Scaling AI becomes the grand challenge of the Intelligence Era The post Creating A Moore’s Law For AI Scaling appeared first on Semiconductor Engineering .
The accelerating demand for AI compute is pushing the limits of current semiconductor scaling paradigms, necessitating new architectural and manufacturing innovations.
Achieving continued scaling for AI is critical for sustaining advancements in all AI-driven sectors and preventing a computational bottleneck that could stall progress.
The focus of semiconductor innovation is shifting from general-purpose scaling (Moore's Law) to specialized scaling for AI, involving novel transistor architectures and multi-die assemblies.
- · AMD
- · imec
- · Brewer Science
- · Advanced Packaging Sector
- · Companies reliant on traditional scaling
- · AI developers with limited access to advanced compute
New manufacturing techniques like CFETs and forksheet FETs will become standard for high-performance AI chips.
Increased complexity in chip design and manufacturing will further concentrate semiconductor production among a few advanced players.
The definition of 'Moore's Law' will broaden to encompass heterogeneous integration and specialized AI scaling rather than just transistor density.
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