The next step in the GPT evolution

It is going to bring life to your published work!

An android that will take your place when you die, by reading your content
An android that will take your place when you die, by reading your content

Chat GPT has taken over the world by storm, and it is moving from a technology to try out into a real-life use case-based technology. However, it is currently too general, and many people are not able to harness its power. More amount of people requires it to be used in their specific cases, with their specific models.

This is the next task of GPT, getting more specialized. With generality, development is easy as there is only a single general that fits the world. But when specificity is a deal-breaking requirement, the environment of the task plays a huge role. The environment or the area of specificity changes with each topic and simply cannot be transferred or moved around.

As GPT is based on deep learning protocols, it can learn from different contexts pretty easily. And this is where the next step in GPT lies. Training GPT for task-based operations.

The lawsuit use case

Say you have a large lawsuit filed against you today. And that lawsuit is over 100 pages long of just text. You can spend half your life reading it or better use state-of-the-art technology to help your case. You can get 100 different lawyers provided you are rich to each individually review it and then explain it to you.

This is going to cost you a lot of money, and still, someone would have to spend the time to go through it.

You may go to chat gpt and ask it something about your case, but it isn't going to help you with solving your case. You can try to upload the whole document as input and then ask questions to get some sort of relevant output.

Current NLP language processors are more or less on the look for things. These can be keywords or tokens, sentences, and phrases.


Here comes GPT Integration to the rescue

GPT has opened its API and now allows users to fine-tune their models based on their data and use case. It now allows you to train its response on specific text documents you can provide. This includes things like Law suits files, code documentation, and your high school English textbook, and start asking and querying it questions.

GPT 3.4 and GPT4 both models have this feature, and you can get started with this right away if you'd like. Visit this to learn more OpenAI

Simply go to the documentation, download the library ( available in NodeJS and Python), and your context-based text, by following the method. And voila! Your personally trained GPT chatbot that specifically trains on your data is now available. 

There are other features too, like fine-tuning models and embeddings that can help you further aid your use case.

Understanding its potential

All apps that you see on the web are going to change with this. Trust me, all of them are.

OpenAI has made it dynamic for everyone to be able to do this instead of just big tech (well, at least for now), and hope it continues in the same trend.

Do you have a blog with 100s of posts? Well, now you can set up this system and have anyone ask questions to you. Almost like they are asking questions to your soul. Think of it like your consciousness has been preserved in the blog, and the GPT is helping it bring it back to life. A parallelized consciousness!

Imagine the possibilities.

dArticle, a decentralized blogging application, currently has this feature, so be sure to use it as your publishing platform!

Follow me for more updates on Decentralization and Artificial Intelligence concepts.

You are viewing an NFT