1st AI Tool Chatgpt :- Its No Long when Robots Think & Act like intelligent Human !!

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Artificial Intelligence (chatgpt) :-

It is the future of the World! Journey begin towards AI Robots. Chatbot is the first step in this way !!

Chatbot to intelligent AI robot

What I can do for you?

Hi, Have you seen famous Hollywood movie I robot, In this movie we have seen robots are dealing all tasks independently. robots was doing everything even thinking like human. At that time it was looking fictitious. Have you ever thinks that this would become a reality. really no we didn’t. Progress over the time in this AI tools development begin in this decade and now we are able to see lots of development in this stream all over the world. The days are not so far when robots will listen & react same as human. Development on this areas like human Emotions reading with the help of face reading technology is on the hike now. With the help of AI based deep & machine learning modules days are no longer when machine start working according to tone of human instructions. facial expression’s & emotions reading will play vital role. So what are the ways to do so lets check.

Before knowing more about chat GPT (chatbots) lets have a look on Natural Language processing because NLP is base of any AI tool like chatbots:- https://www.technofesto.com/nlp/

What is Chatgpt ? How it get evolved ?

Chatgpt is an AI tool that is basically a chatbot. it gives answers, suggestions, and solutions as per the uploaded database by the developer. According to your questions, it generates a possible answer based on its level of intelligence. It’s not a search engine like Google. For any AI tool development, there are several phases that you can come to know after reading this article thoroughly.

It’s important to note that developing a high-quality chat AI tool like Chat GPT is a complex and resource-intensive task. It requires a deep understanding of NLP, machine learning, and infrastructure management. If you don’t have the necessary expertise, you may consider collaborating with a team of experts or leveraging existing chatbot platforms that provide customization options.

Certainly! Let’s dive deep into more detail on each step of developing a chat AI tool like Chat GPT

In conclusion, the problem identified within Company/Organization Name requires immediate attention and resolution in order to mitigate its negative impacts and achieve our desired objectives. By clearly defining the problem and proposing a solution approach, we are taking the necessary steps toward addressing the issue and improving our overall performance and success

Chat GPT chatgpt

Problem statement: –

The purpose of this defining problem statement for AI tools like Chat GPT during development is to provide a clear and concise problem definition for Company/Organization/technique. This problem definition will serve as a foundation for understanding the challenges and issues that need to be addressed in order to achieve our objectives.

The company / Organization is currently facing the following problem.

Describe the problem in detail, including its impact on the company/organization and its stakeholders.

This problem is affecting specific areas or departments, resulting in negative consequences or challenges. It is hindering our ability to achieve specific goals or objectives, and if left unaddressed, it can have long-term implications for our overall success.

The key aspects of the problem include a list of the key factors or elements contributing to the problem. These factors have been identified through research, analysis, or observations and are critical to understanding the root causes of the pain.

The problem requires attention and resolution because explains the reasons why it is essential to address the problem. By addressing this problem, we can state the potential benefits or outcomes, leading to improved efficiency, enhanced performance, increased customer satisfaction, etc.

The primary objectives for addressing this problem are as follows:

Specify the primary objective or goal to be achieved.
List any additional objectives or goals that are relevant to solving the problem.

Solution Approach: – 

To resolve the identified problem, we propose the following solution approach:

Briefly describe the proposed solution approach, including any strategies, methodologies, or frameworks that will be employed.
Outline the key steps or actions that will be taken to implement the proposed solution approach.

Expected Outcomes:-

By successfully addressing the problem, we anticipate the following outcomes:

Specify the expected positive outcomes, such as improved efficiency, increased productivity, cost savings, etc.
List any additional anticipated benefits or improvements that are relevant to solving the problem.

Prepare objective & Project timeline: –

Clearly define the goals and objectives of your chat AI tool same as what Chat GPT team did. Determine what problem you want to solve and how the tool will provide value to users. Identify the target audience and the specific use cases you want to address.

Collect and Prepare Data:

Gather a large dataset of conversational data. This can include chat logs, customer support transcripts, social media conversations, or any other relevant source. The dataset should be diverse and representative of the intended use cases. Ensure the data is properly labeled. For example, if you want the chat AI tool to provide customer support, you’ll need to label the data with appropriate intent and entity information.

Reprocess and Clean the Data:

Clean the collected data by removing any irrelevant or noisy content. This can include removing duplicate conversations, filtering out spam or irrelevant messages, and handling special characters or formatting issues. Preprocess the text data by tokenizing it into individual words or sub-words, removing stop words (common words with little meaning), and applying other techniques like stemming or lemmatization. Normalize the text by converting it to lowercase or handling specific domain-related abbreviations or acronyms.

Choose a Language Model Architecture:

Select a suitable language model architecture for your chat AI tool. Popular choices include GPT-3, GPT-2, BERT, Transformer-XL, or other transformer-based models. Consider factors such as model size, performance, inference speed, and available resources for training and deployment. GPT-3.5 is the model used by ChatGPT, but it may not be accessible for direct use by external developers. 

Fine-tune the Language Model:

Fine-tuning is the process of training the chosen language model on your specific dataset. This step helps the model adapt to your use case and domain. Fine-tuning typically involves using a technique called transfer learning. You initialize the language model with pre-trained weights and then continue training it on your dataset. Fine-tuning requires significant computational resources, including powerful GPUs or TPUs. It may also require expertise in machine learning and NLP techniques.

Implement the Chat Interface:

Develop a user interface that allows users to interact with your chat AI tool (check out Chat GPT interface- https://chat.openai.com). chatgpt team focused on developing their interface first before going for tool development. This interface can be a web application, a chatbot platform, a messaging app integration, or an API that other applications can integrate with. Design the chat interface to provide a seamless conversational experience. It should handle user queries, send them to the AI model for processing, and display the responses in a user-friendly manner.

Test and Iterate:

Thoroughly test your chat AI tool (chatgpt) to ensure it performs well in different scenarios. Evaluate its accuracy, response quality, and robustness. Collect feedback from users and iterate on the model and interface based on the insights gained. Continuously refine and improve the system based on user needs and expectations.

Deploy and Scale:

Deploy your chat AI tool (chatgpt) to a production environment, making sure it can handle concurrent users and scale to meet the demand. Set up proper monitoring and logging to track the tool’s performance, identify any issues, and make necessary optimizations or updates as required. Monitor user feedback and usage patterns to identify areas for improvement and plan for future enhancements.

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