Sylvain Duranton is the Global Leader of BCG X and a member of BCG’s Executive Committee. BCG X is the tech build & design unit of BCG. Turbocharging BCG’s deep industry and functional expertise, BCG X brings together advanced tech knowledge and ambitious entrepreneurship to help organizations enable innovation at scale.
Research Institution on September 16, 2022 in Hsinchu, Taiwan. Taiwan's semiconductor manufacturing capabilities are crucial to global supply chains, with megacap companies like Apple, Nvidia and Qualcomm heavily dependent on the island's exports. Taiwan accounts for some 60 percent of global semiconductor foundry revenue, according to media reports. Generative AI is reshaping the future – including geopolitics – and at the core of this upheaval are transistor-etched silicon chips.
A decade after transistors replaced vacuum tubes in electronics in the late 1950s, Fairchild Semiconductor began cramming multiple transistors onto a single chip, marking the start of Moore’s Law, which states that the number of transistors on a microchip doubles about every two years. But with Moore’s Law faltering, demand for computational power is higher than ever due to the rise of generative AI and edge computing.
While Nvidia dominates the AI chip market with its CUDA platform — a platform for programming NVIDIA GPUs — alternatives are emerging. The UXL Foundation, for example, is working on free alternatives to CUDA, potentially opening the market to more hardware options. As non-Nvidia chips gain traction, a more competitive landscape will likely alleviate capacity constraints and diversif the supply for AI hardware.
Power consumption and memory constraints are also critical challenges in chip design. High-bandwidth memory and in-memory computing are emerging solutions, helping address memory bottlenecks that can slow AI performance. Leaders like Samsung and SK Hynix are pushing the envelope on memory innovation to unlock new levels of performance and efficiency.
The future of computing points towards modular systems combining CPUs, GPUs, AI accelerators, and specialized chips. Intel’s strategy of integrating CPU and GPU cores in one package exemplifies this shift, combining diverse processing capabilities to suit various AI workloads. This modular approach fosters flexibility and efficiency, ensuring that businesses and nations investing in these technologies remain at the forefront of innovation.
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