Third-party cyber evaluations involving OpenAI models
openai.com·13h ago
Data Science
Simon Willison's Blog·Jul 3·5 min read
Open Source AI Gap Map
TL;DR
A gap existed in the indexing of open source AI resources, making it difficult to navigate the ecosystem. Open Source AI launched the Gap Map, which catalogs 421 products including software tools, models, datasets, and hardware projects.
✦ Why It Matters
Engineers and researchers can leverage the Gap Map to efficiently find and utilize open source AI resources.
Key Takeaways
- Explore the Gap Map to find relevant AI tools and libraries.
- Contribute to the uncategorized artifacts by researching and citing them.
- Utilize the available data on GitHub for your own projects.
- Engage with the community to enhance collaboration in open source AI.
Full Summary
Open Source AI Gap Map is a project initiated by a global partnership to create a public option for AI, supported by $400 million in funding. Recently, they released Gap Map v0.1, which catalogs 421 open source AI products, including 266 software tools, 85 models, 50 datasets, and 20 hardware projects from 228 organizations.
These products are categorized into 14 groups across three layers: model components, product/user experience (UX), and infrastructure. Additionally, there are 24,400 uncategorized artifacts that will remain unscored until further research is conducted.
The underlying data is available under an MIT license on GitHub, comprising 1,184 YAML files and various scripts for data collection. This transparency allows developers to explore the ecosystem and contribute to its growth.