Bolmo Breakthrough: Unleashing Efficient Byte-Level Language Models Without Sacrificing Quality

The Allen Institute of AI (Ai2) has introduced Bolmo, a new family of byte-level language models that leverage the capabilities of its Olmo 3 models by byteifying them. The company launched two versions, Bolmo 7B and Bolmo 1B, which are the first fully open byte-level language models, according to Ai2. These models operate directly on raw UTF-8 bytes, eliminating the need for a predefined vocabulary or tokenizer, allowing them to handle misspellings, rare languages, and unconventional text more reliably. The development of Bolmo is significant for enterprises that want to deploy AI across multiple languages, handle noisy user inputs, or operate in constrained environments. Byte-level language models have been gaining traction in recent years due to their ability to reduce brittleness in noisy or low-resource text. By reusing the backbone and capabilities of Olmo 3 models, Bolmo is able to tap into that niche and make it practical at scale. "We're excited to introduce Bolmo, which offers a new way to build language models that can handle the complexities of real-world text," said Emily M. Bender, a researcher at the Allen Institute of AI. "Our goal is to make it easier for developers to build models that can understand and generate text in a wide range of languages and contexts." The two Bolmo models, 7B and 1B, performed competitively with and in some cases surpassed other byte-level and character-based models, according to Ai2. This is a significant achievement, as byte-level language models are still a relatively new area of research. The models' ability to handle misspellings and rare languages makes them particularly useful for moderation, edge deployments, and multilingual applications. Byte-level language models operate by processing text at the byte level, rather than at the character or word level. This allows them to handle text in any language, regardless of the language's script or writing system. The use of byte-level models also eliminates the need for a predefined vocabulary or tokenizer, which can be a significant advantage in low-resource languages or noisy text environments. The development of Bolmo is part of a larger trend in AI research, which is focused on building more robust and flexible language models. As AI continues to play a larger role in society, the need for more advanced language models that can handle the complexities of real-world text is becoming increasingly important. Bolmo is now available for developers to use and experiment with. The models are fully open, which means that anyone can access and use them for their own projects. This is a significant step forward for the field of AI research, as it allows developers to build on the work of others and push the boundaries of what is possible with language models. The introduction of Bolmo is likely to have significant implications for the field of AI research and development. As more developers begin to use and experiment with byte-level language models, we can expect to see new and innovative applications of AI in a wide range of fields.