co-sell program for organizations that provide software solutions that run on or integrate with AWS. The program helps organizations drive new business and accelerate sales cycles by connecting the participating ISVs with the AWS Sales organization. Workato Enterprise Automation Platform is also now available in AWS Marketplace. Through the AWS ISV Accelerate Program, Workato receives focused co-sell support and benefits to connect with AWS field sellers globally, who service millions of active AWS customers. Co-selling provides better customer outcomes and provides mutual commitment from AWS and AWS Partners. AWS Marketplace is a curated digital catalog that customers can use to find, buy, deploy, and manage third-party software, data, and services to build solutions and run their businesses on AWS. Customers can find thousands of software, solutions, and services across a number of categories including security, machine learning, business applications, and more. They can quickly launch pre-configured software, and choose software solutions in Amazon Machine Images (AMIs), software as a service (SaaS), and other formats. “We are beyond excited to join the AWS ISV Accelerate Program, further cementing our position within the enterprise automation space. To pair this with our debut in AWS Marketplace lends itself to our continued commitment to enabling companies to tap into the growth mindset and transform their organization with Workato. “This endeavor allows us to reach new AWS customers and help them reach their fullest potential.” Markus Zirn, Senior Vice President, Strategy & Business Development at Workato Workato is transforming automation across businesses with a single platform for data, apps, and processes and is emerging as a market leader in enterprise automation. Workato is a proven automation platform that allows organizations to build scalable quote-to-cash processes that increase accuracy and speed while reducing human intervention. Enterprises significantly improve their quote-to-cash approach while also providing a better purchasing experience to the end customer. Workato solutions running on AWS allow companies to automate work throughout the entire organization — completely on the cloud. Building on the relationship with AWS, Workato is also helping joint customers solve complex business challenges, starting with Quote-to-Cash. The solution enables organizations to better integrate their tech stack to allow for seamless data transfer and bilateral sync and to automate repeatable processes at scale to further improve efficiency and accuracy. About Workato The leader in enterprise automation, Workato helps organizations work faster and smarter without compromising security and governance. Built for Business and IT users, Workato is trusted by over 17,000 of the world's top brands, including Broadcom, Intuit, and Box. Headquartered in Mountain View, Calif., Workato is backed by Altimeter Capital, Battery Ventures, Insight Venture Partners, Tiger Global, and Redpoint Ventures.

Read More

SOFTWARE

New Relic Brings Error Tracking into Atlassian Open DevOps Solution

New Relic | August 10, 2022

New Relic , the observability company, today announced it has joined the Atlassian Platform Partner Program as part of the Atlassian Open DevOps solution that integrates Jira Software with popular DevOps tools. New Relic has integrated errors inbox with Jira Software to empower developers to easily access and set up full stack error tracking and software performance monitoring from inside Jira Software, Atlassian’s issue and project management tool. With this integration, developers can create Jira Software issues directly within errors inbox, the New Relic platform functionality for error tracking. This announcement coincides with the launch of the Jira Software toolchain page, which helps developer teams to discover and install DevOps tools to improve DevOps practices across their software development lifecycle. “As applications grow more complex, developers need a system in place to proactively fix errors before the customer experience is impacted,” said Peter Pezaris, SVP, Strategy and User Experience at New Relic. “Errors inbox for Jira Software, which builds on the strong history between New Relic and Atlassian, makes developers’ lives easier by allowing them to get to the root cause faster with full error details — including stack traces — and alerts whenever a critical, customer-impacting error arises. Ticketing is made easier, too, as teams can instantly create Jira Software issues with all the right information, without leaving their error management workflow.” Key benefits and capabilities of the New Relic and Jira Software integration include: Track, triage, and resolve errors in one place: Errors are grouped and displayed on a single screen for visibility and easy triaging. Tackle errors across the full application stack with APM, RUM, Mobile, and Serverless (Lambda Functions) data tracked. Resolve errors before impacting customers: Proactively review and triage errors before they affect customers. Get to the root cause faster with full error details, including stack traces and logs in context, provided in the error inbox. Collaborate across teams: Squash bugs as a team with shared error visibility, shared comments, and an integration with Slack. Create Jira Software issues with a click: With the new integration, set up templates and quickly file Jira ​​Software issues containing error details, associated issues, and direct links to the stack trace and entities in New Relic for easy debugging. “Atlassian and New Relic share a vision to improve the developer experience by meeting users where they are and allowing them to use the tools they know and love. “We are excited to include New Relic errors inbox as an app in the Jira Software toolchain page, which makes it easier for millions of users to discover and connect DevOps apps used throughout the software development lifecycle to fill gaps in the toolchain as their DevOps practices evolve.” Bryant Lee, VP of Partnerships and Developer Experience at Atlassian “We have been really impressed with how New Relic errors inbox offers a single place to track all the errors for the entire stack," said Mudit Mehta, Software Engineer II at Postman. "Errors inbox helps developers save time instead of looking and jumping through multiple tools for cloud-based or external error tracking. With the integration for Jira Software, I can quickly view an error and notify the right team members by filing a templated Jira Software issue in seconds without even leaving the New Relic platform.” The Jira Software toolchain page is the latest collaboration between New Relic and Atlassian. The integration builds on the recent launch of the Bitbucket quickstart in New Relic Instant Observability, which gives engineers visibility into the health and performance of their Bitbucket pipelines to continuously improve and optimize their deployments. Developers can also connect Jira Software to New Relic alerts to help the right teams get the right information in the software development life cycle. Errors inbox for Jira Software is available for free to all New Relic full platform users and Jira Cloud users. For more information, visit www.newrelic.com. Additional integrations for Atlassian’s Connect applications with errors inbox and other capabilities will be available later this year. About New Relic As a leader in observability, New Relic empowers engineers with a data-driven approach to planning, building, deploying, and running great software. New Relic delivers the only unified data platform that empowers engineers to get all telemetry—metrics, events, logs, and traces—paired with powerful full stack analysis tools to help engineers do their best work with data, not opinions. Delivered through the industry’s first usage-based consumption pricing that’s intuitive and predictable, New Relic gives engineers more value for the money by helping improve planning cycle times, change failure rates, release frequency, and mean time to resolution. This helps the world’s leading brands including adidas Runtastic, American Red Cross, Australia Post, Banco Inter, Chegg, GoTo Group, Ryanair, Sainsbury’s, Signify Health, TopGolf, and World Fuel Services (WFS) improve uptime, reliability, and operational efficiency to deliver exceptional customer experiences that fuel innovation and growth.

Read More

SOFTWARE

Cycle.io announces partnership with leading custom Software Development firm, Dev.Pro

Cycle.io | August 05, 2022

Cycle.io, a low-ops application deployment platform, recently announced the Cycle Partner Program, and today we are happy to add Dev.Pro as one of our new Development Agency Partners. Our partnership empowers Dev.Pro development teams to build and deploy advanced solutions, products, and services efficiently on the Cycle Platform. Dev.Pro, a US based software, custom development partner, works with customers across many industries using state of the art technologies. Dev.Pro enables their customers to grow by expediting time to market and delivering new products and features in a cost effective and efficient manner. This new partnership with Cycle expands the Dev.Pro portfolio and ensures that customers continue to have access to the latest solutions. “The Cycle & Dev.Pro partnership is a natural fit for both organizations. Cycle offers a reliable, scalable, and feature rich platform; while Dev.Pro has the engineering expertise and experience to build and support even the most complex environments. ” Brian Agee, Chief Revenue Officer, Dev.Pro. Cycle’s all-in-one platform has been used to deploy over a million containers, becoming the bridge between our partners' infrastructure and their code. The platform offers increased flexibility to scale their solutions utilizing Cycle’s rich set of features via the portal or through their powerful API. “We are extremely excited to have Dev.Pro join our partner program. Dev.Pro has a reputation for having impressive engineering skills and outperforming customer expectations. Working with the Dev.Pro team over the course of the past six months indicates that this is only the tip of the iceberg”. Karl Empey, Head of Sales, Cycle.io. About Cycle Cycle is the all-in-one low-ops platform built for deploying, scaling, and monitoring your websites, backends, and APIs. With automatic platform updates, standardized deployments, a powerful API, and bottleneck crushing automation—the platform offers batteries included, and no DevOps team required. Founded in 2015, the company is headquartered in Reno, NV. About Dev.Pro Dev.Pro is a software development partner that allows innovative technology companies to amplify their growth ambitions and expedite time-to-market.Result-driven. Quality-obsessed. Dev.Pro builds teams that deliver a custom software development experience to meet any skillset, complexity, or scale. With a carefully curated staff of more than 850 highly skilled specialists, Dev.Pro offers a wide range of technical expertise including: Software Development, Cloud, DevOps, UI/UX Design, System Integration, Reporting/Analytics, and Manual/Automation Testing. Dev.Pro is a globally distributed company operating in 50+ countries spread across 5 continents.

Read More

SOFTWARE

Workato joins AWS ISV Accelerate Program and AWS Marketplace

Workato | August 12, 2022

Workato, a leading enterprise automation platform, has announced today that it has been accepted into the Amazon Web Services (AWS) Independent Software Vendor (ISV) Accelerate Program, a co-sell program for organizations that provide software solutions that run on or integrate with AWS. The program helps organizations drive new business and accelerate sales cycles by connecting the participating ISVs with the AWS Sales organization. Workato Enterprise Automation Platform is also now available in AWS Marketplace. Through the AWS ISV Accelerate Program, Workato receives focused co-sell support and benefits to connect with AWS field sellers globally, who service millions of active AWS customers. Co-selling provides better customer outcomes and provides mutual commitment from AWS and AWS Partners. AWS Marketplace is a curated digital catalog that customers can use to find, buy, deploy, and manage third-party software, data, and services to build solutions and run their businesses on AWS. Customers can find thousands of software, solutions, and services across a number of categories including security, machine learning, business applications, and more. They can quickly launch pre-configured software, and choose software solutions in Amazon Machine Images (AMIs), software as a service (SaaS), and other formats. “We are beyond excited to join the AWS ISV Accelerate Program, further cementing our position within the enterprise automation space. To pair this with our debut in AWS Marketplace lends itself to our continued commitment to enabling companies to tap into the growth mindset and transform their organization with Workato. “This endeavor allows us to reach new AWS customers and help them reach their fullest potential.” Markus Zirn, Senior Vice President, Strategy & Business Development at Workato Workato is transforming automation across businesses with a single platform for data, apps, and processes and is emerging as a market leader in enterprise automation. Workato is a proven automation platform that allows organizations to build scalable quote-to-cash processes that increase accuracy and speed while reducing human intervention. Enterprises significantly improve their quote-to-cash approach while also providing a better purchasing experience to the end customer. Workato solutions running on AWS allow companies to automate work throughout the entire organization — completely on the cloud. Building on the relationship with AWS, Workato is also helping joint customers solve complex business challenges, starting with Quote-to-Cash. The solution enables organizations to better integrate their tech stack to allow for seamless data transfer and bilateral sync and to automate repeatable processes at scale to further improve efficiency and accuracy. About Workato The leader in enterprise automation, Workato helps organizations work faster and smarter without compromising security and governance. Built for Business and IT users, Workato is trusted by over 17,000 of the world's top brands, including Broadcom, Intuit, and Box. Headquartered in Mountain View, Calif., Workato is backed by Altimeter Capital, Battery Ventures, Insight Venture Partners, Tiger Global, and Redpoint Ventures.

Read More

SOFTWARE

New Relic Brings Error Tracking into Atlassian Open DevOps Solution

New Relic | August 10, 2022

New Relic , the observability company, today announced it has joined the Atlassian Platform Partner Program as part of the Atlassian Open DevOps solution that integrates Jira Software with popular DevOps tools. New Relic has integrated errors inbox with Jira Software to empower developers to easily access and set up full stack error tracking and software performance monitoring from inside Jira Software, Atlassian’s issue and project management tool. With this integration, developers can create Jira Software issues directly within errors inbox, the New Relic platform functionality for error tracking. This announcement coincides with the launch of the Jira Software toolchain page, which helps developer teams to discover and install DevOps tools to improve DevOps practices across their software development lifecycle. “As applications grow more complex, developers need a system in place to proactively fix errors before the customer experience is impacted,” said Peter Pezaris, SVP, Strategy and User Experience at New Relic. “Errors inbox for Jira Software, which builds on the strong history between New Relic and Atlassian, makes developers’ lives easier by allowing them to get to the root cause faster with full error details — including stack traces — and alerts whenever a critical, customer-impacting error arises. Ticketing is made easier, too, as teams can instantly create Jira Software issues with all the right information, without leaving their error management workflow.” Key benefits and capabilities of the New Relic and Jira Software integration include: Track, triage, and resolve errors in one place: Errors are grouped and displayed on a single screen for visibility and easy triaging. Tackle errors across the full application stack with APM, RUM, Mobile, and Serverless (Lambda Functions) data tracked. Resolve errors before impacting customers: Proactively review and triage errors before they affect customers. Get to the root cause faster with full error details, including stack traces and logs in context, provided in the error inbox. Collaborate across teams: Squash bugs as a team with shared error visibility, shared comments, and an integration with Slack. Create Jira Software issues with a click: With the new integration, set up templates and quickly file Jira ​​Software issues containing error details, associated issues, and direct links to the stack trace and entities in New Relic for easy debugging. “Atlassian and New Relic share a vision to improve the developer experience by meeting users where they are and allowing them to use the tools they know and love. “We are excited to include New Relic errors inbox as an app in the Jira Software toolchain page, which makes it easier for millions of users to discover and connect DevOps apps used throughout the software development lifecycle to fill gaps in the toolchain as their DevOps practices evolve.” Bryant Lee, VP of Partnerships and Developer Experience at Atlassian “We have been really impressed with how New Relic errors inbox offers a single place to track all the errors for the entire stack," said Mudit Mehta, Software Engineer II at Postman. "Errors inbox helps developers save time instead of looking and jumping through multiple tools for cloud-based or external error tracking. With the integration for Jira Software, I can quickly view an error and notify the right team members by filing a templated Jira Software issue in seconds without even leaving the New Relic platform.” The Jira Software toolchain page is the latest collaboration between New Relic and Atlassian. The integration builds on the recent launch of the Bitbucket quickstart in New Relic Instant Observability, which gives engineers visibility into the health and performance of their Bitbucket pipelines to continuously improve and optimize their deployments. Developers can also connect Jira Software to New Relic alerts to help the right teams get the right information in the software development life cycle. Errors inbox for Jira Software is available for free to all New Relic full platform users and Jira Cloud users. For more information, visit www.newrelic.com. Additional integrations for Atlassian’s Connect applications with errors inbox and other capabilities will be available later this year. About New Relic As a leader in observability, New Relic empowers engineers with a data-driven approach to planning, building, deploying, and running great software. New Relic delivers the only unified data platform that empowers engineers to get all telemetry—metrics, events, logs, and traces—paired with powerful full stack analysis tools to help engineers do their best work with data, not opinions. Delivered through the industry’s first usage-based consumption pricing that’s intuitive and predictable, New Relic gives engineers more value for the money by helping improve planning cycle times, change failure rates, release frequency, and mean time to resolution. This helps the world’s leading brands including adidas Runtastic, American Red Cross, Australia Post, Banco Inter, Chegg, GoTo Group, Ryanair, Sainsbury’s, Signify Health, TopGolf, and World Fuel Services (WFS) improve uptime, reliability, and operational efficiency to deliver exceptional customer experiences that fuel innovation and growth.

Read More

SOFTWARE

Cycle.io announces partnership with leading custom Software Development firm, Dev.Pro

Cycle.io | August 05, 2022

Cycle.io, a low-ops application deployment platform, recently announced the Cycle Partner Program, and today we are happy to add Dev.Pro as one of our new Development Agency Partners. Our partnership empowers Dev.Pro development teams to build and deploy advanced solutions, products, and services efficiently on the Cycle Platform. Dev.Pro, a US based software, custom development partner, works with customers across many industries using state of the art technologies. Dev.Pro enables their customers to grow by expediting time to market and delivering new products and features in a cost effective and efficient manner. This new partnership with Cycle expands the Dev.Pro portfolio and ensures that customers continue to have access to the latest solutions. “The Cycle & Dev.Pro partnership is a natural fit for both organizations. Cycle offers a reliable, scalable, and feature rich platform; while Dev.Pro has the engineering expertise and experience to build and support even the most complex environments. ” Brian Agee, Chief Revenue Officer, Dev.Pro. Cycle’s all-in-one platform has been used to deploy over a million containers, becoming the bridge between our partners' infrastructure and their code. The platform offers increased flexibility to scale their solutions utilizing Cycle’s rich set of features via the portal or through their powerful API. “We are extremely excited to have Dev.Pro join our partner program. Dev.Pro has a reputation for having impressive engineering skills and outperforming customer expectations. Working with the Dev.Pro team over the course of the past six months indicates that this is only the tip of the iceberg”. Karl Empey, Head of Sales, Cycle.io. About Cycle Cycle is the all-in-one low-ops platform built for deploying, scaling, and monitoring your websites, backends, and APIs. With automatic platform updates, standardized deployments, a powerful API, and bottleneck crushing automation—the platform offers batteries included, and no DevOps team required. Founded in 2015, the company is headquartered in Reno, NV. About Dev.Pro Dev.Pro is a software development partner that allows innovative technology companies to amplify their growth ambitions and expedite time-to-market.Result-driven. Quality-obsessed. Dev.Pro builds teams that deliver a custom software development experience to meet any skillset, complexity, or scale. With a carefully curated staff of more than 850 highly skilled specialists, Dev.Pro offers a wide range of technical expertise including: Software Development, Cloud, DevOps, UI/UX Design, System Integration, Reporting/Analytics, and Manual/Automation Testing. Dev.Pro is a globally distributed company operating in 50+ countries spread across 5 continents.

Read More

Events

GITEX GLOBAL

Conference

GITEX GLOBAL

Conference