Tag Machine Learning

Hello everyone!

Today, I am excited to share with you about my experience creating a Python program that uses ChatGPT with OpenAI’s API to maintain two separate conversations with two different people. This project was a stepping stone to my next video, where I plan to use facial recognition, speech recognition, and text-to-speech to create a bot that can hold conversations with multiple people looking and talking to it, “like a real boy.”

To start, let me explain what ChatGPT is. ChatGPT is an AI language model that can be used to generate human-like responses to text prompts. It is one of the many language models available on OpenAI’s API platform. OpenAI’s API allows developers to use their state-of-the-art AI models for a variety of applications, including natural language processing, computer vision, and more.

For my project, I decided to use ChatGPT to maintain two separate conversations with two different people. I started by creating a Python script that would connect to OpenAI’s API and authenticate my credentials. I then wrote a function that would generate a response to a given text prompt using ChatGPT. Finally, I wrote the main program that would loop through the two conversations, prompting each person for a response and using ChatGPT to generate a response to each.

The program worked flawlessly, and I was able to maintain two separate conversations with two different people using ChatGPT. I was thrilled with the results and excited to see how this would tie into my next video.

In my next video, I plan to use facial recognition, speech recognition, and text-to-speech to create a bot that can hold conversations with multiple people looking and talking to it, “like a real boy.” With the help of ChatGPT, I will be able to generate human-like responses to text prompts, which will make the conversations feel more natural and engaging.

In conclusion, my experience creating a Python program that uses ChatGPT with OpenAI’s API to maintain two separate conversations with two different people was a great success. I am excited to see how this ties into my next video. Don’t forget to like the video and subscribe to my YouTube channel, for more exciting content like this.

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I’ve been getting more and more into programming with A.I. to let a computer find solutions to problems I give it with reinforcement training or a neural network and a bunch of data. It’s not as simple as it sounds. I recently found a couple music projects that use A.I. to separate vocals, drums, bass, piano and other sounds from each other into their own audio tracks. One is called Spleeter and the other is Facebook Research’s Demucs. They both use Python and TensorFlow (a popular machine learning programming library).

I wrote an application with Node.js that will take advantage of Spleeter and use Youtube to download songs from a playlist and automatically separate them and save the music tracks. Then play the original and silently watches the RMS volume of the vocals and drums to determine when to open his mouth or turn his neck.

When Halloween comes I hope to tie these to lights out front with relays and add a couple more singers to the stage.
I’m working on changing the high voltage servo for the mouth to a stepper motor with a bike brake cable for remote jaw actuation.
Take a look below to see behind the scenes of how the skeleton is controlled.

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