TOSHISTATS starts applying "deep reinforcement learning" to TEXT GENERATION to create Machine intelligence!


Inspired by "AlphaGo by DeepMind", TOSHISTATS researches "deep reinforcement learning (DRL)" since 2016. Today, I announce that TOSHISTATS starts applying DRL to TEXT GENERATION to create Machine intelligence. I am very excited as DRL could work in the field of "Natural Language Processing" very well. I will update the progress of that. Stay tuned!

Cheers Toshi





TOSHI STATS introduces "OpenAI Gym" as the framework of Deep Reinforcement Learning


Since AI-Go player "AlphaGo" beat human professional Go player in 2016, Deep Reinforcement Learning becomes one of the key technologies to develop machine intelligence. Today I am very glad to announce that "OpenAI Gym (1)" is introduced as the framework to develop this technology. Although there are several frameworks for the environments of Deep Reinforcement Learning,  OpenAI Gym is widely used in the communities of researchers and there are many open source projects with it. OpenAI Gym provides many game-based environments for Deep Reinforcement Learning. Here are several examples of the environments and the code to run it.


Hope I can update the progress of our development of Deep Reinforcement Learning soon.

Regards  Toshi


(1) OpenAI Gym, Greg Brockman, Vicki Cheung, Ludwig Pettersson, Jonas Schneider, John Schulman, Jie Tang, Wojciech Zaremba, 2016

TOSHI STATS starts the project of MI (Machine intelligence) in 2018


Happy new year everyone!  As a new year starts now, I would like to announce our new project in TOSHI STATS.  

This is about "Machine intelligence".  With inputs of images/videos and texts, I would like to do experiments of  "what can computers say in our languages?".  I have been developing our base model to do that. With introducing both images and text at once, our model must be more intelligent than before.  I will update the progress the project on our blog.  Hope you can enjoy the results soon!


Regards  Toshi


"Tensorflow Object Detection API" is introduced as our core framework now

Last week, Google released an awesome tool for anyone who is interested in computer vision and deep learning. It is called "Tensorflow Object Detection API". TOSHI STATS introduces this awesome API as our core computer vision framework.  The image above is one of the results of detection task from the API.

I would like to explain why Object Detection API is awesome

  •  It has major classification models.
  •  It enables us to  combine classification models with object detection frameworks
  •  It can be run locally and on Google Cloud Platform

We will make the most of this API to get insights from images and videos.  See you soon!




"Tensorflow Object Detection API" was released by Google on June 15 2017

"Speed/accuracy trade-offs for modern convolutional object detectors."
Huang J, Rathod V, Sun C, Zhu M, Korattikara A, Fathi A, Fischer I, Wojna Z,
Song Y, Guadarrama S, Murphy K, CVPR 2017