Using ChatGPT with YOUR OWN Data. This is magical. (LangChain OpenAI API)

Summary

The video demonstrates how to integrate personal data with Chat GPT to enhance its functionality. By using the Lang chain library and an Open AI API key, users can structure and query their own data, such as documents, schedules, and social media feeds. The process is simple, requiring minimal coding, and offers a more personalized experience while raising considerations about privacy and data usage with Open AI services.

Takeaways

• 📊 The speaker has discovered a method to integrate personal custom data with Chat GPT, allowing it to organize and structure documents for easy interaction and information retrieval.
• 💡 Chat GPT can describe companies and provide historical information based on the user's internships when fed with personal data.
• 📅 The tool can also track personal events, such as dentist appointments, by analyzing data the user has previously inputted.
• 📆 The speaker demonstrates the ability to inquire about future events, like their parents' trip, by providing Chat GPT with their calendar data.
• 🔍 Chat GPT can summarize social media feeds, such as Twitter, when provided with the data, offering a quick overview of the day's posts.
• 📝 The tool can assist in summarizing web pages and articles when the user does not want to read the entire content.
• 💻 A local solution for data analysis is presented using a GitHub Library called The Lang Chain, which simplifies the process with minimal coding.
• 🔑 The Lang Chain tool facilitates the loading of text documents, vectorizing the data, and enabling queries against the structured information.
• 🔗 The use of an Open AI API key is necessary for the process, and it's possible to obtain one with a free trial budget.
• 🛠️ The speaker emphasizes the importance of learning Python, a widely used language in the tech industry, for those aspiring to work at top-tier companies.
• 🔒 Privacy concerns are raised regarding the use of APIs, with Open AI's policy stating that user data will not be used for model training after March 1st and will be deleted after 30 days.

Q & A

What is the main topic of the video?

The main topic of the video is about how to integrate personal custom data with Chat GPT to enhance its functionality and provide more personalized assistance.

How does the speaker describe the process of feeding personal data into Chat GPT?

The speaker describes a process where they structure and organize their personal data, then feed it into Chat GPT, allowing the AI to crawl through and interact with the data, providing information and answers based on the user's documents and history.

What are some examples of personal data the speaker uses with Chat GPT?

The speaker mentions using data from their internships, dentist appointments, parents' trip schedules, Twitter feed, and even code snippets.

What is the Lang Chain library mentioned in the video?

Lang Chain is a GitHub library that simplifies the process of integrating custom data with Chat GPT. It allows for text loading, vectorizing, and structurizing data for querying against it.

How does the speaker address the privacy concerns related to using Open AI's API?

The speaker notes that Open AI's privacy policy states they will not use data submitted by their API to train or improve their models starting from March 1st. However, they also mention that before this date, data could have been used and was retained for up to 30 days for monitoring purposes.

What is the significance of the code provided in the video?

The code provided in the video demonstrates how to set up a personal bot using Lang Chain to ingest custom data and query it using Chat GPT, allowing for a more personalized and interactive experience.

What are the potential applications of the personalized Chat GPT as described in the video?

The potential applications include summarizing social media feeds, analyzing personal documents, creating calendaring apps, finding bugs in code, and generating review summaries for products based on customer feedback.

How does the speaker discuss the difference between the Open AI API and the Azure Open AI API in terms of privacy?

The speaker mentions that the Azure Open AI API keeps the data within Microsoft and encrypts it, with only certain employees able to access it for debugging within 30 days. In contrast, the Open AI API's previous practices were less clear, but they stopped using user data for training around March.

What is the speaker's opinion on using third-party plugins with Chat GPT?

The speaker expresses concern about the authenticity and potential manipulation of third-party plugins. They suggest that writing your own code provides more control and transparency over what the AI is doing with your data.

How does the speaker demonstrate the capability of Chat GPT to understand and extend patterns?

The speaker provides an example where they give Chat GPT a sequence of odd numbers and ask it to extend the pattern by adding 10 more numbers. Chat GPT successfully identifies and continues the pattern, showing its ability to understand and apply numerical sequences.

What advice does the speaker give to those who are hesitant to learn Python?

The speaker advises that Python is a valuable language to learn because it's simple to read, easily adaptable to other languages, and widely used at top-tier tech companies. They emphasize that it's a standard language and recommend learning it, even if one already knows other languages like Java.