Anthropic, the company behind the generative AI model Claude, is launching a new program to fund the development of novel benchmarks for evaluating AI models. This initiative aims to reshape how AI models are assessed, focusing on benchmarks that accurately reflect real-world applications and prioritize AI safety. Anthropic’s investment in this area will likely significantly impact the development and evaluation of future AI models, including its own.
A historical overview of AI benchmarks
AI benchmarks play an important role in evaluating model performance. Traditionally, they measure tasks such as image recognition and natural language processing. However, more comprehensive and realistic benchmarks are needed for more advanced systems, such as generative models. Traditional benchmarks fail to capture the complexity of real-world applications and do not reflect the challenges of modern AI technologies.
Why did Anthropic take such an initiative?
Anthropic aims to address the shortcomings of existing benchmarks by funding new and comprehensive assessment methods. Focusing on AI safety and societal impacts, the company wants to develop criteria measuring advanced capabilities. The program aims to create hard enough benchmarks, realistic and relevant to safety.
The program will focus on three main areas: AI safety assessments, advanced capability and safety benchmarks, and infrastructure, tools, and methods for assessment. By addressing these areas, Anthropic aims to create scalable and ready-to-use benchmarks.
Key focus areas of the program
One of the main areas of focus is AI security assessments. These assessments measure tasks with significant security implications, such as carrying out cyber-attacks. Another area of focus is advanced capability and security benchmarks, which measure performance on complex tasks that require a high level of expertise. The third area is the development of infrastructure, tools, and methods for creating assessments.
Principles of effective assessments
Effective evaluations should be rigorous and meaningful. Assessments should be sufficiently difficult and should not be included in the training data of the AI model. Efficiency and scalability are important principles. Evaluations should be developed with input from domain experts. Good documentation and reproducibility are essential for transparency and replication.
Application and review process
Anthropic has established a structured process for submitting and reviewing proposals for the new criteria. Interested organizations can submit their proposals through the application form. The company provides financial support and offers financing options tailored to project needs.
Selected proposals will have the opportunity to collaborate with Anthropic’s domain experts. The collaboration will ensure that evaluations are developed to high standards and address the most pressing challenges in AI safety and performance.
Anthropic’s initiative to fund the next generation of AI benchmarks aims to improve the evaluation of AI models. By addressing the limitations of existing benchmarks, the program aims to create more comprehensive and meaningful assessments. Through collaboration with third-party organizations and support from domain experts, Anthropic hopes to elevate the field of AI safety and add valuable tools to the AI ecosystem.
Featured image credit: vecstock / Freepik
