 Knowledge Graph With ChatGPT Apr 3rd 2023, 14:54, by ganesh s GPT fascinates. I was keen to evaluate my fascination firsthand. This is an extension of some custom code I had written to convert natural language into a "meaningful" representation in a graph but with relatively simple text, which was about the use of natural plants for the treatment of common ailments. To set some context, I did my share of nltk/ NLP learning when I labored and converted the contents of a book to a graph took more than a few weekends and loads of stackoverflow/d3.js threads to fix my errors and clean up code. With that experience, I set out this evening to 'test drive' the GPT engine. I took up two relatively simple use cases, with one being an attempt at summarizing the NIST 800 sp 53 control catalog in a simple graph, while the other was relatively more human imagination-driven, with me wanting to narrate a simple story of the "boy who cried wolf" using Neo4j. |  Low Code Approach for Building a Serverless REST API Apr 3rd 2023, 14:31, by Rohini Arun kumar Building REST-based services is pretty common when it comes to the backend world. When it comes to developing the service in a serverless world, it's a trend, but it comes with a lot of pain. For instance, we need to write a function in the language of our choice, then need to build a provisioning script like cloud formation or terraform to chain the set of services used for building the solution. In this article, we will be building a REST-based service on AWS lambda, API gateway, and PostgreSQL database. The key part is that we will be developing it completely using a low code integration tooling and runtime framework, Kumologica. |  Creating Scalable OpenAI GPT Applications in Java Apr 3rd 2023, 14:03, by Denis Magda One of the more notable aspects of ChatGPT is its engine, which not only powers the web-based chatbot but can also be integrated into your Java applications. Whether you prefer reading or watching, let's review how to start using the OpenAI GPT engine in your Java projects in a scalable way, by sending prompts to the engine only when necessary: |  A Developer's Dilemma: Flutter vs. React Native Apr 3rd 2023, 12:39, by Uday Pitambare A few years ago, if you or your team decided to develop a mobile app for both iOS and Android, you would be required to maintain two codebases, one for each platform. This meant either learning or hiring developers well-versed in Swift and/or Objective-C(for iOS) and Kotlin and/or Java(for Android), the primary programming languages used to build native apps for these platforms. As you can imagine, this not only puts a strain on your resources and budget allocation but also involves longer development cycles and painstaking efforts to ensure consistency between both apps. With the advent of cross-platform app development frameworks in the last few years, mobile app developers and companies are increasingly moving or at least considering using these technologies to build their mobile apps. The primary reason is that these frameworks enable developers to write code only once and build for both Android and iOS. Maintaining a single codebase significantly reduces your time-to-launch and ensures a high level of consistency between both apps. We will discuss in detail in a bit how this is made possible by React Native and Flutter, which are the two most popular cross-platform mobile app development frameworks at the moment. React Native is a Facebook(Now Meta) project and was released publicly about two years before Google released the initial version of Flutter in 2017. Before the emergence of these two frameworks, there were a few other options for developers, like Xamarin, Cordova, and Ionic, but they have since fallen out of favor because of many complexity and performance issues. There is a relatively recent effort by the JetBrains team(the company that built some of the popular IDEs) called Kotlin Multiplatform mobile. However, it is still in Beta and not as popular as React Native or Flutter. |  Understanding AVL Trees in C#: A Guide to Self-Balancing Binary Search Trees Apr 3rd 2023, 11:37, by Denis Kondratev In my previous article, we discussed the binary search tree and its implementation in C#. We learned that this data structure allows for fast searching, insertion, and deletion of elements in logarithmic time. Still, if the tree is not balanced properly, its performance can suffer greatly. We also noted that there is a more advanced tree called AVL with self-balancing, which guarantees logarithmic time complexity for all operations, regardless of the incoming data. In this article, we will continue our exploration of binary search trees by diving deeper into AVL Trees. We will discuss their structure, properties, and implementation details and compare them to other self-balancing trees. We will also provide examples of AVL Trees in action and demonstrate how they solve the problem of unbalanced trees. By the end of this article, you will have a solid understanding of AVL Trees and be equipped with the knowledge to use them effectively in your own code. | |
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