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AIが切り開く新しい半導体市場

AIチップリーディングカンパニーが描く未来戦略

2024/12/11(水) | 12:35 - 14:00

SuperTHEATER 東2ホール 

無料  同時通訳 

生成AIが引き起こした半導体の爆発的成長。規模と同時に大きく姿を変えつつある半導体市場において、いかに競争力を強化し、成長を持続できるか。日本政府の行政機関、最先端ロジックファウンドリ、そしてAI技術をリードする米国企業のトップが登壇し、その未来へ向けたビジョンを語ります。

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パート1「Special Guest Address」

Yoji Muto
武藤 容治
経済産業大臣


 

パート2「AIチップリーディングカンパニーが描く未来戦略」

12:40 - 13:00
AI時代を切り拓く新たな半導体ビジネスモデルRUMS
Atsuyoshi Koike
小池 淳義
Rapidus
代表取締役社長

現在主流のファブレス・ファウンドリモデルに対し、AIがもたらす専用多品種化とスピードに対応した新たなビジネスモデルRUMS(Rapid and Unified Manufacturing Service)を提案する。RUMSでは設計と製造の密接な連携と顧客との共創を重視し、最終製品のイノベーションとグリーン化、そして究極のゴールである人類の幸福の実現を目指す。

13:00 - 13:30
Scaling AI in Hardware and Software
JimKeller
Jim Keller
Tenstorrent
CEO

Tenstorrent uses open software, chiplets and industry standards like RISC-V, Ethernet, MLIR, etc to build a scalable AI solution from embedded to data center. Our hardware design is modular and easy to understand. Our software stack is inherently multi chip aware with deep integration of sharding, data movement and networking. This talk will describe how we use industry standards and layers to build a scalable and accessible AI computer.

13:30 - 14:00
Building The Most Performant AI, From Sand to Cloud
Dario Gil
Darío Gil
IBM
Senior Vice President and Director of IBM Research

For the past two years, we have seen AI capturing the imagination of the public and institutions alike. But as fast as AI is advancing, we are not extracting its full value. Delivering maximum efficiency and performance AI requires an end-to-end solution that co-optimizes hardware, algorithms and AI models, software, and applications— everything from sand to cloud, including handling multiple types of AI workloads in heterogeneous and distributed environments. In this keynote, we will examine what it takes to build such a system. 

We will see how advances in semiconductor technology, chip design, and optimizations for AI workloads lead to chips that make training and running deep learning models less memory intensive, faster, and more efficient. The integration of these chips into the design of AI infrastructure can determine the cost, speed, and efficiency of every stage of the AI lifecycle. Innovations in software and decoding techniques are bringing several times latency improvements. Infrastructure and software co-designed and co-optimized with models and advances to increase the efficiency of algorithms will deliver improvements in speed, energy, compute space, and time efficiency.

A holistic approach that considers algorithms with infrastructure and software up and down a fully integrated stack focused on excelling at critical enterprise workloads has been IBM’s philosophy to building computing systems since its dawn. We did it with IBM Z, a highly specialized full stack system that continues to be the workhorse of enterprise computing and premier transaction processing platform in the world. We are doing it with IBM quantum systems, the industry leading quantum computing platform. And now, we are doing it with generative AI. Join Darío Gil, IBM Senior Vice President and Director of Research, as he unpacks how IBM is building what’s next in generative AI systems to unlock the value of artificial intelligence in the enterprise.

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