In the previous section, we touched upon the general idea of Artificial Intelligence. AI systems, at their core, are designed to process information, much like humans do. But what kind of information are we talking about? Information comes in many forms, and in the field of AI, we refer to these different forms or types of data as modalities.
Think of modalities as the different channels through which information can be received or expressed. For humans, these are our senses: sight, hearing, touch, taste, and smell. AI systems also work with information from various sources, and understanding these sources is fundamental before we can explore how AI combines them. Let's look at the primary data modalities you'll encounter in Multimodal AI.
Text is perhaps the most familiar data modality. It's information conveyed through written language. This includes:
For an AI system, text isn't just a collection of letters. It's a sequence of characters, words, and sentences that carry meaning. While we'll get into the specifics of how AI processes text later, for now, think of it as structured information that AI can analyze to understand topics, sentiment, or even answer questions based on the provided text.
Image data represents visual information. It's how we capture and share what we see. Examples include:
When an AI system "looks" at an image, it typically sees a grid of tiny dots called pixels. Each pixel has color and brightness information. By analyzing patterns in these pixels, AI can learn to identify objects (like a cat or a car), recognize scenes (a beach, a forest), or detect specific features within an image.
Audio data is information conveyed through sound. This modality encompasses a wide range of sound types:
For an AI system, audio is typically represented as sound waves that have been converted into a digital format. These digital signals capture characteristics like frequency (pitch) and amplitude (loudness) over time. AI can analyze these signals to transcribe speech into text, identify different musical genres, or recognize specific sound events.
An AI system can receive input from various data modalities like text, images, and audio.
While text, images, and audio are the most common modalities we'll discuss in this introductory course, it's good to know that AI can work with other types of data too. For instance:
For our purposes in "Introduction to Multimodal AI," we will primarily focus on how AI systems work with combinations of text, image, and audio data.
Each data modality carries information in a unique way and has its own inherent structure. Text is sequential, images are spatial, and audio unfolds over time. Recognizing these differences is the first step in appreciating the complexities and capabilities of Multimodal AI. When an AI system can process and relate information from these diverse sources, it can achieve a more comprehensive understanding of the world, much like humans do.
In the sections that follow, we'll explore what it means to combine these modalities and why doing so can lead to more powerful and intelligent AI systems.
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