🤖 Building an AI Business in 24 Hours: A Step-by-Step Guide
Are you interested in building an AI business but don’t know where to start? In this article, we’ll show you how to build an AI business in just 24 hours. We’ll cover everything from generating ideas to building a prototype and connecting it to a database.
🧠 Generating Ideas
The first step in building an AI business is to generate ideas. You can start by brainstorming and sketching down your ideas. It’s important to think about what kind of problem you want to solve and how AI can help.
One idea could be to create a Chrome extension that uses AI to do auto-completes for people when they’re writing in text fields. However, large companies like Grammarly already have this space covered. Another idea could be to create a startup that searches through documentation of popular libraries and languages and uses AI as a chatbot to give you answers from that documentation.
Brainstorming some more, you could use AI for image processing, but large companies like Mid Journey and Adobe already have this covered quite well. Let’s Enhance, for example, lets you upscale your images with AI really well, and Adobe has released their recent update which brings even more AI features to things like Photoshop and Illustrator.
With so much competition in the AI space right now, you need to pivot and change your idea. Remember that one of the best ways to come up with ideas is to try and remember past problems.
🤔 Identifying a Problem
Think about a problem you’ve had in the past that AI could solve. For example, you might have been doing a tutorial on Free Code Camp and gotten stuck during the video. You might have wanted to search for something specific in a long video and download the transcript of that video to search through it.
📈 Building a Prototype
Once you’ve identified a problem, it’s time to build a prototype. You can start by using the YouTube API to download the transcript and then plug that into a database that a chat GPT can use to find the answer for you.
You can use the YouTube captions API to download the transcript, but you might encounter some problems. You can try out different options and test them out until you find one that works.
Next, you can connect directly to the YouTube API and connect that directly to Chad GPT. You can create a file called comments.js that pulls out the captions for your YouTube video. You can then merge all the text together into a file called merge.txt that Chad GPT can use as part of the transcript.
You can plug this all into a prompt with a specific question called “What is this video about?” and cross your fingers. You can open up console, run node, and wait for the response. Chad GPT should answer your question accurately.
🌐 Connecting to a Database
The next thing you want to do is plug this all into a database so you can store and communicate with it better. You can use a vector database because that is what is best now, especially when you’re trying to use large language models.
You can use Astra DB because they’ve recently introduced vector databases as part of their database suite. You can create a new free account and create a new database on the dashboard. You can select to create a vector search database and call it YouTube transcripts.
You can fill out some basic information such as the provider being on Google Cloud and the region being US West. You can create the database and test it out.
🚀 Building a Web Interface
The next thing you want to do is build a web interface that you can use to communicate with the back end. You can use Tailwind CSS for the user interface and some JavaScript to render out different types of UI based on messages from the back end.
The messages you get from Chad GPT can be looped through and printed out as HTML content. The back end is quite simple. You grab the URL address of the video as well as the messages passed from the client. These are sent to Astra DB as well as Chad GPT.
You pass this information back to the front end, and the front end updates its state based on the data that was sent. The end result is a project that’s working exactly how you intended.
🎉 Conclusion
Building an AI business in 24 hours is possible if you follow these steps. You need to generate ideas, identify a problem, build a prototype, connect to a database, and build a web interface.
Remember that this is an MVP, and there are limitations. If the video is a few hours long, you might not be able to fit the entire transcript into a Chad GPT message. You might need to split the transcript into small sections and save those in Astra DB.
If you want to check out this project, we’ll link it in the description below. Thank you to Astra DB for sponsoring today’s video. They make videos like this happen on the channel.
🌟 Highlights
– Building an AI business in 24 hours is possible if you follow these steps.
– You need to generate ideas, identify a problem, build a prototype, connect to a database, and build a web interface.
– Remember that this is an MVP, and there are limitations.
❓ FAQ
Q: Is it possible to build an AI business in 24 hours?
A: Yes, it’s possible if you follow the steps outlined in this article.
Q: What kind of problem should I solve with AI?
A: Think about a problem you’ve had in the past that AI could solve.
Q: What kind of database should I use?
A: You should use a vector database because that is what is best now, especially when you’re trying to use large language models.
Q: What are the limitations of this project?
A: If the video is a few hours long, you might not be able to fit the entire transcript into a Chad GPT message. You might need to split the transcript into small sections and save those in Astra DB.
Resources:
– Astra DB: https://www.astra.com/
– YouTube API: https://developers.google.com/youtube/v3
– Tailwind CSS: https://tailwindcss.com/