The AI Race Is Becoming A Silicon Race

Iri Trashanski, Chief Strategy Officer at Ceva, is shaping the future of the Smart Edge with extensive experience across tech sectors.

​Google, Amazon, Meta, Microsoft, Apple, OpenAI and other technology leaders are investing in custom silicon as AI becomes increasingly central to their products and platforms. The reason is straightforward: Competitive differentiation in AI is moving deeper into the technology stack. When AI becomes strategic, the architecture underneath it becomes strategic too.​

The takeaway for other companies is broader than custom chip development. Companies need to decide where proprietary technology creates meaningful competitive advantage, where proven intellectual property can accelerate development and where their engineering resources can create the most value.

Semiconductor IP can play an important role in that strategy. Instead of spending years developing every underlying capability, companies can start with proven building blocks and focus their investment on the architecture, algorithms, software and experiences that differentiate the finished product.

Why Silicon Matters More In The AI Era

For much of the software era, companies could differentiate at the application layer while relying on relatively standardized computing platforms underneath. But as AI moves into PCs, vehicles, robots, industrial equipment, wearables and billions of connected devices, product performance increasingly depends on decisions made at the silicon level.

Consider what makes an AI experience effective. It needs to respond quickly. It may need to operate without a reliable cloud connection. It needs to protect sensitive data. In battery-powered products, it needs to accomplish all of this within tight power constraints.

These requirements change the engineering challenge. At the edge, simply adding more compute is rarely the answer. The challenge is delivering the appropriate compute within the application’s power, memory, latency and cost constraints.