TDSE Company Overview

We will be exhibiting our appearance inspection AI "TDSE Eye" at the Smart Factory EXPO held from January 24 (Wednesday) to January 26 (Friday), 2024! On that day, we plan to showcase an anomaly detection demo at our booth using the collaborative robot "TECHMAN AI Cobot" and the robot hand with integrated visual and tactile sensors "Finger Vision." If you are considering automating appearance inspection, please visit the TDSE booth at Tokyo Big Sight, West Hall! ● TDSE Booth: Tokyo Big Sight, West Hall, Booth Number: W69-31

We will be introducing our visual inspection AI system "TDSE Eye," which streamlines visual inspection processes, at the 4th AI & Artificial Intelligence EXPO [Autumn] held at Makuhari Messe from October 25 (Wednesday) to 27 (Friday), 2023! On the day of the event, the developers of TDSE Eye will be available at our booth, so please feel free to consult us about improving the efficiency of visual inspections! We sincerely look forward to your visit. 【Exhibited Product】 ● Visual Inspection AI TDSE Eye 　・Streamlines visual inspection tasks such as parts inspection, food inspection, and equipment inspection 　・No need to prepare defective images thanks to AI built on good product learning 　・Available from 100,000 yen per month 　・No AI or IT skills required 【Exhibition Details】 ● Opening Hours: October 25 (Wednesday) to 27 (Friday) 10:00-18:00 (until 17:00 on the final day) ● Exhibition Location: Makuhari Messe, Exhibition Halls 1-3, Booth Number: 13-31

To effectively utilize AI that is suited for business, it is not enough to simply be able to develop AI. It is important to integrate the development and operational processes to ensure sustainability. In this webinar, we will focus on the keyword "MLOps" and explain best practices for solving this challenge in a series. This is the first session of the webinar series. We will explain the background and purpose of the need for MLOps, its basic concepts, and the overall picture. 【Agenda】 1. Introduction to the basic concepts and importance of MLOps 2. Overview of MLOps 3. Introduction of case studies 4. MLOps in organizational elements