The Future of AI: Multimodal AI Models

(source)

You've probably seen words like Machine Learning and Multimodal AI Models but aren't sure what they mean. It can be hard to fully know the technical terminology with today's emerging advanced AI models like ChatGPT or with AI models already integrated into our lives like virtual assistants Siri or Alexa. Today's article is on what is Multimodal AI Models and how they change our everyday lives.

What Are Multimodal AI Modals

Multimodal AI models are AI models that can process and interpret multiple types of data input at a time like audio, text, images, videos, and more.

For example, ChatGPT 4 can analyze and create images, so let's say I have a picture of a beach, and I ask ChatGPT:

Tell me what the weather might be in this picture.

ChatGPT combined different types of information – like pictures and text – to tell me what it thinks is the weather.

Why are Multimodal AI Models important?

Why are Multimodal AI Models so important? Combining different types of data can give you a more complete understanding of a topic, or in other words, ChatGPT can be your researcher. Instead of going through hundreds of websites on Google, you only need to type one prompt and get all you need in one convenient place.

Real-world examples of Multimodal AI Models

(source)

One great example we hear from Google a lot is their Gemini AI. I wrote an article all about it here. The article was about how Google has released Gemini 1.0, a multi-modal system that combines image, text, speech, and numerical data types to perform better results. I compared ChatGPT 4.0 with Bard's new AI, Gemini Pro, to test their natural language understanding and response capabilities.

Another fascinating example is GitHub Copilot. GitHub Copilot uses the ChatGPT-3 model. GitHub Copilot is an AI tool in collaboration with GitHub and OpenAI to help developers by autocompleting code.

Conclusion

In conclusion, multimodal AI models have revolutionized data processing by allowing various data types - such as audio, text, images, and videos - to be processed simultaneously. Now, you have at least an understanding of multimodal AI models and maybe overall AI terminology.