While this year's AGI-related topics in Japan seem fewer than previous years (see my articles for 2015 and 2014), new players such as AIX Research Center at the University of Electro-Communications and Araya Brain Imaging came into the scene. A public fund was given to a five-year project Comparison and Fusion of Artificial Intelligence and Brain Science.
SIG-AGI, a special interest group of the Japanese Society for AI (JSAI), held sessions at the JSAI 2016 Convention, three workshops, and an event at the 30th Anniversary of JSAI (index in Japanese).
The Whole Brain Architecture Initiative (WBAI)(NPO) held a symposium, five seminars for the general public, the second annual hackathon, and a session at ICONIP.
Below, I write the development of WBAI's activities as an insider.
WBAI has a specific approach for AGI using brain-like connectomic architecture and off-the-shelf machine learning algorithms. Last year, it was seeking collaborators on this approach world-wide, as it could not find enough researchers domestically. Besides, it was also in need of software infrastructure such as basic cognitive architecture and learning environments. In April, Dwango AI Lab., an affiliated private research laboratory, held a hackathon on a new learning environment (LIS or Life in Silico) for intelligent agents. It was a great success with around 150 participants. At the time, the situation around A(G)I was rapidly changing overseas. One thing was the advent of OpenAI, an NPO aiming to counter AGI development by commercial superpowers such as Google. In 2015, people in WBAI and SIG-AGI were talking with people in the AGI community overseas about establishing a similar entity. The endeavor was supposedly quenched by the inauguration of OpenAI. Another thing happening overseas was impressive advances of DeepMind. While WBAI had a rather long-term plan for promoting researches with the WBA approach, there was a concern that DeepMind would realize AGI in a nearer future in a somewhat WBA way (some details in my memo "A Scenario in which DeepMind will realize AGI by 2018"). So WBAI veered.
With the success at the hackathon in April, WBAI set eyes on the potential of 'hobbyist' engineers/researchers and held another hackathon on Deep Predictive Coding Networks (originally proposed by David Cox's group) in July and created a new development community called SIG-WBA (the course of events is documented here). WBAI is now more focused on popularizing evolving A(G)I technologies. Problems? Recently, research institutes such as Google, OpenAI, and GoodAI have released learning environments for intelligent agents. That's a good thing (also for WBAI), but it requires human resources to check them out. More importantly, WBAI is yet to develop basic connectomic architecture to be the core of their approach to attract researchers and engineers anywhere. (The official version of WBAI's policy can be found here, which, of course, continues to evolve. To keep you updated, follow WBAI on Twitter ...)