A “ChatGPT moment” for China’s humanoid robots – the tipping point at which the technology becomes widely usable – remains years away as persistent challenges in adapting to new tasks and training efficiency continue to hold back the industry, leading experts said on Wednesday at the Boao Forum for Asia in Hainan.

Despite rapid advances in recent years, humanoid robots were still far from large-scale deployment, with both hardware and software limitations yet to be fully resolved, panellists said during a discussion on the sector’s future.

“The core issue is that robotics data is extremely high-dimensional, while text data [used to train large language models] is essentially one-dimensional,” said Shao Hao, chief scientist at the robotics lab of Chinese smartphone maker Vivo.

“Looking back, deep learning began gaining momentum around 2012, but the breakthrough moment didn’t arrive until around 2019. The key difference maker was data.”

In the robotics industry, references to OpenAI’s “ChatGPT” have become shorthand for the point at which a technology overcomes key technical bottlenecks and achieves mass adoption.

By massively expanding the volume of training data – including large amounts of human-labelled inputs – OpenAI developed models capable of generalising across previously unseen tasks, underpinning ChatGPT’s launch in late 2022.