Everyone knows the importance of images in the digital age. But have you ever wondered how artificial intelligence understands and processes images? Today, we will explore GPT-4’s image encoding method, which many are curious about. During this process, a magic number, 170, appears. Let’s examine what this number means and the actual process of image encoding.
Basics of Image Encoding
Converting images to text involves many steps. The most crucial is processing each image by dividing it into small tiles. GPT-4 encodes tiles of 512×512 size into 170 tokens. The critical point here is that each token must be converted into a vector.
GPT-4’s High-Resolution Image Processing
GPT-4 processes each tile in high-resolution mode using 170 tokens. This means a single image contains information equivalent to about 227 words. But what does this number 170 mean? While it might be a magic number used without explanation in programming, in GPT-4, this number is the core of image processing.
Embedding and Vectorization Process
Transformer models operate on vectors, not discrete tokens. Therefore, the input image is first converted into vectors. For example, a sentence is converted into integer tokens using BPE (Byte Pair Encoding), then each token is transformed into a 4096-dimensional vector. This is the preprocessing required before reaching the first layer of the transformer model.
Differences Between CLIP and GPT-4
The CLIP model embeds text and images into the same semantic vector space, allowing it to find images related to text strings. However, GPT-4 uses a more advanced strategy for encoding images, enabling it to process all forms of data, thus being “omnimodal.”
Pyramid Strategy and Experimental Validation
The pyramid strategy in image encoding is one way to encode various details of an image. This method represents images using grids of different sizes. It shows high accuracy for grids of 5×5 or smaller, but performance decreases with larger grids. This means GPT-4 can accurately process grids up to a certain size.
Conclusion
GPT-4’s image encoding method is highly complex and sophisticated. The method of encoding images using 170 tokens results from extensive research and experimentation. This allows GPT-4 to process and understand images like text.
Reference: Oran Looney, “A Picture is Worth 170 Tokens: How Does GPT-4 Encode Images?”