Yan Zhuang, The Athletes at China’s Robot Games Fell Down a Lot, Aug. 18, 2025.
There’s a very real concern that robots could eventually make some of our jobs obsolete. But at a robot-only sports competition in China over the weekend, the immediate concern was that they would fall over or crash into each other.
The Humanoid Robot Games, a three-day event in Beijing that ended on Sunday, featured more than 280 teams from universities and private companies in 16 countries. Some robots landed back flips and successfully navigated obstacle courses and rough terrain.
In other cases, the robots’ athletic ability left, well, something to be desired.
During soccer matches, child-size ones tripped over each other, falling down like dominoes. One goalkeeper robot stood placidly as its opponent kicked a ball at its legs several times before finally managing to score.
One robot by China’s Unitree Robotics plowed into a human staff member while sprinting during a track event, knocking him down. [...]
“Despite the pratfalls, significant progress in robot locomotion and balance is being achieved including back flips, side flips, and other acrobatic and martial arts moves,” said Ken Goldberg, a robotics professor at the University of California, Berkeley. [...]
But Professor Fern said the type of robots used in the games are generally not equipped for higher-level functions like planning or reasoning and usually need a human operator to help guide them.
So, how do we link them to such capabilities residing in the cloud?
Eric Schmidt and Selina Xu, Silicon Valley Needs to Stop Obsessing Over Superhuman A.I. Aug. 19, 2025.
It is uncertain how soon artificial general intelligence can be achieved. We worry that Silicon Valley has grown so enamored with accomplishing this goal that it’s alienating the general public and, worse, bypassing crucial opportunities to use the technology that already exists. In being solely fixated on this objective, our nation risks falling behind China, which is far less concerned with creating A.I. powerful enough to surpass humans and much more focused on using the technology we have now. [...]
The current modus operandi is build at all cost. Every tech giant is in the race to reach A.G.I. first, erecting data centers that can cost more than $100 billion and with some like Meta offering signing bonuses to A.I. researchers that top $100 million. The costs of training foundation models, which serve as a general-purpose base for many different tasks, have continued to rise. Elon Musk’s start-up xAI is reportedly burning through $1 billion a month. Anthropic’s chief executive, Dario Amodei, expects training costs of leading models to go up to $10 billion or even $100 billion in the next two years.
To be sure, A.I. is already better than the average human at many cognitive tasks, from answering some of the world’s hardest solvable math problems to writing code at the level of a junior developer. Enthusiasts point to such progress as evidence that A.G.I. is just around the corner. Still, while A.I. capabilities have made extraordinary leaps since the debut of ChatGPT in 2022, science has yet to find a clear path to building intelligence that surpasses humans.
In a recent survey of the Association for the Advancement of Artificial Intelligence, an academic society that includes some of the most respected researchers in the field, more than three-quarters of the 475 respondents said our current approaches were unlikely to lead to a breakthrough. While A.I. has continued to improve as the models get larger and ingest more data, there’s concern that the exponential growth curve might falter. Experts have argued that we need new computing architectures beyond what underpins large language models to reach the goal.
Right. And this crazy over-commitment to machine learning (sunk costs fallacy) starves the pipeline by skewing research, education, and training. We need research on other approaches and broad training, not a narrow focus on machine learning.
While some Silicon Valley technologists issue doomsday warnings about the grave threat of A.I., Chinese companies are busy integrating it into everything from the superapp WeChat to hospitals, electric cars and even home appliances. In rural villages, competitions among Chinese farmers have been held to improve A.I. tools for harvest; Alibaba’s Quark app recently became China’s most downloaded A.I. assistant in part because of its medical diagnostic capabilities. Last year China started the A.I.+ initiative, which aims to embed A.I. across sectors to raise productivity.
It’s no surprise that the Chinese population is more optimistic about A.I. as a result. At the World A.I. Conference, we saw families with grandparents and young children milling about the exhibits, gasping at powerful displays of A.I. applications and enthusiastically interacting with humanoid robots. [...]
Many of the purported benefits of A.G.I. — in science, education, health care and the like — can already be achieved with the careful refinement and use of powerful existing models. [...]
Instead of only asking “Are we there yet?” it’s time we recognize that A.I. is already a powerful agent of change. Applying and adapting the machine intelligence that’s currently available will start a flywheel of more public enthusiasm for A.I. And as the frontier advances, so should our uses of the technology.
Amen.
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