If you’re skilled in using ChatGPT or other language models to generate content, you may be wondering how you can turn that expertise into a source of income. There are many potential ways to make money using ChatGPT, depending on your interests and skills. In this blog post, we’ll outline five creative ways to monetize your ChatGPT skills and turn your passion for language models into a successful business or freelance career. 1. Content creation: ChatGPT can be used to generate unique, high-quality content for websites and blogs. You can then sell this content to clients or publish it on your own website and monetize it through advertising or affiliate marketing. One way to make money using ChatGPT for content creation is to identify a specific niche in that you have knowledge and interest. This could be a particular industry, topic, or style of writing. Having a clear focus will make it easier for you to generate relevant and accurate content and find potential clients. Once you’ve identified your niche, you’ll want to set up a website or blog to showcase your writing skills and promote your content creation services. You can use this platform to publish the content you generate with ChatGPT and monetize it through advertising or affiliate marketing. To improve the quality of the content generated by ChatGPT, it’s essential to train the language model on a large dataset of high-quality content related to your niche. This will help ChatGPT understand the language and style of your place and generate more relevant and accurate content. Once you’ve trained ChatGPT, you can start generating content on various topics within your niche. You can then use this content to pitch to clients or publish it on your own website. To market your content creation services, you can use social media, online job boards, and freelance marketplaces to find clients and build your portfolio. Remember to properly attribute any content generated by ChatGPT and to make sure you have the rights to use and sell the content. 2. Social media management: ChatGPT can be used to generate social media posts and engage with followers. You can offer this service to businesses or individuals looking to outsource their social media management. To make money using ChatGPT for social media management, you’ll want to identify a specific niche in which you have knowledge and interest. This could be a particular industry, topic, or type of social media platform. Next, set up a website or portfolio to showcase your social media management skills and promote your services. You can include examples of the content generated with ChatGPT and any relevant experience or qualifications. To improve the quality of the content generated by ChatGPT, it’s essential to train the language model on a large dataset of high-quality social media posts related to your niche. This will help ChatGPT understand the language and style of your place and generate more relevant and accurate content. Once you’ve trained ChatGPT, you can use it to generate unique, high-quality social media posts on various topics within your niche. You can then use these posts to engage with followers and build a following on social media. To market your social media management services, you can use social media, online job boards, and freelance marketplaces to find clients and build your portfolio. Remember to properly attribute any content generated by ChatGPT and to make sure you have the rights to use and sell the content. 3. E-commerce product descriptions: ChatGPT can be used to write compelling product descriptions for e-commerce websites. This can save businesses time and improve the quality of their product listings. To make money using ChatGPT for e-commerce product descriptions, you’ll want to identify a specific product category or industry that you have knowledge and interest in. This will make it easier for you to generate relevant and accurate product descriptions and find potential clients. Next, set up a website or portfolio to showcase your writing skills and promote your e-commerce product description services. You can include examples of descriptions generated with ChatGPT and any relevant experience or qualifications. To improve the quality of the product descriptions generated by ChatGPT, it’s essential to train the language model on a large dataset of high-quality product descriptions related to your niche. This will help ChatGPT understand the language and style of your place and generate more relevant and accurate descriptions. Once you’ve trained ChatGPT, you can use it to generate unique, high-quality product descriptions for various products within your niche. You can then use these descriptions to pitch to e-commerce businesses or publish them on your own website. To market your e-commerce product description services, you can use social media, online job boards, and freelance marketplaces to find clients and build your portfolio. Remember to properly attribute any content generated by ChatGPT and to make sure you have the rights to use and sell the content. 4. News articles: ChatGPT can be used to write news articles and summaries, which can be sold to news outlets or published on your own website and monetized through advertising or subscriptions. To make money using ChatGPT for news articles, you’ll want to identify a specific topic or industry that you have knowledge and interest in. This could be a particular type of news, such as business, politics, or entertainment. Next, set up a website or blog to showcase your writing skills and promote your news writing services. You can include examples of articles generated with ChatGPT and any relevant experience or qualifications. To improve the quality of the articles generated by ChatGPT, it’s important to train the language model on a large dataset of high-quality news articles related to your niche. This will help ChatGPT understand the language and style of your niche and generate more relevant and accurate articles. Once you’ve trained ChatGPT, you can use it to generate unique, high-quality news articles on a variety of topics within your niche. You can then sell these articles to news outlets
Hosting a static website on Azure has never been easier thanks to the preview release of Azure Static Web App. In this tutorial, we will walk you through the steps to set up and deploy your first static web app on Azure. Before we get started, there are a few prerequisites you need to install on your local machine: If you don’t have a GitHub account yet, now is a good time to create one. You will need it to connect your static web app to a GitHub repository. Now that you have the prerequisites installed, let’s start setting up your static web app on Azure. Once your static web app is created, you can connect it to a GitHub repository and configure the build and deployment options. Now it’s time to publish your static website. Simply commit and push your static website files to the selected repository and branch, and Azure will automatically detect the changes and start building and deploying your static website. Once the deployment is complete, you can access your static website at the URL provided in the Azure portal. You can also customize the URL by setting up a custom domain or using your own subdomain. That’s it! You now have a fully functional static website hosted on Azure. If you encounter any issues or have any questions, don’t hesitate to ask for help. Happy coding! You may also like to see: Laravel Tips & Tricks for Carbon and Time and How to Build real-time applications with Node.js and WebSockets? If you like this post let us know what would you want us to post next in the comment section also help this post reach more and more people via our social media accounts on Instagram, Facebook, Twitter, and LinkedIn.
The MySQL Blackhole storage engine is a unique engine that does not store any data. Instead, it discards any data that is inserted into it and always returns an empty result set for SELECT queries. So why would anyone use it? The Blackhole engine can be useful in a few specific situations. For example, you might use it to capture and discard slow query log data, or to route certain types of queries to a separate server or application. It can also be used as a placeholder for a real storage engine, or as a way to “blackhole” or discard certain types of data. However, it’s important to note that the Blackhole engine is not a general-purpose storage engine and should not be used as the primary storage engine for your data. It is designed for specific use cases where data does not need to be stored, and its limited functionality makes it unsuitable for most applications. Creating a Blackhole-Engine Table To use the Blackhole engine, you must create a Blackhole engine table in your MySQL database. You can do this using the CREATE TABLE statement, with the ENGINE option set to BLACKHOLE: Once you have created a Blackhole-engine table, you can use it just like any other table in MySQL. However, any data you insert into it will be discarded, and SELECT queries will always return an empty result set. Use Cases for the Blackhole Engine Here are a few potential use cases for the MySQL Blackhole storage engine: You may also like: What’s New in Ruby 3.2.0 & Discover the Future of Search with ChatGPT and BingIf you like this post then you may also like to share the same with your colleagues. Let us know your thoughts on our blogs and on social media posts on Instagram, Facebook, LinkedIn, and Twitter.
ChatGPT is a natural language processing (NLP) model developed by OpenAI that can be used to build chatbots and other conversational AI applications. In this blog post, we will show you how to use ChatGPT to build a simple search engine that allows users to search the web using Bing. To get started, you will need to sign up for a Bing Web Search API key. You can do this by visiting the Microsoft Azure portal and creating a new Cognitive Services API key. You can sign up for a ChatGPT account at https://www.chatgpt.com/ and obtain a Bing Search API key by following the instructions at https://docs.microsoft.com/en-us/azure/cognitive-services/bing-web-search/getting-started. Once you have your API key, you will need to install the azure-cognitiveservices-search-websearch package using pip: Next, you will need to install ChatGPT and its dependencies. You can do this by running the following command: Now, you are ready to start using ChatGPT to build your search engine. Here is some sample code that shows you how to use the Bing Web Search API to search the web and return the results to the user: To use ChatGPT to build your search engine, you will need to create a function that takes the user’s query and passes it to the search function. You can then use ChatGPT to generate a response based on the search results. Here is an example of how you might do this: or you can use the following code to search the web with Bing and ChatGPT: With this code, you can use ChatGPT to generate a response to the user’s query and use the Bing Search API to search the web for the information the user is looking for. You can then return the top 10 search results to the user as a list of links. You may also like: What’s New in Ruby 3.2.0 If you like this post then you may also like to share the same with your colleagues. Let us know your thoughts on our blogs and on social media posts on Instagram, Facebook, LinkedIn, and Twitter.
Ruby 3.2.0 Is From Another Dimension — and it shows! This version of Ruby is packed with amazing features and upgrades that make it even faster, stronger, and more versatile than ever before. Highlights include improved memory usage, better parallelization, updated Google V8 JavaScript engine support, language-level JIT compiler, and improved threading efficiency. All these combined improvements have taken this powerful programming language to the next level! Enhanced JIT compiler Enhanced type inference Pattern matching Pattern matching is a powerful and flexible way to match data structures and extract values from them. It is a feature that is commonly found in functional programming languages, and it is now available in Ruby 3.2.0. One of the main benefits of pattern matching is that it allows you to write concise and expressive code, especially when working with complex data structures. For example, consider the following code, which uses pattern matching to extract the first and last names from a list of people: This code will output the first and last names of each person in the list, separated by a space. Notice how pattern matching allows us to easily extract the values we want without having to use explicit variable assignments or restructuring. Frozen string literals Other Improvements Ruby 3.2.0 includes a number of other improvements in addition to the major features discussed above. Here are a few of the other notable improvements in Ruby 3.2.0: If you like this post then you may also like to share the same with your colleagues. Let us know your thoughts on our blogs and on social media posts on Instagram, Facebook, LinkedIn, and Twitter. You may also like to see: Agile and Waterfall: Comparing Two Popular Approaches to Software Development
Agile and Waterfall!! When it comes to software development, there are many different approaches and methodologies that teams can use to plan, design, and build software products. Two of the most popular methodologies are Agile and Waterfall. Agile and Waterfall Agile is a flexible, iterative approach to software development that emphasizes adaptability and the ability to quickly respond to change. Agile methodologies, such as Scrum and Extreme Programming, focus on delivering small increments of working software regularly and involve close collaboration between the development team and the customer. Waterfall, on the other hand, is a more structured and linear approach to software development. In the Waterfall model, development is broken down into distinct phases, and progress flows in one direction, like a waterfall. The Waterfall model is often associated with more traditional, large-scale software development projects, and is known for its predictability and clear roles and responsibilities. In this blog, we’ll delve into the key differences between Agile and Waterfall, and explore the pros and cons of each approach. We’ll also discuss when it might be appropriate to use one approach over the other, and how Agile and Waterfall can be combined or adapted to fit the needs of a specific project or team. Agile software development: Agile is a set of values and principles for software development outlined in the Agile Manifesto. The Agile Manifesto emphasizes the following values: These values are reflected in various Agile methodologies, such as Scrum, Lean, and Extreme Programming. Scrum is a popular Agile methodology that is widely used in software development and other fields. It is based on the idea of “sprints,” or short, focused periods of work during which a specific set of tasks is completed. At the end of each sprint, the team demonstrates the working software they have produced and adjusts their plan for the next sprint based on feedback from the customer. Lean is another Agile methodology that is based on the principles of the Toyota Production System. It emphasizes continuous improvement, waste reduction, and the delivery of value to the customer. Extreme Programming (XP) is an Agile methodology that is focused on delivering high-quality software through collaboration, communication, and frequent feedback. It involves practices such as pair programming, in which two developers work together on the same piece of code, and continuous integration, in which code is regularly integrated and tested to identify and fix issues early on. Pros of using Agile: 👍 There are several benefits to using an Agile approach to software development: Cons of using Agile: 👎 There are also some potential drawbacks to using an Agile approach: Waterfall software development: The Waterfall model is a traditional, linear approach to software development. It is based on the idea of completing one phase of the project before moving on to the next. The phases of the Waterfall model typically include: In the Waterfall model, progress flows in one direction, like a waterfall, and there is little overlap between the phases. This can make it more difficult to go back and make changes once a phase has been completed. Pros of using Waterfall: 👍 Cons of using Waterfall: 👎 When to use Agile or Waterfall: There is no one-size-fits-all approach to software development, and the right methodology will depend on the specific needs and constraints of the project. Some factors to consider when deciding between Agile and Waterfall include: Hire a team of experts: https://precisedevelopers.com/hire-mern-stack-developer/ If you like this post let us know what would you want us to post next in the comment section also help this post reach more and more people via our social media accounts on Instagram, Facebook, Twitter, and LinkedIn.
Welcome to our blog on the software development process! In this post, we’ll be taking a high-level look at the steps that are typically followed when creating a software product. Whether you’re a software developer or just interested in the field, understanding the software development process can be helpful in understanding how software is created and how it evolves over time. The software development process is the series of steps that a team follows to create a software product. While every organization has its own specific process, there are some common stages that are followed in most software development projects. These stages include planning, design, testing, and deployment. Planning: This is the first stage of the software development process, where the project goals and objectives are defined. The team works with the client to gather requirements and define the scope of the project. A project plan is created that outlines the timeline, budget, and resources needed for the project. Design: In this stage, the team works on designing the architecture and user interface of the software. They create wireframes and prototypes to visualize how the software will look and function. The design stage also includes developing a database schema and choosing the technologies that will be used to build the software. Testing: Once the software has been developed, it goes through a thorough testing process to ensure that it is free of bugs and defects. There are different types of testing that can be performed, including unit testing, integration testing, and acceptance testing. The goal of testing is to identify and fix any issues before the software is released to the public. Deployment: After the software has been thoroughly tested and any issues have been resolved, it is ready to be deployed. This typically involves installing the software on servers or hosting it in the cloud and then making it available to users. The deployment process may also include creating documentation and providing training to users on how to use the software. This is just a high-level overview of the software development process. There are many other tasks and activities that may be involved depending on the specific project and team. However, these four stages – planning, design, testing, and deployment – are common to most software development projects. You may also like to see: Laravel Tips & Tricks for Carbon and Time and How to Build real-time applications with Node.js and WebSockets? Here are Live examples to illustrate each stage of the software development process: Planning: Design: Testing: Deployment: I hope these examples help to illustrate the stages of the software development process. Keep in mind that these are just a few examples and the specific tasks and activities involved in each stage can vary greatly depending on the project and team. If you like this post let us know what would you want us to post next in the comment section also help this post reach more and more people via our social media accounts on Instagram, Facebook, Twitter, and LinkedIn.
In the past few years, we have seen an explosion in the use and adoption of blockchain technology. But what exactly is blockchain and why is it causing such a stir? A blockchain is distributed across a network of computers which means that it allows for increased security and transparency as each transaction is verified by multiple computers on the network. This means that the record cannot be altered retroactively without the alteration of all subsequent blocks and the consensus of the network. In other words, it is a secure and transparent way to store and transfer data and value. One of the key advantages of blockchain technology is that it allows for secure peer-to-peer transactions without the need for a central authority or third-party intermediary. This has the potential to disrupt and revolutionize a wide range of industries, including finance, banking, and supply chain management. In addition to its other features, blockchain also has the ability to facilitate smart contracts. These are self-executing contracts in which the terms of the agreement between buyer and seller are written directly into lines of code. This has the potential to streamline and automate many business processes, reducing the risk of fraud and increasing efficiency. The rise of blockchain technology has the potential to significantly change the way we do business and interact with each other. As more and more people become aware of and adopt blockchain, it is likely to play an increasingly important role in shaping the future of the global economy. If you like this post and found it informational then follow us on our social media accounts on Instagram, Facebook, LinkedIn, and Twitter and share your experience with us and your colleagues. You may also like to see: OpenAI new and improved embedding model
Laravel Tips Carbon is a popular PHP library for working with dates and times in PHP. It provides a simple and intuitive interface for various operations on dates and times, such as calculating differences between dates, adding or subtracting time units from dates, and formatting dates for display. Laravel, one of the most popular PHP web development frameworks, includes Carbon as a dependency, making it easy to use Carbon in your Laravel applications. 2. Use the now method to get the current date and time: 3. Use the parse method to create a Carbon instance from a string: 4. Use the createFromFormat method to create a Carbon instance from a custom date format: 5. Use the diffInDays, diffInWeeks, diffInMonths, and diffInYears methods to get the difference between two dates in various units of time: 6. Use the addDays, addWeeks, addMonths, and addYears methods to add or subtract a specific unit of time from a date: Follow our Trending Instagram Page for Laravel Tips with 8K+ Followers: https://www.instagram.com/laravel.tips In conclusion, Carbon is a valuable tool for working with dates and times in your Laravel applications. Its simple and intuitive interface makes it easy to perform various operations on dates and times, such as calculating differences, adding or subtracting time units, and formatting dates for display. Using Carbon in your Laravel app, you can quickly and easily manage and manipulate dates and times, helping you build robust and efficient applications. You may also like: Getting Started with Laravel Sanctum: A Guide to Building Secure Applications & What are the new features in laravel 10? If you like this post let us know what would you want us to post next in the comment section also help this post reach more and more people via our social media accounts on Instagram, Facebook, Twitter, and LinkedIn.
OpenAI has announced a new embedding model which is more capable, cost-effective, and simpler to use than its previous model. The new model, text-embedding-ada-002, replaces five separate models for text search, text similarity, and code search, and outperforms Davinci, their previous most capable model, at most tasks. The new model is priced 99.8% lower than Davinci. Since the inception of the OpenAI /embeddings endpoint, many applications have started to use numerical representations of concepts, known as embeddings, to personalize, recommend, and search for content. Embeddings make it easy for computers to understand relationships between different concepts, which has led to their widespread use in a variety of applications. You can get embeddings for the new model using just two lines of code with the OpenAI Python Library, just like you could with previous models: Model Improvements 1) Stronger performance text-embedding-ada-002 outperforms all the old embedding models on text search, code search, and sentence similarity tasks. It also gets comparable performance on text classification. For each task category, OpenAI evaluates the models on the datasets used in old embeddings. 2) Unification of capabilities OpenAI has merged five separate models (text-similarity, text-search-query, text-search-doc, code-search-text, and code-search-code) into a single new model, making the /embeddings endpoint much simpler to use. This new model outperforms the previous embedding models on a variety of text search, sentence similarity, and code search benchmarks. 3) Longer context The new model has a context length of 8192, which is four times longer than the previous model. This makes it more convenient to work with long documents. 4) Smaller embedding size The new embeddings have 1536 dimensions, which is one-eighth the size of davinci-001 embeddings. This makes the new embeddings more cost-effective when working with vector databases. 5) Reduced price OpenAI has slashed the price of its new embedding models by a whopping 90% in comparison to its old models of the same size. The new model performs just as well, if not better, than the old Davinci models but at less than one percent of the price. The new embedding model is a big step forward for natural language processing and code tasks. It’ll be exciting to see how customers use it to create even more powerful applications in their respective fields. Limitations The new text-embedding-ada-002 model isn’t outperforming text-similarity-davinci-001 on the SentEval linear probing classification benchmark. If you need to train a light-weighted linear layer on top of embedding vectors for classification prediction, they suggest comparing the new model to text-similarity-davinci-001 and choosing whichever model gives optimal performance. Examples of Embeddings APIs KelendarAI It’s a sales outreach product that uses embeddings to match the right sales pitch to the right customers. It does this by looking at customer profiles and sale pitches and then finding the most suitable matches. This process can eliminate 40-56% of unwanted targeting. Notion It’s an online workspace company, that will use OpenAI’s new word embeddings to improve Notion search beyond today’s keyword matching systems. This will help users find the right Notion workspace for their needs more easily and quickly. If you like this post let us know what would you want us to post next in the comment section also help this post reach more and more people via our social media accounts on Instagram, Facebook, Twitter, and LinkedIn. You also like to see: Getting Started with Laravel Sanctum: A Guide to Building Secure Applications
Real-time applications are web-based applications that allow for bidirectional communication between the client and the server. This means that the server can send data to the client in real-time, and the client can also send data to the server in real-time. Real-time applications are useful for a variety of purposes, such as online chat applications, real-time collaboration tools, and live updates on social media or news websites. One way to build real-time applications is by using Node.js and WebSockets. Node.js is a popular open-source JavaScript runtime environment that is designed for building scalable network applications. It uses an event-driven, non-blocking I/O model, which makes it well-suited for real-time applications that require high performance and low latency. WebSockets is a protocol that allows for full-duplex communication over a single TCP connection. This means that both the client and the server can send data to each other simultaneously, without the need for HTTP requests and responses. WebSockets are useful for building real-time applications because they allow for efficient communication between the client and the server, with low latency and minimal overhead. To get started with building a real-time application using Node.js and WebSockets, you’ll need to set up a Node.js server. You can do this by installing Node.js on your machine and creating a primary server using the http module. Once you have a Node.js server up and running, you’ll need to install the ws module, which is a WebSockets module for Node.js. To establish a WebSocket connection, you’ll need to create a WebSocket server on the Node.js side and a WebSocket client on the client side. On the Node.js side, you can create a WebSocket server using the ws a module like this: const WebSocket = require(‘ws’); const wss = new WebSocket.Server({ port: 8080 }); On the client side, you can create a WebSocket client using JavaScript like this: const socket = new WebSocket(‘ws://localhost:8080’); Once you have a WebSocket connection established, you can send and receive data in real-time using the send and onmessage methods. On the Node.js side, you can use the send method to send data to the client like this: wss.on(‘connection’, function connection(ws) { ws.send(‘Hello, client!’); }); On the client side, you can use the onmessage event to receive data from the server like this: You may also like: Laravel vs Codeigniter, Which is the best in 2023? socket.onmessage = function(event) { console.log(event.data); } There are many different types of real-time applications that you can build using Node.js and WebSockets. Some examples include online chat applications, real-time collaboration tools, and live updates on social media or news websites. When building a real-time application using Node.js and WebSockets, it’s important to consider performance, error handling, and security. To optimize performance, you may consider using a load balancer to distribute incoming connections across multiple servers and a tool like PM2 to manage your Node.js processes. Here are Best 10 Tips Best practices for remote work and maintaining productivity
Laravel Sanctum is a lightweight authentication system for single-page applications, mobile applications, and traditional web applications. It provides a simple and seamless authentication experience for developers and users alike, making it easy to build modern and secure applications with Laravel. Here are some key features of Laravel Sanctum: Let’s see it in detail One of the key features of Sanctum is its ability to authenticate multiple devices for a single user. This means that a user can be logged in on multiple devices simultaneously, and each device will have its own unique access token. This is particularly useful for applications where the user may need to switch between devices, such as a mobile application and a web application. In addition to supporting multiple devices, Sanctum also makes it easy to authenticate external services and APIs. This is useful for applications that need to authenticate third-party services, such as a backend service or an external API. To use Sanctum, you’ll need to install the Laravel framework on your server and configure your application to use the Sanctum package. This process is relatively straightforward, and the Laravel documentation provides detailed instructions on how to set up Sanctum for your application. Once you have Sanctum installed and configured, you’ll need to create routes and controllers for your authentication flows. This will typically involve creating routes for logging in, logging out, and retrieving the authenticated user’s information. You can also use Sanctum to handle password resets and other authentication-related tasks. One of the benefits of using Sanctum is its integration with Laravel’s built-in authentication system. This means that you can use Sanctum to handle your application’s authentication flows, while still taking advantage of Laravel’s built-in features, such as user roles and permissions. Overall, Laravel Sanctum is a powerful and easy-to-use tool for building modern, secure, and scalable authentication systems. Whether you’re building a single-page application, a mobile application, or a traditional web application, Sanctum is an excellent choice for managing your application’s authentication flows. You may also like What are the new features in laravel 10? If you like this post then you may also like to share the same with your colleagues. Let us know your thoughts on our blogs and on social media posts on Instagram, Facebook, LinkedIn, and Twitter.