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AI’s Role in Building the Metaverse

Abhinav Anand | June 24, 2022 | 92 views | Read Time : 2 min

AI’s Role in Building the Metaverse
Metaverse is the newest growing topic in technology, with a lot of conversation taking place around how Metaverse is going to change the dynamics of socioeconomics. As a result, several businesses worldwide are already working towards developing services that cater to this new digital environment. Backed by AI, this environment has functions of AI that mix multiple technologies, including VR, 3D animation, and blockchain.

This gives us a glimpse of how seriously Metaverse is parading towards becoming the next most popular technology. Even the technological behemoth Facebook recently changed its name to Meta. Artificial intelligence will enable, populate and sustain the Metaverse. At its core, AI will eventually power all the technical layers of the Metaverse, enabling spatial computing, giving creators a framework, and bringing forth new, complex storytelling techniques.

Application of AI in Metaverse

The future of the Metaverse can benefit from AI, both from a commercial standpoint and in terms of how AI might make the Metaverse more inclusive.


Inclusive User Interfaces

The promise of extremely immersive experiences is one of the cornerstones of the Metaverse's potential success. While for some people, this can enhance social relationships, it also has the potential to operate as a significant barrier for others with disabilities trying to access this emerging digital world. Additionally, those with limited digital skills may find themselves excluded from this new social environment and experience. Because of this, AI for accessibility should be a key component in ensuring that everyone, regardless of their capabilities, has access to the Metaverse.

Learning the Data

We are already aware that learning data is one of the critical components of artificial intelligence and machine learning. When a model is fed historical data, it picks up on the outputs of the preceding model and uses these to suggest new and more effective outcomes.


The outputs improve gradually over time as additional data and human input are added to the model. The likelihood that AI will one day be able to carry out activities and produce accurate results in the same way that humans can is ascending as a result of this. This reduces the need for human intervention while increasing the Metaverse's capacity for expansion.


Conclusion

The number of machine-learning factors will continue to grow exponentially as we go towards the future, which will result in even more realistic AI storytelling, creative collaboration, and machine understanding.


A compelling, authentic, and scalable metaverse experience will ultimately be challenging to produce without AI. Because of this, organizations like Meta are collaborating closely with think tanks and ethics groups to reduce the risks associated with AI without compromising the technology's promise.

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

Article | March 2, 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.

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AI TECH

What Are The Best Programming Languages To Develop AI Solution

Article | February 3, 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.

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AI TECH

Web 3.0: New Horizon of Internet

Article | December 17, 2021

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!

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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.

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Engaging the Metaverse - Innovation and Changing Paradigms in E-learning Design—part II

Article | March 2, 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
AI TECH

AI/ML in 2022: More Real-world Deployments, Focus on AI Ethics and Blockchain Hopes

Article | February 3, 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.

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AI TECH

The Future of Virtual Reality and Augmented Reality

Article | December 17, 2021

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.

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WorkWave Launches ServiceBot™ by WorkWave, Delivering Powerful AI Sales Technology to a Variety of Service Industries

WorkWave | August 04, 2022

WorkWave®, a leading provider of SaaS software solutions that support every stage of a service business's life cycle, has announced the launch of ServiceBot, a highly successful sales automation tool which makes e-commerce easy via an artificial intelligence (AI)-enabled chatbot that lives on a company's website. Formerly known as Lawnbot, ServiceBot will now be available for all service industries, from lawn care to pest control to cleaning, and more. "At WorkWave, we have made a promise to propel the industries we lead forward, and this means continuing to deliver innovation that helps our customers win and outpace their competition — ServiceBot clearly does that. "ServiceBot is the first use of AI technology within WorkWave platforms and solutions, and opens the door across the entire portfolio to incorporate this type of technology into other areas that drive operational efficiency or improve the customer experience. Hundreds of our customers are already using ServiceBot to generate new customers 24 hours a day, 7 days a week." WorkWave CEO David F. Giannetto ServiceBot shows the power of WorkWave's business model, and its recent expansion to lead multiple industries, by bringing its greater resources to bear, helping Lawnbot to evolve into ServiceBot which can now support any home service business. ServiceBot automates the sales process and allows consumers to purchase, schedule and pay for service visits right on their website, through AI-driven, human-like interactions. ServiceBot is seamlessly integrated into WorkWave's industry-leading platforms including Real Green SA5 and is currently being integrated into PestPac, with ServMan and WinTeam soon to come. With ServiceBot, customers can offer service to potential customers at any moment. As a mobile device-friendly, 24-hour, one-stop-shop sales automation tool, ServiceBot is able to sell to customers wherever they are, at any time. About WorkWave For nearly 40 years, WorkWave has been building best practices into its market-leading field service and last mile software solutions to allow best-in-class companies to grow their business, service their customers and maximize their money. Its solutions empower service-oriented companies to reach their full potential through scalable, cloud-based software solutions that support every stage of a business life cycle, including marketing, sales, service delivery, customer interaction and financial transactions. WorkWave is a trusted partner for thousands of customers across a wide variety of industries, including pest control, lawn care, cleaning, HVAC, plumbing and electrical, and last mile delivery. WorkWave's award-winning culture and solutions have been recognized in the SaaS Awards, the Cloud Awards, the American Business Awards, the NJBIZ Best Places to Work Awards, and the Stevie Awards for Great Employers.

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Inspur Information's AIStation Works With NVIDIA AI Enterprise Software Suite to Power Innovation

Inspur Information | August 03, 2022

Inspur Information, a leading IT infrastructure solutions provider, is combining AIStation, its unified management and scheduling AI computing resource platform, with NVIDIA AI Enterprise, a cloud-native suite of AI and data analytics software, to provide enterprise users with a convenient and efficient platform for utilizing AI computing resources. This includes professional development, advanced deployment tools, and state-of-the-art components. The combined platform allows enterprises to quickly implement the industry's most advanced AI capabilities and rapidly deploy AI applications to drive intelligent business innovation. There have been multiple attempts to build AI resource stacks for improving AI innovation and implementation. However, implementing AI technologies is a very challenging task. Enterprises not only need to meet requirements for computing power, but also maximize their computing resource utilization, quickly build and manage AI deployment environments, and efficiently introduce AI capabilities. It requires an AI platform that supports agile development and necessitates easy management and deployment to quickly implement AI applications and accelerate their performance. Inspur Information's AIStation is an end-to-end platform that provides one-stop support for AI development and deployment. With powerful resource scheduling and management capabilities, it accelerates the development and deployment of AI technologies. NVIDIA AI Enterprise is an optimized end-to-end, cloud-native AI and data analytics software suite. It supports the processes from environment construction, data processing, training, and inference to allow for faster development and implementation of AI technologies. AIStation's superior scheduling, management and monitoring capabilities are able to fully unleash NVIDIA AI Enterprise's excellent AI development and deployment capabilities. The combined solution expertly handles data storage, computing power and task scheduling, cluster operation and maintenance, and provides enterprises with an agile and easy-to-use AI platform that can fully utilize their AI computing resources. It also enhances the development and deployment of AI-related tools and components. Resulting AI development and deployment is markedly sped up, making AI transformation more efficient, and improving the business value of AI. Detailed benefits of the combined Inspur Information and NVIDIA AI Enterprise solution include: Maximizing computing resources The solution makes it easier for enterprise customers to use and manage hardware infrastructure including NVIDIA GPUs, and supports Multi-Instance GPU features in the NVIDIA Ampere architecture, enabling users to centrally allocate and monitor computing resources and efficiently allocate those computing resources in large-scale computing power clusters. Acquiring AI capabilities quickly The cloud-native environment management mechanism based on Docker containers gives users an effort-free experience for building cloud-native development environments. Thanks to the powerful scheduling and management capabilities of Inspur Information's AIStation and the professional frameworks, models, applications and development tools of NVIDIA AI Enterprise, users can build AI environments and run AI tasks with ease to achieve fast delivery and quickly introduce advanced AI capabilities. Managing AI infrastructure with ease The multi-tenant management policy allows cluster administrators to focus on managing hardware infrastructure and controlling user quotas. Users can manage AI services and perform AI production within quota limits, and developers can quickly obtain AI compute resources without needing to be audited by administrators often. In addition, administrators can monitor key services and performance of the platform in real-time, and improve system availability by leveraging the fault-tolerant mechanisms and high-availability architecture. Today, AI technologies are changing various industries such as finance, transportation, medical care, education, and scientific research. By introducing AI technologies and applications, enterprises can boost their business capabilities and create greater value. Inspur Information is working closely with NVIDIA to promote the construction of intelligent computing infrastructure and develop AI capability stacks to further accelerate enterprises' AI strategies and AI transformation. Inspur Information and NVIDIA have a longstanding collaboration, with Inspur AI servers supporting the full lineup of NVIDIA GPUs, including the NVIDIA A100, A30, A10, and A2. Inspur AI servers were among the first in the industry to fully support NVIDIA Ampere architecture-based GPUs and the company has obtained NVIDIA-Certified System status for its AI servers. About Inspur Information Inspur Information is a leading provider of data center infrastructure, cloud computing, and AI solutions. It is the world’s 2nd largest server manufacturer. Through engineering and innovation, Inspur Information delivers cutting-edge computing hardware design and extensive product offerings to address important technology sectors such as open computing, cloud data center, AI, and deep learning. Performance-optimized and purpose-built, our world-class solutions empower customers to tackle specific workloads and real-world challenges.

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Vendr Launches 2.0, The Most Complete SaaS Buying Platform on The Market

Vendr | August 10, 2022

Vendr, the world’s first SaaS buying platform, today announced the launch of Vendr 2.0, the most complete SaaS buying platform on the market. SaaS is a top-three line item expense, but most companies aren’t getting the appropriate return on their software investment. Vendr 2.0 harnesses Vendr’s SaaS purchasing and SaaS management products, combining the power of seasoned negotiators armed with insights from over 13,000 deals alongside robust software featuring an integrated system of record. Now, enterprise customers will be equipped with an unprecedented level of visibility into which software their teams are buying and using — in one central location. This enables leaders to reduce overspend and eliminate duplicative products. Most importantly, it unlocks insights that lead to better software choices and faster procurement at lower prices. The launch comes on the heels of the company’s recent ​​$150MM Series B, co-led by return investor Craft Ventures and new investor SoftBank Vision Fund 2––which brought the company into Unicorn status––and its acquisition of SaaS management company Blissfully earlier this year. “The software purchasing process is broken and becoming all the more cumbersome as companies everywhere work to cut costs, as they seek to do more with less. “The introduction of Vendr 2.0 enables organizations to manage their second-highest expense––software––more effectively than ever before, while reducing the difficulties surrounding the process. Vendr 2.0 aims to be the most complete, no-brainer, SaaS buying platform on the market –– and one that pays for itself.” Ryan Neu, Vendr CEO and co-founder The standard buying process historically wastes time and resources for both software vendors and customers. Vendr enables businesses to maximize the return on their SaaS investments through cost savings and more efficient spend, improving stack visibility across the organization. Composed of the best industry data of more than 2,000 SaaS suppliers, Vendr 2.0 is facilitating critical transformation in how organizations purchase and manage software. Tapping Into Transparency Software buying is a perpetual process and it no longer makes sense to have buying and supplier lifecycle management exist in disparate places. By bringing everything into one place, companies layer the benefits of an expert service team and deep SaaS insights into an integrated system of record that offers unparalleled visibility into their stack. Using Vendr, customers can take a proactive approach to their SaaS spend, equipping their teams with the best software while saving money. Buyer <-> supplier: Vendr offers insights and negotiation support to help buyers and sellers quickly evaluate whether a deal is fair for both sides, ensuring that the process continues moving along internally once it comes time to buy. Buyer <-> procurement function: Vendr provides visibility into internal approval workflows and offers fast-tracked ways to request purchases, leading to smoother relationships between buyers and their company procurement functions. Finance/procurement <-> department heads: With better visibility and faster purchase cycles, stakeholders can easily see the value-add of finance and procurement, ensuring compliance and keeping a handle on costs, leading to better business outcomes for all. This new platform builds upon the competitive advantages that Vendr has in the market as the category creator with the deepest source of supplier insight––based on thousands of deals––as well as the most seasoned negotiators in the industry. Vendr has processed over $1.5B in customer software spend and delivered over $240M in software savings to its customers. To see how much you could be saving on your annual software expense, get in touch here. About Vendr Vendr is changing how companies find, buy and manage SaaS. The first of its kind, Vendr's SaaS buying platform offers both a product and people-powered service to enable the world's fastest-growing companies to purchase software quickly and with guaranteed savings. Today, Vendr has facilitated over $1.5B+ in SaaS purchases across 2,500+ suppliers for Finance and Procurement teams at HubSpot, Brex, Canva, Reddit, Toast, and more. Headquartered in Boston with a second location in Charleston, Vendr was founded in 2019 by Ryan Neu and co-founders Ariel Diaz and Aaron White, who joined the team through the acquisition of Blissfully in 2022. The company has over 250 employees globally

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WorkWave Launches ServiceBot™ by WorkWave, Delivering Powerful AI Sales Technology to a Variety of Service Industries

WorkWave | August 04, 2022

WorkWave®, a leading provider of SaaS software solutions that support every stage of a service business's life cycle, has announced the launch of ServiceBot, a highly successful sales automation tool which makes e-commerce easy via an artificial intelligence (AI)-enabled chatbot that lives on a company's website. Formerly known as Lawnbot, ServiceBot will now be available for all service industries, from lawn care to pest control to cleaning, and more. "At WorkWave, we have made a promise to propel the industries we lead forward, and this means continuing to deliver innovation that helps our customers win and outpace their competition — ServiceBot clearly does that. "ServiceBot is the first use of AI technology within WorkWave platforms and solutions, and opens the door across the entire portfolio to incorporate this type of technology into other areas that drive operational efficiency or improve the customer experience. Hundreds of our customers are already using ServiceBot to generate new customers 24 hours a day, 7 days a week." WorkWave CEO David F. Giannetto ServiceBot shows the power of WorkWave's business model, and its recent expansion to lead multiple industries, by bringing its greater resources to bear, helping Lawnbot to evolve into ServiceBot which can now support any home service business. ServiceBot automates the sales process and allows consumers to purchase, schedule and pay for service visits right on their website, through AI-driven, human-like interactions. ServiceBot is seamlessly integrated into WorkWave's industry-leading platforms including Real Green SA5 and is currently being integrated into PestPac, with ServMan and WinTeam soon to come. With ServiceBot, customers can offer service to potential customers at any moment. As a mobile device-friendly, 24-hour, one-stop-shop sales automation tool, ServiceBot is able to sell to customers wherever they are, at any time. About WorkWave For nearly 40 years, WorkWave has been building best practices into its market-leading field service and last mile software solutions to allow best-in-class companies to grow their business, service their customers and maximize their money. Its solutions empower service-oriented companies to reach their full potential through scalable, cloud-based software solutions that support every stage of a business life cycle, including marketing, sales, service delivery, customer interaction and financial transactions. WorkWave is a trusted partner for thousands of customers across a wide variety of industries, including pest control, lawn care, cleaning, HVAC, plumbing and electrical, and last mile delivery. WorkWave's award-winning culture and solutions have been recognized in the SaaS Awards, the Cloud Awards, the American Business Awards, the NJBIZ Best Places to Work Awards, and the Stevie Awards for Great Employers.

Read More

AI TECH

Inspur Information's AIStation Works With NVIDIA AI Enterprise Software Suite to Power Innovation

Inspur Information | August 03, 2022

Inspur Information, a leading IT infrastructure solutions provider, is combining AIStation, its unified management and scheduling AI computing resource platform, with NVIDIA AI Enterprise, a cloud-native suite of AI and data analytics software, to provide enterprise users with a convenient and efficient platform for utilizing AI computing resources. This includes professional development, advanced deployment tools, and state-of-the-art components. The combined platform allows enterprises to quickly implement the industry's most advanced AI capabilities and rapidly deploy AI applications to drive intelligent business innovation. There have been multiple attempts to build AI resource stacks for improving AI innovation and implementation. However, implementing AI technologies is a very challenging task. Enterprises not only need to meet requirements for computing power, but also maximize their computing resource utilization, quickly build and manage AI deployment environments, and efficiently introduce AI capabilities. It requires an AI platform that supports agile development and necessitates easy management and deployment to quickly implement AI applications and accelerate their performance. Inspur Information's AIStation is an end-to-end platform that provides one-stop support for AI development and deployment. With powerful resource scheduling and management capabilities, it accelerates the development and deployment of AI technologies. NVIDIA AI Enterprise is an optimized end-to-end, cloud-native AI and data analytics software suite. It supports the processes from environment construction, data processing, training, and inference to allow for faster development and implementation of AI technologies. AIStation's superior scheduling, management and monitoring capabilities are able to fully unleash NVIDIA AI Enterprise's excellent AI development and deployment capabilities. The combined solution expertly handles data storage, computing power and task scheduling, cluster operation and maintenance, and provides enterprises with an agile and easy-to-use AI platform that can fully utilize their AI computing resources. It also enhances the development and deployment of AI-related tools and components. Resulting AI development and deployment is markedly sped up, making AI transformation more efficient, and improving the business value of AI. Detailed benefits of the combined Inspur Information and NVIDIA AI Enterprise solution include: Maximizing computing resources The solution makes it easier for enterprise customers to use and manage hardware infrastructure including NVIDIA GPUs, and supports Multi-Instance GPU features in the NVIDIA Ampere architecture, enabling users to centrally allocate and monitor computing resources and efficiently allocate those computing resources in large-scale computing power clusters. Acquiring AI capabilities quickly The cloud-native environment management mechanism based on Docker containers gives users an effort-free experience for building cloud-native development environments. Thanks to the powerful scheduling and management capabilities of Inspur Information's AIStation and the professional frameworks, models, applications and development tools of NVIDIA AI Enterprise, users can build AI environments and run AI tasks with ease to achieve fast delivery and quickly introduce advanced AI capabilities. Managing AI infrastructure with ease The multi-tenant management policy allows cluster administrators to focus on managing hardware infrastructure and controlling user quotas. Users can manage AI services and perform AI production within quota limits, and developers can quickly obtain AI compute resources without needing to be audited by administrators often. In addition, administrators can monitor key services and performance of the platform in real-time, and improve system availability by leveraging the fault-tolerant mechanisms and high-availability architecture. Today, AI technologies are changing various industries such as finance, transportation, medical care, education, and scientific research. By introducing AI technologies and applications, enterprises can boost their business capabilities and create greater value. Inspur Information is working closely with NVIDIA to promote the construction of intelligent computing infrastructure and develop AI capability stacks to further accelerate enterprises' AI strategies and AI transformation. Inspur Information and NVIDIA have a longstanding collaboration, with Inspur AI servers supporting the full lineup of NVIDIA GPUs, including the NVIDIA A100, A30, A10, and A2. Inspur AI servers were among the first in the industry to fully support NVIDIA Ampere architecture-based GPUs and the company has obtained NVIDIA-Certified System status for its AI servers. About Inspur Information Inspur Information is a leading provider of data center infrastructure, cloud computing, and AI solutions. It is the world’s 2nd largest server manufacturer. Through engineering and innovation, Inspur Information delivers cutting-edge computing hardware design and extensive product offerings to address important technology sectors such as open computing, cloud data center, AI, and deep learning. Performance-optimized and purpose-built, our world-class solutions empower customers to tackle specific workloads and real-world challenges.

Read More

FUTURE TECH

Vendr Launches 2.0, The Most Complete SaaS Buying Platform on The Market

Vendr | August 10, 2022

Vendr, the world’s first SaaS buying platform, today announced the launch of Vendr 2.0, the most complete SaaS buying platform on the market. SaaS is a top-three line item expense, but most companies aren’t getting the appropriate return on their software investment. Vendr 2.0 harnesses Vendr’s SaaS purchasing and SaaS management products, combining the power of seasoned negotiators armed with insights from over 13,000 deals alongside robust software featuring an integrated system of record. Now, enterprise customers will be equipped with an unprecedented level of visibility into which software their teams are buying and using — in one central location. This enables leaders to reduce overspend and eliminate duplicative products. Most importantly, it unlocks insights that lead to better software choices and faster procurement at lower prices. The launch comes on the heels of the company’s recent ​​$150MM Series B, co-led by return investor Craft Ventures and new investor SoftBank Vision Fund 2––which brought the company into Unicorn status––and its acquisition of SaaS management company Blissfully earlier this year. “The software purchasing process is broken and becoming all the more cumbersome as companies everywhere work to cut costs, as they seek to do more with less. “The introduction of Vendr 2.0 enables organizations to manage their second-highest expense––software––more effectively than ever before, while reducing the difficulties surrounding the process. Vendr 2.0 aims to be the most complete, no-brainer, SaaS buying platform on the market –– and one that pays for itself.” Ryan Neu, Vendr CEO and co-founder The standard buying process historically wastes time and resources for both software vendors and customers. Vendr enables businesses to maximize the return on their SaaS investments through cost savings and more efficient spend, improving stack visibility across the organization. Composed of the best industry data of more than 2,000 SaaS suppliers, Vendr 2.0 is facilitating critical transformation in how organizations purchase and manage software. Tapping Into Transparency Software buying is a perpetual process and it no longer makes sense to have buying and supplier lifecycle management exist in disparate places. By bringing everything into one place, companies layer the benefits of an expert service team and deep SaaS insights into an integrated system of record that offers unparalleled visibility into their stack. Using Vendr, customers can take a proactive approach to their SaaS spend, equipping their teams with the best software while saving money. Buyer <-> supplier: Vendr offers insights and negotiation support to help buyers and sellers quickly evaluate whether a deal is fair for both sides, ensuring that the process continues moving along internally once it comes time to buy. Buyer <-> procurement function: Vendr provides visibility into internal approval workflows and offers fast-tracked ways to request purchases, leading to smoother relationships between buyers and their company procurement functions. Finance/procurement <-> department heads: With better visibility and faster purchase cycles, stakeholders can easily see the value-add of finance and procurement, ensuring compliance and keeping a handle on costs, leading to better business outcomes for all. This new platform builds upon the competitive advantages that Vendr has in the market as the category creator with the deepest source of supplier insight––based on thousands of deals––as well as the most seasoned negotiators in the industry. Vendr has processed over $1.5B in customer software spend and delivered over $240M in software savings to its customers. To see how much you could be saving on your annual software expense, get in touch here. About Vendr Vendr is changing how companies find, buy and manage SaaS. The first of its kind, Vendr's SaaS buying platform offers both a product and people-powered service to enable the world's fastest-growing companies to purchase software quickly and with guaranteed savings. Today, Vendr has facilitated over $1.5B+ in SaaS purchases across 2,500+ suppliers for Finance and Procurement teams at HubSpot, Brex, Canva, Reddit, Toast, and more. Headquartered in Boston with a second location in Charleston, Vendr was founded in 2019 by Ryan Neu and co-founders Ariel Diaz and Aaron White, who joined the team through the acquisition of Blissfully in 2022. The company has over 250 employees globally

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