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🧠 AI🟢 BullishImportance 7/10
AI+HW 2035: Shaping the Next Decade
arXiv – CS AI|Deming Chen, Jason Cong, Azalia Mirhoseini, Christos Kozyrakis, Subhasish Mitra, Jinjun Xiong, Cliff Young, Anima Anandkumar, Michael Littman, Aron Kirschen, Sophia Shao, Serge Leef, Naresh Shanbhag, Dejan Milojicic, Michael Schulte, Gert Cauwenberghs, Jerry M. Chow, Tri Dao, Kailash Gopalakrishnan, Richard Ho, Hoshik Kim, Kunle Olukotun, David Z. Pan, Mark Ren, Dan Roth, Aarti Singh, Yizhou Sun, Yusu Wang, Yann LeCun, Ruchir Puri|
🤖AI Summary
A research paper presents a 10-year roadmap for coordinated AI and hardware co-development, targeting 1000x efficiency improvements in AI training and inference by 2035. The vision emphasizes energy efficiency over raw compute scaling, proposing integrated solutions across algorithms, architectures, and systems to enable sustainable AI deployment from cloud to edge environments.
Key Takeaways
- →Research community proposes shifting AI scaling focus from compute power to energy efficiency with 1000x improvement targets by 2035.
- →Current fragmented approach to AI and hardware development is constraining progress toward holistic and sustainable AI systems.
- →Success metrics include democratizing AI infrastructure access and enabling seamless cloud-to-edge AI deployment.
- →The roadmap calls for coordinated national initiatives and sustained public-private partnerships to achieve AI+HW co-design goals.
- →Vision emphasizes human-centric design principles embedded into intelligent systems development.
#ai-hardware#energy-efficiency#ai-scaling#co-design#research-roadmap#sustainability#edge-computing#ai-infrastructure#efficiency-gains#2035-vision
Read Original →via arXiv – CS AI
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