
Lennart Heim
Articles
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2 months ago |
rand.org | Lennart Heim
Recent coverage of DeepSeek's AI models has focused heavily on their impressive benchmark performance and efficiency gains. While these achievements deserve recognition and carry policy implications (more below), the story of compute access, export controls, and AI development is more complex than many reports suggest. Here are some key points that deserve more attention: Real export restrictions on AI chips only started in October 2023, making claims about their ineffectiveness premature.
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Jan 17, 2025 |
lawfaremedia.org | Lennart Heim |Janet Egan |Jen Patja
Published by The Lawfare Institute in Cooperation With Janet Egan, Senior Fellow at the Center for a New American Security (CNAS) and Lennart Heim, an AI researcher at RAND, join Kevin Frazier, a Tarbell Fellow at Lawfare, to analyze the interim final rule on AI diffusion announced by the Bureau of Industry and Security on January 13, 2025. This fourth-quarter effort by the Biden Administration to shape AI policy may have major ramifications on the global race for AI dominance.
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Jan 14, 2025 |
rand.org | Lennart Heim
Availability: Web-Only Year: 2025 Pages: 39DOI: https://doi.org/10.7249/PEA3776-1 Document Number: PE-A3776-1 Heim, Lennart, Understanding the Artificial Intelligence Diffusion Framework: Can Export Controls Create a U.S.-Led Global Artificial Intelligence Ecosystem? RAND Corporation, PE-A3776-1, January 2025.
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Apr 6, 2024 |
blog.heim.xyz | Lennart Heim
Post-training enhancements can indeed significantly improve model performance. Regulators should be aware that AI capabilities might be substantially improved through post-training enhancements. We observe that, with current methods, capabilities can be increased to an equivalent of 5x to 20x increase in training compute through post-training enhancements.
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Mar 28, 2024 |
lawfaremedia.org | Markus Anderljung |Lennart Heim |Haydn Belfield
Published by The Lawfare Institute in Cooperation With Computing power—compute, for short—is a key driver of artificial intelligence (AI) progress. Over the past 13 years, the amount of compute used to train leading AI systems has increased by a factor of 350 million. This has enabled the major AI advances that have recently gained global attention. However, compute is important not only for the progress of AI but also for its governance. Governments have taken notice.
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