Chinese researchers develop hybrid chip design that holds promise for “thinking machines”

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Their work on Tianjic hints at China’s accelerated pace of development in the fields of AI and chip design.

Chinese researchers have developed a hybrid chip architecture that could move the world a step closer to achieving artificial general intelligence (AGI) and a future filled with humanlike “thinking machines”.

The potential for attaining AGI, also known as “full AI”, by adopting such a general hardware platform was set out by a team of researchers, led by Tsinghua University professor Shi Luping, in a research paper that was published as the cover story of scientific journal Nature on Thursday.

Their research presented the case for the Tianjic chip, which was designed by integrating the “computer-science-oriented and neuroscience-oriented” approaches to developing AGI.

Tianjic shows that combining those two approaches, which rely on fundamentally different formulations and coding schemes, can enable a single computing platform to run diverse machine-learning algorithms and reconfigurable building blocks, among others.

“This chip for general AI has the potential of being applied across many industries,” said Shi, a professor at the Centre for Brain-Inspired Computing Research in Beijing’s Tsinghua University, in an interview on Thursday. “Autonomous driving, robotics and automation would be among the fields where this chip can make a difference.”

In their featured report on Nature, the Chinese researchers said they designed a self-driving bicycle to evaluate how their attempt at an AGI chip would fare in a road test. The bicycle was equipped with a camera, gyroscope, speedometer, driving and steering motors and a Tianjic chip.

The test, which was recorded on video, had the bicycle perform obstacle detection and avoidance, balance control, voice command recognition, tracking and decision making under different road conditions.

Shi said the chip ably demonstrated “its prowess in supporting multiple coding schemes and adaptive capabilities in a complicated environment”.

Efforts are now underway to incubate start-ups that would focus on developing applications based on the Chinese researchers’ work on the Tianjic chip design, according to Shi. He said the goal was to launch a version of the chip for mass production by early next year, without elaborating on the details of potential commercial partnerships, investments and the costs such a plan would entail.

The researchers’ work on Tianjic and AGI hints at the accelerated pace of development in China in the fields of AI and semiconductor design.

The world’s second-largest economy has not been shy about its. The country’s State Council released a road map in July 2017, with the goal of creating a domestic industry worth 1 trillion yuan (US$145 billion) and becoming a global AI powerhouse by 2030.

At present, most mainstream AI research has been focused on so-called domain-dependent and problem-specific solutions such as facial recognition and automated trading. By comparison, AGI represents the hopes of building general-purpose systems with intelligence comparable to the human mind.

While China is on a par with global peers in chip design, in terms of the foundry business, meaning the manufacture of integrated circuits. Beijing has called for self-sufficiency in strategic technologies, including chip making, amid the country’s ongoing tech and trade war with the US.
China has recently made progress on its 200 billion yuan fund aimed at investing in home-grown semiconductor development, as the world’s second-largest economy looks to reduce dependence on foreign chip technology.
Telecommunications gear maker ZTE Corp was brought to the brink of collapse last year when the US cut off the supply of American technology. Huawei Technologies, the world’s largest telecoms network equipment supplier, has so far survived a US trade ban that blocks it from buying components like chips and software from American hi-tech firms.
The value of China’s annual chip imports has surpassed oil in recent years, surging to US$312 billion in 2018.
Source: SCMP
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