[Seminar] How Physical AI Will Change Industry and Society

[Speaker] Kuniomi Mabuchi, Co-Founder and CEO of XinobiAI Inc. [Key Lecture Content] The evolution of generative AI is expanding from the digital space into the real world. How will "Physical AI," which recognizes, judges, and acts through robotics and autonomous driving, change industries, society, and our work? In this lecture, based on the book "The True Nature of Physical AI," we will clearly explain its fundamental concepts, the technologies supporting its evolution, trends among major global companies and countries, and areas of application such as manufacturing and logistics. Furthermore, we will explore the changing roles and responsibilities of humans and AI/machines, unravel Japan's strengths and challenges, and envision the changes in industry and society towards the 2030s, as well as the future brought about by Physical AI. [Lecture Topics] 1. What is Physical AI? - Changes occurring after "Generative AI" 2. Technologies supporting the evolution of Physical AI 3. Global competitive trends and changes in industrial structure 4. The potential of Physical AI spreading in the field 5. How will human work and responsibilities change? 6. Outlook for the 2030s and Japan's potential 7. Q&A / Business card exchange

[Lecture Topics] 1. How Will Data Centers Change in the AI Era - The Current State of Watt-Bit Collaboration and What is Needed to Transform Concepts into Actual Demand Wataru Kurata, Manager, Telecommunications and Media Industry, Fortience Consulting Inc. 1. It’s not that power is "insufficient," but rather "unable to be transported." 2. The current state of watt-bit collaboration. 3. Where are the new aggregation points? 4. The idea that "if you build it, they will come" does not hold. 5. What will the next generation of data centers look like? 6. Q&A / Business Card Exchange 2. The Current Status and Future of All-Photonics Networks (APN) Akira Sugiyama, General Manager, Strategic Sales Engineering Division, Network Customer Success Division, 1Finity Inc. 1. All-Photonics Network (APN) 2. AI Data Centers and Interconnections between DCs 3. Distributed Data Center Computing 4. Evolution of Coherent Technology 5. Expansion of APN into Submarine Cable Networks 6. Q&A / Business Card Exchange

[Speaker] Partner Attorney Ato Takase, Uchida & Samejima Law Firm [Lecture Items] 1. The Three-Tier Structure of AI Contracts 2. The Boundary Between "Development" and "Use" 3. Technical Composition of AI Systems 4. Points of Consideration by Technical Composition 5. The Chain of Contracts and "Cutting Points" 6. Case Type Determination 7. Procurement of Base Models 8. Rights Management of Training Data 9. Q&A / Business Card Exchange

In this seminar, we will provide a detailed explanation of how to integrate data between Salesforce and other systems. There are three methods for data integration with Salesforce: the "Data Loader," which is provided free of charge by Salesforce, the "Web API," which is developed individually, and the highly extensible "Data Integration Tools (EAI Tools)." We will compare the advantages and disadvantages of each method and provide tips for finding the most suitable integration method for your company's needs, incorporating actual case studies. 【Recommended for】 - Those who are struggling with data integration between Salesforce and core systems - Those who are facing challenges due to the burden on the field, hindering the utilization of Salesforce - Those who want to easily integrate data with peripheral systems

Despite introducing BI tools, are you facing challenges such as "the numbers differ between systems," "it takes time to aggregate data," or "it is not utilized on-site as much as expected"? To successfully leverage data, it is crucial not only to implement analytical tools but also to establish a framework for data collection and integration beforehand. However, many companies struggle with questions like "I don't know where to start" or "Isn't it necessary to consolidate data before it can be utilized?" In reality, there is a significant difference in the mindset and approach to building a foundation between companies that have successfully adopted data utilization and those that have not. In this seminar, we will clarify why the numbers on-site do not match, why the expected results are not achieved even after implementing BI, and we will explain in an easy-to-understand manner the concepts behind building a foundation for successful data utilization. Additionally, we will introduce checkpoints to assess your company's current situation and practical approaches to proceed with a small start.