Core Insights - Zomato founder Deepinder Goyal announced a personal investment of $25 million to launch Continue Research, a scientific collective aimed at extending healthy human lifespan through open-access discovery [1] - The initiative seeks to challenge traditional biological models by identifying simple mechanisms that influence aging [1][3] Funding Structure - The funding framework consists of two categories: Moonshot grants ranging from $50,000 to $250,000 for short-term exploratory research, and Deep Dive grants from $250,000 to $2 million for longer mechanistic investigations [5] - Moonshot grants allow researchers six to twelve months to explore seemingly straightforward hypotheses that may be overlooked by traditional funding bodies [5] Research Philosophy - Continue Research operates under a philosophy that small interventions targeting foundational biological processes can lead to significant changes in aging experiences [3] - The initiative emphasizes a systems-level view of the human body to identify biological factors controlling aging at its roots [2] Open-Source Commitment - All research generated by Continue Research will be made publicly available, ensuring unrestricted access for the scientific community and the public [6] - The initiative commits to open-source science and public data sharing, including all data, protocols, and outcomes [6] Organizational Structure - Goyal structured Continue Research as a research collective with a funding mechanism, rather than a traditional corporation or startup, allowing global support for scientists while focusing on simple solutions to complex aging questions [4]

Core Insights - The interview with Wang Zhizhen highlights the significant impact of AI tools like AlphaFold on the field of structural biology, particularly in predicting protein structures, which accelerates research progress [1][2] - Despite the advancements brought by AlphaFold, it is noted that the predictions are not always 100% accurate, especially for novel protein structures, indicating limitations in its application [1] Group 1: AI in Scientific Research - AlphaFold is recognized as a representative application of AI in science, demonstrating remarkable potential in predicting protein three-dimensional structures [1] - The tool has become widely used among scientists in the field, allowing for rapid insights into protein structures from amino acid sequences [1] Group 2: Challenges in Structural Biology - Structural biologists face the challenge of not only determining molecular structures but also understanding their functions, which involves complex interactions among multiple molecules [2] - The study of molecular functions requires interdisciplinary approaches, including cell biology, to fully comprehend how molecules operate [2]