One enthusiastic teacher recently released a video explaining why we should now create short video content (clips) that serve as the toolbox (resource) from which AI draws to create tutorials for specific purposes or simply answer questions. Essentially, this is how AI is trained in the initial stages. Instead of being trained on data found on the Internet, you can train the AI with content you create.

For instance, if you want to study from a textbook, scan it into a PDF, feed it to AI, and voila! You now have what you would consider reliable information—provided the AI can perform accurate pattern matching to provide accurate responses.

I personally enjoy loading PDF files of scientific papers into AI. The results I obtain are relevant to the content of the paper.

However, there’s a downside to loading source documents into AI: there’s a limit to how much you can load. One AI model claims to be able to handle up to 200 source documents, but it doesn’t specify the volume limit for each document, which is crucial. Almost any AI can process a 2-hour video, transcribe the spoken text, and provide a summary of the content. Additionally, they can answer questions that may require Internet access to acquire additional material to explain or elaborate on points made in the original video.

The above is an AI rewrite of what I originally wrote. Here’s an AI summary of the above:

AI can be trained on user-created content, such as short video clips or scanned documents, to generate tutorials or answer questions. While this method offers control over the training data, there are limitations on the volume of documents that can be processed.

John Carter Sr.