Taiwan’s technology sector should lean into the nation’s advantages in servers and chips to overcome the barriers to artificial intelligence (AI) development, Taiwan Semiconductor Industry Association executive officer Wu Chih-yi (吳志毅) said yesterday.
He made the comments at the 12th edition of the Executive Yuan’s quadrennial National Science and Technology Conference in Taipei, saying that the past decade’s transition from discriminative to generative AI has enabled the technology to progress by leaps and bounds.
The key factor driving generative AI’s growth is advances in semiconductor technology
Photo: Cheng I-hwa, AFP
Advances in semiconductor technology are crucial to the development of generative AI, with 2-nanometer chips replacing the 10-nanometer chips that were used just 10 years ago, he said.
The importance of AI can be gleaned from the fact that nine out of 10 of the world’s biggest corporations are involved in the technology, and it is expected to contribute more than US$15 trillion to the global economy by 2030, he said.
The average time elapsed between the initial capitalization of an AI start-up to its growth into a US$1 billion company is 3.4 years, 50 percent shorter than other investment “unicorns,” he said.
The most common application of AI technology is quality control by visual inspection in semiconductor manufacturing, circuit board printing and packaging, but numerous other uses exist in medicine, inventory management and advertising, Wu said.
AI’s exorbitant energy consumption remains one of the main stumbling blocks for the technology, with AI data centers projected to use about 10 percent of all electricity generated in the US, he said.
This means that developing cooling and energy-saving technologies for data centers would likely play a key role in the industry’s future, he said.
The industry must not lose sight of the technology’s negative effects, such as decreased data quality, increased need for synthetic data, information security risks and forced paradigm shifts in business models, he said.
Taiwan’s deficit in data quantity, computing power and software talent makes the nation unsuited for developing generalist large language model AIs, he said, adding that specialist small language model algorithms should instead be the industry’s focus.
The nation makes 90 percent of the world’s servers and its main advantages rest in deep-learning integrated circuit technology, and not the large graphics processing units in which Nvidia and AMD specialize, he said.
Chip designs are far from reaching their theoretical limits imposed by physics, and advances in materials technology would allow progressively better semiconductors to be developed for at least another 20 years, he said.
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