Monthly Ludens Report Nov/Dec
We wrapped up a busy 2018 with some great events and media coverage. Our regular Ludens meetup has gained great popularity, with an increasing number of people from the world of AI attending each time with keen interest. It is satisfying to see that the Ludens project is gaining worldwide popularity. We thank everyone who supported us in 2018, and here is our last activity report for 2018.
11/15 Announcement of VHA at Tsinghua University (Beijing)
On 15th November, at an industry-academic exchange meeting held at Tsinghua University, Ludens representative Mr. Ishii made a presentation on the Virtual Human Agent “Ludens” project.
Tsinghua University is one of Asia’s most prestigious universities and ranked 2nd in Asia according to Times Higher Education 2018 rankings.
At Tsinghua, we had a highly productive discussion and got extraordinary interest from AI researchers and students in Ludens’s VHA.
11/27 BlockShow Asia 2018
We were invited to BlockShow Asia, a major international event for sharing established Blockchain solutions, with Mr. Ishii and Mr. Ishiguro taking part as presenter and panel participant respectively.
At this event, we also had an exhibition booth for our project, and our VHA “Rachel” successfully worked as a receptionist. The popularity of Rachel as a receptionist was really exciting for us! Good job!
Ludens project was profiled in the famous media “Nikkei FinTech”
In November 2018, Nikkei FinTech, a famous magazine about emerging technologies across the world, wrote an article about Couger Inc., which is our Japan-based partner company. The article also covered in detail about the Ludens’s VHA technology, which combines AI, AR, and blockchain.
The article talks as to how Ludens enables ‘virtual human agent’ to recognize objects and perform tasks like a human being, has amazing memory and emotions, and can react efficiently in real time.
12/6 Ludens meetup#4
On 6th December, we held the 4th Ludens meetup at DeNA’s office in Shibuya. As usual, the theme was related to AI, and this time we discussed “How can machines learn from small data sets”. In general, computers need a large amount of data as well as multidimensional data to learn from and train its algorithms. However, large data is not available easily in the practical world. As such, we need to find ways to make computers able to learn from a small amount of data. Dr. Priya Kansal, from Couger Inc., was the first speaker and explained the concept of “Learning from small data”. After her detailed and technical talk, Mr. Alisher Abdulkhaev, machine learning engineer at PKSHA Technology, presented about “One-shot learning”. This solution is still open for research, and he showed some published approaches and code demonstrations of use cases.
AI learning simulator “Dimension” was featured in TechCrunch
We have been developing the AI learning simulator “Dimension”, which creates situations where many virtual people walk around streets and stores. This can be used for training and testing AI of self-driving vehicles and autonomous mobile robots. As those development needs are expanding, Honda R&D and Chubu University are already using Dimension for research purposes. Below is a link to an article that explains what we have done on this project so far.
Christmas messages from the Singapore office!
We have been developing the AI learning simulator “Dimension”, which creates situations where a number of virtual people walk around streets and stores. This can be used for training and testing self-driving vehicles and autonomous mobile robots. As those development needs are expanding, Honda R&D and Chubu University are already using Dimension for research purposes. Below is a link to an article that explains in detail what we have done on this project so far.
