From: mk_thisisit
The progress and development in AI have been significantly accelerated by open research and open-source software, fostering global collaboration and knowledge sharing. This approach ensures that the entire community benefits from advancements, rather than just individual entities [00:00:00].
Benefits of Openness
When research and work, including techniques and code, are published openly, the entire world benefits [03:59:19]. The creators gain prestige and recognition, while the broader community reaps real benefits from the shared knowledge [03:59:19]. This collaborative model, often mistakenly viewed as competition, is a form of global cooperation [03:59:19].
Global Collaboration in AI Research
Good ideas in AI appear everywhere in the world [04:09:44]. The research community is global, with contributions from various regions. For instance, the first LLaMA model from Meta was created in their Paris lab [04:14:13], which houses over 100 scientists and has produced many successful projects [04:14:13]. Other significant labs include the one in Montreal [04:14:13]. There is no single institution or region with a monopoly on good ideas [04:14:13].
China, for example, has produced very innovative work in AI for a long time, particularly in computer vision, with Chinese scientists making up half of the participants at leading computer vision conferences [04:14:13]. Ideas from new Chinese models are quickly adopted and integrated into future versions of systems developed in the U.S., Europe, and the Middle East [04:14:13]. This global exchange of knowledge is the charm of open source and open research [04:14:13].
Impact on AI Progress
The rapid progress in AI over the last decade is precisely due to open research [03:59:19]. This approach accelerates development across the entire field [03:59:19].
Case Study: PyTorch
Almost the entire AI industry, at least in the research and development stage, uses PyTorch, an open-source software system [03:59:19]. PyTorch was initially created by Meta colleagues at FAIR and later by the wider community [03:59:19]. Ownership was transferred to the Linux Foundation, making it community-managed, although Meta remains a major contributor [03:59:19]. Companies like Microsoft, Nvidia, and even Open AI and Anthropic utilize PyTorch, with academic research also heavily relying on it; it’s mentioned in about 70% of relevant publications [03:59:19]. This widespread adoption exemplifies how progress in AI is based on the mutual use of others’ work [03:59:19].
Contrast with Closed Approaches
While open research is prevalent, some companies operate with more secrecy. Open AI, for example, has never fully adopted an open approach, keeping everything a secret [03:59:19]. Google, which previously had partial openness, has become partially closed [03:59:19]. This closed approach can exclude many people from the research community, hindering overall progress [03:59:19].
Conclusion
The speaker emphasizes that open research and open-source software are crucial for the continued rapid development of AI [03:59:19].