Megabyte: The Tokenization-Free GPT Architecture from Meta AI In their new pre-print research paper, Meta AI has unveiled Megabyte, a groundbreaking framework for Generative Pre-Trained Transformer (GPT) systems that is completely tokenization-free. OpenAI’s Andrej Karpathy has described this architecture as “promising”, and it comes with exciting implications for the future of AI. Tokenization is a lossy process that’s similar to file compression, and it’s essential to process large quantities of data. GPT models convert bytes to tokens, which are then processed by the transformer to generate output tokens that are later decoded. Unfortunately, even with tokenization, the state-of-the-art system has a hard limit for the amount of data it can process. With GPT-4, this limit is only slightly over 4,000 tokens, which translates to approximately 3,000 words. The Megabyte system created by Meta AI seeks to revolutionize this process. It utilizes a novel multi-layer prediction architecture that is capable of end-to-end modeling over 1 million bytes of data. With standard 8-bit encoding, each character takes up one byte of data. Therefore, an AI system that can process 1 million bytes of data without tokenization can work with text documents containing 750,000 words – a 3,025% increase over GPT-4. The implications of this research are significant; tokenization is a roadblock to the field due to its data limits and the amount of energy and time required to train systems. Without tokenization, researchers can now train AI models with more robust foundational support for non-English languages, which opens up possibilities for democratizing these technologies. Building tools such as cryptocurrency trading bots and decentralized autonomous organization technologies in native language codes worldwide is a real possibility. Megabyte’s model also performs exceptionally well on processing audio and image files, and the amount of energy consumption is about the same as text processing, which opens up horizons for working with multimedia content. For instance, GPT-4 can handle ten feature-length news articles in a single prompt, while Megabyte has the capacity to parse the entirety of War and Peace, along with other average-length novels. To sum up, Megabyte has the potential to replace tokenization, opening up possibilities for democratizing technologies and increasing the capacity for processing non-English languages. Furthermore, it will enable the creation of AI tools that can work with multimedia content. Editor Notes Megabyte has set a new standard for GPT systems and has presented researchers and developers with an opportunity to strengthen foundational support for non-English languages. This research aligns with the vision of GPT News Room to keep its readers updated with groundbreaking news on Generative Pre-trained Transformer systems. Check out the website for the latest developments in the field. via GPT News Room https://ift.tt/Ba7FURH
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