Taketo Yoshida

  • Engineer

Taketo Yoshida

  • Construction

Taketo first graduated from the Department of Aerospace Engineering at the University of Tokyo, where he currently remains enrolled in a master’s course concerning Intelligent Machine Informatics, through the Graduate School of Information Science and Technology. His graduate school activities mainly involve research in Imitation Learning within the broader field of Deep Reinforcement Learning. He joined DeepX after becoming captivated by its sincere approach in developing solutions for social problems and its vision to improve productivity in various industries, through the automation of machinery by means of artificial intelligence technology. He is currently engaged in development and experimentation based on Reinforcement Learning methods, with the aim of solving real problems in society.


My background lies in mechanical engineering, with my studies involving engines in the Department of Aerospace Engineering during my undergraduate years at university. At the time of its inception, during the Industrial Revolution, the engine was something of a diamond in the rough, which has gradually been polished over the intervening centuries through to the present day. In the process of studying this evolution, I realized that the current state of high performance in engines is due to a combination of the length of time since the basic design was first invented, and the relative lack of potential improvement on that original, resulting in an extended period of incremental refinement.

As such, I realigned my studies toward artificial intelligence in the transition to graduate school, as I wanted to learn of and apply myself to a field that can contribute directly to problem-solving, rather than continue the endless iteration of a proven design. Presently, however, most of the practical applications concerning artificial intelligence and related technologies are limited to the realm of cyberspace. There is certainly a wealth of data there, which is perfect for active applications of AI technology, but there are also many real-world issues in society that are impossible to address in such a manner.

The growing labor shortages in both the primary and secondary industries would have to be the most readily apparent example of these social issues. In order to solve this problem, it is imperative that we gather data first-hand, consider how best to apply innovative technologies, and continue to apply ourselves to the constant cycle of trial and error. Through persisting in my efforts at DeepX, I endeavor to harness artificial intelligence technology with the hope of resolving these social issues.



  • Applying Reinforcement Learning methodologies to existing physical machinery
  • Machine learning, especially development of products and services via Reinforcement Learning
  • Developing proprietary simulators
  • Overall managing of machine learning projects


  • I have practiced judo since kindergarten and, even now, occasionally engage in bouts with students at my alma mater. My signature move is the shoulder throw.

  • I often prepare ajillo at home. The ease of preparation, combined with its air of exoticism, make it one of my favorite dishes. I aim to refine my recipe each time, all the while experimenting with different ingredients and proportions in order to strike a perfect balance.

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