Monday 16 September 2024

Use Cases of ChatGPT in Real Life

 

 In recent days, ChatGPT and its applications have been trending all over the internet. In this article, I have summarized some of the interesting applications of ChatGPT. The common application of ChatGPT is it can be used in chat-bots which benefits a lot of industries like Banking, Ed-tech, fin-tech, and Health. The other main application stated on the website is the interaction with ChatGPT is conversational ie., the response given by ChatGPT is similar to a response you receive from a human.


What is ChatGPT

ChatGPT is a large language model OpenAI developed and designed to understand and generate human-like text. As a cutting-edge AI system, it is transforming industries with remarkable abilities to improve communication and customer service and automate various tasks.

ChatGPT is trained on a massive amount of data, including books, websites, and other text sources, which allows it to have a vast knowledge base and to understand a wide range of topics. It can also generate new text on its own, using its understanding of language and its training data to produce responses that are often creative and insightful.


Understanding ChatGPT

ChatGPT is an advanced language model that can generate contextually relevant responses. It has been trained on vast amounts of text data and can provide human-like conversation, which makes it an excellent resource for industries that require efficient and effective communication


Is ChatGPT free?


Yes, chat GPT is free to use. However, a paid version of Chat GPT has also been launched by OpenAI in the US. The paid version of chat GPT is termed ChatGPT Plus. People who wish to use the paid version of Chat GPT can use it by paying USD 20 per month. While people who do not intend to pay the price of using it can use the free version of the app. 


How Can You Access ChatGPT?

ChatGPT can be accessed on your mobile browser or computer/laptop. Using ChatGPT is very easy. To know how to use chatGPT, follow the steps mentioned below: 

Step 1: Visit https://chat.openai.com/auth/login to get started. 

Step 2: Sign up on this website by entering your full name. 

Step 3: Verify your account through a code sent to your mobile phone or email id. 

Step 4: Once the verification is completed from your end, you can begin using it. 


ChatGPT, also known as GPT-3, is a powerful language model developed by OpenAI. Some of the advantages of using ChatGPT include:


  1. Natural Language Understanding: ChatGPT is trained on a large dataset of human language, making it capable of understanding natural language inputs and providing human-like responses.

  2. Flexibility: ChatGPT can be used for a wide range of natural language processing tasks, such as language translation, text summarization, text completion, and question-answering.

  3. High Accuracy: ChatGPT has been trained on a large dataset and has been fine-tuned to provide high accuracy in different language tasks.

  4. Language Generation: ChatGPT can generate human-like text based on a given prompt. It can be used to generate creative writing, news articles, chatbot responses, and more.

  5. Low-code/No-code: ChatGPT can be integrated with different applications, platforms and services with minimal or no coding experience. It can be used to build conversational AI, chatbots, and other NLP applications.

  6. Cost-effective: Using a pre-trained model like ChatGPT can be a cost-effective solution for businesses, as it eliminates the need to train a model from scratch and the associated costs.

  7. Scalability: ChatGPT can handle large volumes of text data and can scale to meet the demands of a wide range of use cases.

  8. Fast deployment: With pre-trained models like ChatGPT, deployment is faster as compared to training models from scratch.

ChatGPT is still in its early stages and is being updated and improved. As a result, the accuracy, flexibility and other features are expected to improve over time.



 I will share some of the use cases for ChatGPT and provide sources, mostly from Twitter, for the information.


1. You can create a blog post

You may be familiar with AI tools that can generate blog posts for you, but these usually require payment. However, ChatGPT offers a free alternative for creating blog posts (since ChatGPT is free to use).

As an example, I have used ChatGPT to write a blog post related to productivity tools, and this is what I got.

Use Cases of ChatGPT in Real Life




3. You can create a movie script for your new movie

I know we all love to watch movies but what if you can create the movie scripts within minutes?

Yes, ChatGPT can help you with that.

Use Cases of ChatGPT in Real Life


4. Write a Program

I have asked ChatGPT to write a simple bubble sort program, and it has written the code for a bubble sort program

Use Cases of ChatGPT in Real Life


 5. Developer Help

Can instruct you to solve errors, explain the exception, and even explain the error message

We found one exception in the bug and we got the below details




7. Generate SQL queries 

SQL is a language that is used to communicate with databases. SQL has been the standard language for relational database management systems that let you access and manipulate databases.



8. Language Support

ChatGPT supports a wide range of languages, including:

  1. English

  2. Spanish

  3. French

  4. German

  5. Italian

  6. Portuguese

  7. Dutch

  8. Russian

  9. Arabic

  10. Chinese (Simplified and Traditional)

  11. Japani

  12. Korean

  13. Hindi

  14. Urdu

  15. Bengali

  16. Tamil

  17. Telugu

  18. Kannada

  19. Malayalam

In total, ChatGPT supports over 50 languages.

So, yes Marathi language is available on ChatGPT. To use it, you simply start your conversation in Marathi , and ChatGPT will detect the language and respond in Marathi accordingly.


Some of the best use cases of ChatGPT in the industry sector are:

1. Customer service:

                 ChatGPT can be used to create chatbots that can interact with customers, answering questions and resolving issues in real time . ChatGPT can be used to provide 24/7 support to customers by answering frequently asked questions and resolving issues. It can answer frequently asked questions and provide relevant information quickly and efficiently.

2. Content creation:

                ChatGPT can be used to generate high-quality and unique content, such as blog posts, product descriptions, and social media posts. ChatGPT can generate articles, reports, and other types of content based on specific prompts

3. Data analysis:

               ChatGPT can be used to process and analyze large amounts of data, such as customer feedback and survey responses, to gain insights and inform business decisions.

4. Business automation:

              ChatGPT can be used to automate repetitive tasks, such as data entry and customer follow-up, to save time and increase efficiency.

5.Language translation:

           ChatGPT can be used to translate text in real time, which can be useful for businesses that operate in multiple languages.

6. Personalization:

            ChatGPT can be used to personalize interactions with customers, such as recommendations and personalized messaging, which can help to increase engagement and sales.

7.Predictive analytics:

           ChatGPT can be used to analyze data to make predictions about future events, such as sales trends and customer behavior, which can help businesses to make better decisions.

8. Summarization:

ChatGPT can be used to summarize large documents and extract key insights, which can be useful for businesses in research, market analysis, and the legal sector.

With the help of ChatGPT, there are literally tons of use cases. I just wrote some of them.

Hope you like it.



Don’t forget to leave your feedback and comments below!

Regards

Sujeet Bhujbal

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Blog: www.sujeetbhujbal.com 

CodeProject:-https://www.codeproject.com/Members/SujitBhujbal

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Sunday 25 August 2024

What is Parallel LINQ (PLINQ) in C#

  Hello friends,

 In this article, I will explain to you below details of PLINQ

  • What is Parallel LINQ (PLINQ) in C# 
  • What are the Benefits of PLINQ  
  • How to Write Parallel LINQ Queries 
  • What are the  methods available in PLINQ
  • Performance 
  • Example

1. What is Parallel LINQ (PLINQ) in C# 

        Parallel LINQ (PLINQ) is an extension of LINQ (Language Integrated Query) in C# that allows you to write queries that are automatically parallelized and executed on multiple threads.
 By leveraging the power of multi-core processors, PLINQ improves query performance.
 It simplifies the process of writing parallel code for data-intensive operations, such as filtering, transforming, and aggregating large datasets.

PLINQ automatically partitions the data and processes it concurrently on multiple threads. It uses the Task Parallel Library (TPL) under the hood to manage the parallelization of query operations. 
This parallel execution can significantly improve performance, especially when dealing with large datasets.

 2. What are the benefits of PLINQ

LINQ provides a convenient way to query data, but PLINQ takes it to the next level by automatically parallelizing the queries. This can lead to significant speed improvements when working with extensive datasets or results

3. What are the  methods available in PLINQ

Here's a list of common  methods available for configuring  the behavior of Parallel LINQ (PLINQ) queries

  1. Parallel execution for a LINQ query by converting it into a PLINQ query.
  2. WithDegreeOfParallelism(int degreeOfParallelism): Specifies the maximum number of concurrently executing tasks that will be used by the query.
  3. WithExecutionMode(ParallelExecutionMode mode): Sets the execution mode of the PLINQ query to either ParallelExecutionMode.ForceParallelism or ParallelExecutionMode.Default.
  4. WithCancellation(CancellationToken cancellationToken): Specifies a cancellation token to enable cancellation of the PLINQ query.
  5. WithMergeOptions(ParallelMergeOptions options): Sets the merge options for combining results from parallel partitions (e.g., ParallelMergeOptions.NotBuffered or ParallelMergeOptions.AutoBuffered).
  6. WithOrdered(): Indicates that the output of the query should maintain the original order, even when parallelized.
  7. WithDegreeOfParallelism(int degreeOfParallelism): Sets the maximum number of concurrently executing tasks used by the query.
  8. WithExecutionMode(ParallelExecutionMode mode): Specifies the execution mode of the query (ForceParallelism or Default).
  9. WithCancellation(CancellationToken cancellationToken): Specifies a cancellation token for enabling query cancellation.
  10. WithMergeOptions(ParallelMergeOptions options): Sets the merge options for combining results from parallel partitions.
  11. ForAll(Action<TSource> action): Executes the specified action on each element of the query in parallel.
  12. AsSequential(): Returns a query that ensures subsequent operations are executed sequentially.
  13. AsUnordered(): Returns an unordered query that may execute more efficiently by ignoring the order of elements.
  14. Where<TSource>(Func<TSource, bool> predicate): Filters the elements of the query based on a specified condition.
  15. Select<TSource, TResult>(Func<TSource, TResult> selector): Projects each element of the query into a new form.
  16. OrderBy<TSource, TKey>(Func<TSource, TKey> keySelector): Sorts the elements of the query in ascending order based on a specified key.
  17. OrderByDescending<TSource, TKey>(Func<TSource, TKey> keySelector): Sorts the elements of the query in descending order based on a specified key.
  18. ThenBy<TSource, TKey>(Func<TSource, TKey> keySelector): Performs a secondary ascending sort on the elements based on a specified key.
  19. ThenByDescending<TSource, TKey>(Func<TSource, TKey> keySelector): Performs a secondary descending sort on the elements based on a specified key.
  20. GroupBy<TSource, TKey>(Func<TSource, TKey> keySelector): Groups the elements of the query based on a specified key.
  21. SelectMany<TSource, TResult>(Func<TSource, IEnumerable<TResult>> selector): Projects each element of the query into a sequence and flattens the resulting sequences into one sequence.

4. Performance of PLINQ queries 

PLINQ is most effective when dealing with operations that are time-consuming, such as computations, filtering, or transformations. It may not be beneficial for relatively quick operations, as the overhead of parallelization could outweigh the performance gain.
Although PLINQ can significantly speed up data processing, it's not always the best choice. Make sure to consider factors like data size, hardware, and overhead when deciding whether to use PLINQ.


5. How to write Parallel LINQ Queries


PLINQ seamlessly integrates with the LINQ query syntax. You can use the familiar LINQ keywords (from, where, select, group, join, etc.) to construct your queries. The difference is that PLINQ will automatically parallelize the execution of these queries when appropriate.

Sunday 31 March 2024

What’s New? Explore ALL NET .8 Features

 

What’s New? Explore ALL NET .8 Features


This article discusses the biggest highlights of .NET 8, from my point of view, and includes some code examples to get you started with the new features.



1. Long-term Support (LTS) Release

.NET 8 is classified as a Long-term Support (LTS) release, meaning Microsoft will continue to provide updates and extended support for it (up to three years). LTS releases are designed for stability and continuity, making them suitable for enterprise applications requiring long-term maintenance.

The extended support ensures that businesses can maintain the stability and security of their applications over an extended duration without being forced into frequent upgrades, providing a reliable foundation for sustained software development and deployment



2. Blazor Update

Now, you can use Blazor for both client-side (Blazor WebAssembly) and server-side (Blazor Server) rendering in the same app.
It supports stateless server-side rendering, streaming rendering, progressive enhancement for navigation and form handling, and interactivity per component.

3. System.Text.Json Serialization

System.Text.Json is a JSON serialization library in .NET that offers high-performance and customizable JSON serialization and deserialization. Introduced as part of .NET Core, it’s now a fundamental component in .NET version 8.

System.Text.Json has improved significantly, especially regarding dependability and performance when utilized in Native AOT apps with ASP.NET Core. These improvements include:

4. Improved support for IAsyncDisposable


In .NET core 8, IAsyncDisposable is an interface introduced to support asynchronous resource cleanup. It is similar to IDisposable, but it allows for asynchronous operations during the disposal of an object. This is particularly useful when dealing with asynchronous resources or cleanup tasks.


5. Extended AI and ML Support

Machine learning and artificial intelligence are essential technologies in today’s software environment. Microsoft has improved AI and ML support with .NET 8, which makes it simpler for developers to easily include complex algorithms and models in their apps.


6. Improved Diagnostics and Observability


In .NET development, improved diagnostics and observability refer to enhanced tools and features for monitoring and understanding the behavior of applications. These .NET 8 features include advanced logging, profiling, and tracing capabilities.


7. New C# Language Features


.NET Core 8 gains from the most recent improvements made to C#, a constantly changing language. The coding experience with this version is more efficient and expressive thanks to new features like enhanced pattern matching, record types, and nullable reference types.



8. Performance Improvements



Microsoft team hits a new .NET version to increase performance. Similarly, making sure your apps are quick, effective, and seamless across various platforms is a top priority of the .NET 8 framework.


End Note

As the .NET ecosystem evolves continuously, developers must stay current with the newest developments and best practices.
Although .NET 7 and .NET 8 both provide excellent features and improvements. NET Core 8 is a more compelling option for developers who want to ensure their applications are future-proof. This new version offers a solid basis for the development of modern applications.

 

Tuesday 23 May 2023

How to implement global exception handling in .NET Core

  Hello friends,

 In this article, I will explain What is global exception and Pros and cons of global exception and  

  • How to implement it via middleware’s


Introduction of Global Exception

We often come up with exceptions in our application and we have two ways in general to handle that exception.

  • Handle at controller/service level everywhere in the application
  • Handle from one place and control the application

 

Pros and Cons of Global Exception

Let’s see the pros and cons of this approach

Pros  :

  • Code becomes easy to manage because we don’t need to look into n different try-catch blocks, just look from one place and deal with them.
  • More readable because a few lines of code managing the whole exceptions of the application
  • Removes repeated code (try-catch everywhere)
  • It gives us more control so we can catch exceptions and return responses of our own type, in most cases we return Internal Server Error.  

Cons :

  • A global exception handler can make it harder because sometimes it will catch the exception at a broad level and deal with it accordingly without digging down to the exact lower-level exception

If you are on short time and you need to implement exception handling then global exception handling is the best solution.


How to Implement it via Middleware

We have different ways to implement global exception handling in our .NET application e.g. using custom/built-in exception filter or creating our custom middleware using IMiddleware and implementing its methods.

So every time before and after controller request will come in this middleware and we would add a try-catch block here and the request would be caught here.

Step 1: Create Middleware




If you are worried about what is JsonConvert.SerializeObject(response) then check post on ‘Serialization’.


Step 2 : Register the Middleware as a Service and then use it in Middleware in Program.cs



That’s all you need to do. Now you can add any exception by throwing a new Exception("This is a test exception"), and test if it works or not


 Happy programming!!

Don’t forget to leave your feedback and comments below!

Regards

Sujeet Bhujbal

--------------------------------------------------------------------------------

Blog: www.sujeetbhujbal.com

Personal Website :-http://sujeetbhujbal.wordpress.com/ 

CodeProject:-http://www.codeproject.com/Members/Sujit-Bhujbal 

CsharpCorner:-http://www.c-sharpcorner.com/Authors/sujit9923/sujit-bhujbal.aspx

Linkedin :-http://in.linkedin.com/in/sujitbhujbal 

Twitter :-http://twitter.com/SujeetBhujbal 

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