What shocking AI evolution does the AI ​​Index Report 2025 reveal? (2025-04) [Paper commentary se... скачать в хорошем качестве

What shocking AI evolution does the AI ​​Index Report 2025 reveal? (2025-04) [Paper commentary se...

[Compass for the AI ​​Era] Paper Commentary Series Artificial Intelligence Index Report 2025 Nestor Maslej, Loredana Fattorini, Raymond Perrault, Yolanda Gil, Vanessa Parli, Njenga Kariuki, Emily Capstick, Anka Reuel, Erik Brynjolfsson, John Etchemendy, Katrina Ligett, Terah Lyons, James Manyika, Juan Carlos Niebles, Yoav Shoham, Russell Wald, Tobi Walsh, Armin Hamrah, Lapo Santarlasci, Julia Betts Lotufo, Alexandra Rome, Andrew Shi, Sukrut Oak https://arxiv.org/abs/2504.07139 ⭐️Story Description The story of this video is about a fisherman grandfather explaining to Nyanta the current state and challenges of rapidly evolving AI through the "AI Index Report 2025". AI performance improvement, cost reduction, international competition, social impact, and ethical issues, as well as educational and environmental issues are discussed from various angles. ⭐️Points Explanation 1. Main findings: AI performance improvement has been remarkable, with scores improving by about 18.8 to 67.3 points in one year on the new AI benchmarks MMMU, GPQA, and SWE-bench introduced in 2023. The performance difference between the open-weight model and the closed model has shrunk from 8.0% to 1.7%, and the performance gap in the China-US AI competition has also narrowed significantly, with generative AI investment increasing 18.7% year-on-year to $33.9 billion, accelerating the AI ​​economic effect. 2. Methodology: This report is a comprehensive assessment of the progress of AI by Stanford HAI, which collects and analyzes various data such as AI model development, AI patents, and AI hardware from around the world. The study integrates data from various fields such as LLM evaluation methods, AI medical applications, and AI public data to clarify AI industry trends. Possible improvements include more detailed regional analysis and standardization of continuous monitoring methods for AI carbon emissions. 3. Study limitations: This study is mainly based on data up to October 2024, which may not reflect the latest AI industry trends. In addition, although reports of AI incidents are increasing, it is believed that there are many unreported cases. The evaluation criteria for RAI Responsible AI are also under development, and further standardization of AI evaluation methods and AI governance is needed. These limitations could be addressed by building a real-time data collection system and establishing international reporting standards. 4. Related research: This paper is an extension of the Artificial Intelligence Index reports from the past seven years and tracks the long-term development of AI. In particular, in the areas of AI regulatory policy and RAI Responsible AI, the relevance of frameworks by international organizations such as the OECD and the EU is emphasized. The study shows the efforts of AI governance in countries around the world and the growing interest in AI ethics, and is at the intersection of many research topics, such as the relationship between AI cost reduction and AI performance improvement. 5. Future impact: This study highlights the importance of promoting standardization of AI evaluation methods and international cooperation in AI governance, and will have a significant impact on the formulation of future AI regulatory policies. The spread of AI cost reduction and open weight models will accelerate the democratization of AI and promote new research and development in social fields such as AI medical applications and education. In addition, concerns about AI carbon emissions suggest the need for more environmentally friendly AI hardware development. ▶︎Members only! Early access to videos here:    / @compassinai   ▶︎Qiita: https://qiita.com/compassinai Arxiv monthly rankings now available!