The Japanese Government Joins Forces with Tech Giants to Invest Hundreds of Millions in Developing a Japanese Language Model


Japan announced new guidelines for its "AI Robot Strategy", planning to deploy 10 million AI robots in 18 industries including manufacturing, healthcare, and agriculture by 2040, to systematically address the labor crisis caused by low birthrate and aging population.....
Japan's investment blueprint to FY2040 mobilizes over 370 trillion yen across 17 strategic areas, with Physical AI as the core at 10.5 trillion yen. It refers to systems that perceive, decide and execute physical operations, targeting industrial automation, unmanned transport and infrastructure inspection to counter labor shortages.....
Baidu released its new language model Ernie5.1 on May 11, 2026, based on the pre-trained foundation of Ernie5.0 with 2.4 trillion parameters. Through a 'one-time elastic training framework', it achieves single training optimization for multiple model sizes, with pre-training cost only 6% of similar models. As of May 9, the model ranked fourth globally and first in China on the Arena Search ranking with 1223 points, demonstrating high resource utilization and performance balance.
The Japanese government announced the establishment of a cross-ministerial task force to train talent in strategic industries such as artificial intelligence, semiconductors, quantum technology, shipbuilding, and defense manufacturing. The move aims to shift the workforce toward high-growth areas rather than merely expanding traditional vocational training. According to the "Yomiuri Shimbun", Tokyo is coordinating the establishment of a "Re-skilling and Talent Development Promotion Committee," under the Cabinet Office, to drive strategic adjustments in the workforce.
Apple and The Ohio State University jointly launched the FS-DFM model, which can generate long text comparable to traditional models after only 8 iterations, achieving a writing speed improvement of up to 128 times, breaking through the efficiency bottleneck of long text generation. The model uses discrete flow matching technology, different from self-regressive models like ChatGPT that generate text character by character.