Robotics Get Even Bigger for South Korea
They’re already one of the leading countries in the world when it comes to robotics, but South Korea are once again pushing forward in this area with a recent announcement that they will be injecting 500 billion won ($445 million approx) into the robotics industry over the next five years.
They’re already one of the leading countries in the world when it comes to robotics, but South Korea are once again pushing forward in this area with a recent announcement that they will be injecting 500 billion won ($445 million approx) into the robotics industry over the next five years.
Like I said, South Korea are no strangers to robots and last year won the top prize in DARPA’s Robotics Challenge event with Team Kaist’s DRC-Hubo humanoid robot. They have also designed and created Drinky – a robotic drinking buddy that can chink glasses with you and down his drink in style along with you.
With this new injection if funding, a big chunk of it will be used towards finding new talent that can help pave the way for the next generation of robotic technology by 2020. Robotics is big business and statistics suggest that globally this industry will be worth around $135 billion by 2019.
The trade minister, Joo Hyung, said, “The robot industry has emerged as a new technology frontier that will give a fresh boost to the manufacturing sector. The government will fully support the businesses’ investment into research and development in a bid to help the industry grow as a new export leader.”
South Korea’s robotics industry is already like no other and hosts a range of different robots. These include manufacturing robots, those used in the healthcare sector as well as autonomous prison guards and even robots that fill the seats of absent fans at the Hanwah Eagles baseball team stadium.
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Daniel Okafor
Daniel Okafor is the Senior AI Reporter at TrendinTech, where he covers large language models, machine learning research and the practical use of artificial intelligence across business and government. He previously reported on artificial intelligence for MIT Technology Review, covering the labs behind the current generation of frontier models and the policy debates in Washington and Brussels. Daniel holds a Master of Science in Machine Learning from Carnegie Mellon University and follows the research community closely, attending NeurIPS and ICML each year to speak with the people behind the papers. He has a particular interest in evaluation: how models are benchmarked, where those benchmarks fail and what that means for the companies betting on them.
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