Bloom

Bloom, also known as BigScience Large Open-science Open-access Multilingual Language Model (BLOOM), is a transformer-based autoregressive language model created by a collaborative effort of over 1,000 volunteer researchers. The project, initiated in May 2021 and culminating in the model's release in July 2022, was primarily led by the AI startup Hugging Face. A significant milestone was the training of the model on the Jean Zay supercomputer in France, a process that took 117 days.

The primary goal behind Bloom's creation was to democratize access to large language models (LLMs), which were traditionally the domain of large tech corporations with extensive resources. By making the model, source code, and training data freely available under a Responsible AI License, the initiative fosters public research and broader use. The development involved more than 250 institutions, with funding and support from the French government, Hugging Face, and others.

Bloom operates as a powerful tool for text generation, capable of producing coherent text in 46 natural languages and 13 programming languages. With 176 billion parameters, the model processes vast amounts of text data to continue and complete text from a prompt. Its client base is diverse, ranging from researchers and academics studying language and AI to developers, content creators, and the general public. Businesses can also leverage Bloom for applications like enhanced customer service chatbots and content generation. The model is accessible through the Hugging Face ecosystem, allowing users to run it on local machines or cloud platforms.

The product itself is a highly versatile language model. Its key feature is its open-access nature, which provides a transparent alternative to proprietary AI models. Bloom can be used for a wide array of tasks it was not explicitly trained for by framing them as text generation problems. For instance, it can be prompted to perform tasks resembling semantic search or to function as a chatbot. While powerful, it is resource-intensive to run and is not designed for tasks like embeddings or classification on its own.

Keywords: large language model, open-access AI, multilingual AI, natural language processing, text generation, autoregressive model, BigScience, Hugging Face, AI research, open-source AI, transformer model, democratizing AI, computational linguistics, programming language generation, AI development, natural language generation, machine learning model, responsible AI, AI ethics, collaborative research