Inside BLOOM: How Thousands of AI Researchers Created an Open Source ChatGPT Alternative
An open-source LLM shows that tech incumbents are not the only companies able to create massive models.
When we think about large language models(LLMs) alternatives to ChatGPT, we tend to think about projects from large AI labs or ultra-well-financed startups. But what happens when a large number of AI researchers decide to collaborate to make LLMs available to mainstream researchers? The result is BLOOM, an open source 176 billion parameters LLMs that is able to master tasks in 46 languages and 13 programming languages.
The development of BLOOM was coordinated by BigScience, a vibrant open research collaboration with a mission to publicly release an LLM. The project was brought to life after being awarded a computing grant by GENCI on its Jean Zay supercomputer at IDRIS/CNRS. The project was founded by Hugging Face and the French NLP community and soon attracted a diverse international collaboration with a goal to support linguistic, geographical, and scientific diversity. Over 1200 participants from 38 countries, including experts in machine learning, computer science, linguistics, statistics, socio-cultural anthropology, philosophy, law, and other fields, registered with BigScience and were given access to its communication channels.