Lūgumraksts adresēts: EU, USA, UK, Canada, Australia

Join us in our urgent mission to democratize AI research by establishing an international, publicly funded supercomputing facility equipped with 100,000 state-of-the-art AI accelerators to train open source foundation models. This monumental initiative will secure our technological independence, empower global innovation, and ensure safety, while safeguarding our democratic principles for generations to come.
In an era of unparalleled technological advancements, humanity stands on the precipice of a new epoch characterized by the profound influence of artificial intelligence (AI) and its foundational models, such as GPT-4. The potential applications of these technologies are vast, spanning scientific research, education, governance, and small and medium-sized enterprises. To harness their full potential as tools for societal betterment, it is vital to democratize research on and access to them, lest we face severe repercussions for our collective future.
Increasingly, we are witnessing the emergence of a system wherein educational institutions, government agencies, and entire nations become dependent on a select few large corporations that operate with little transparency or public accountability. To secure our society's technological independence, foster innovation, and safeguard the democratic principles that underpin our way of life, we must act now.
We call upon the global community, particularly the European Union, the United States, the United Kingdom, Canada, and Australia, to collaborate on a monumental initiative: the establishment of an international, publicly funded, open-source supercomputing research facility. This facility, analogous to the CERN project in scale and impact, should house a diverse array of machines equipped with at least 100,000 high-performance state-of-the-art accelerators (GPUs or ASICs), operated by experts from the machine learning and supercomputing research community and overseen by democratically elected institutions in the participating nations.
This ambitious endeavor will provide a platform for researchers and institutions worldwide to access and refine advanced AI models, such as GPT-4, harnessing their capabilities for the greater good. By making these models open source and incorporating multimodal data (audio, video, text, and program code), we can significantly enrich academic research, enhance transparency, and ensure data security. Furthermore, granting researchers access to the underlying training data will enable them to understand precisely what these models learn and how they function, an impossibility when restricted by APIs.
Additionally, the open-source nature of this project will promote safety and security research, allowing potential risks to be identified and addressed more rapidly and transparently by the academic community and open-source enthusiasts. This is a vital step in ensuring the safety and reliability of AI technologies as they become increasingly integrated into our lives.
The proposed facility should feature AI Safety research labs with well-defined security levels, akin to those used in biological research labs, where high-risk developments can be conducted by internationally renowned experts in the field, backed by regulations from democratic institutions. The results of such safety research should be transparent and available for the research community and society at large. These AI Safety research labs should be capable of designing timely countermeasures by studying developments that, according to broad scientific consensus, would predictably have a significant negative impact on our societies.
Economically, this initiative will bring substantial benefits to small and medium-sized companies worldwide.
By providing access to large foundation models, businesses can fine-tune these models for their specific use cases while retaining full control over the weights and data. This approach will also appeal to government institutions seeking transparency and control over AI applications in their operations.