Macnica Data・AI Forum 2024 Autumn
Winning in the era of generative AI with a data-centric approach
The future of companies is about to change dramatically with the power of generative AI. The key to this is the power of data.
At Macnica, in addition to utilizing generative AI and machine learning, we also take a data-centric approach.
In particular, we believe that improving the quality of data will be the key to creating value going forward.
This event will introduce technical information and use cases on the themes of data infrastructure, LLM, and AI TRiSM.
We have prepared content to help Japanese companies promote data-centric use of AI.
session
Use of data and generative AI
Legal issues
Mr. Makoto Uchida
Legal issues regarding the use of data and generative AI
This seminar will cover basic topics such as the legal nature of data and the legal nature of data license agreements, as well as clauses that should be included in data-related contracts, points to be aware of, and common mistakes to make. In addition, based on the experience of having already filed dozens of patent applications related to generative AI and formulating many terms of use for services using generative AI and internal rules regarding the use of generative AI, this seminar will provide an easy-to-understand explanation of points to be aware of and legal issues when using generative AI or services using generative AI as a company.
iCraft Law Office Lawyer and Patent Attorney
Mr. Makoto Uchida
He specializes in building intellectual property strategies related to AI and IT, and building legal strategies for personal information and data businesses. He is a member of the working group for the Ministry of Economy, Trade and Industry's "AI and Data Contract Guidelines Review Committee." He has been selected twice in the intellectual property category of the lawyer rankings conducted by the weekly Toyo Keizai magazine.
Evolving AI technology and the business
"Human-centered approach"
Masaya Mori
Evolving AI technology and a "human-centered approach" in companies
The progress of AI in recent years has been remarkable. In particular, the emergence of generative AI and its rapid evolution have amazed the world on a daily basis. In this presentation, I will discuss the trends in AI technology, touching on key technologies ("world models" and "probabilistic programming").
We will also explain the future direction of AI utilization in companies, referring to the concept of "Human-Centered AI," which is gaining attention.
Hakuhodo DY Holdings Inc.
Executive Officer
CAIO (Chief AI Officer) / Human Centered AI Institute Representative
Mr. Masaya Mori
After working for a consulting firm and an internet company, he joined a professional firm and is engaged in supporting companies in the digital transformation field. He is a professor at Tohoku University, an advisor for the Collaborative Platform Development at the University of Tokyo, and an advisor for the Japan Deep Learning Association.
Generative AI 2.0
～From Prompt Engineering to Beyond～
Yuichi Itabashi (far left)
Digil Inc.
Keiji Taguchi (left)
Impress Corporation.
Jun Taguchi (right)
Macnica
Kosuke Onishi (far right)
Generative AI 2.0
～From Prompt Engineering to Beyond～
It has been about a year and a half since the introduction of generative AI. While companies have achieved some success in areas such as idea generation, translation, and summarization, they are aware of the challenges of taking the next step. What kind of changes are necessary to make more advanced use of generative AI?
In this session, entitled "Generative AI 2.0 - From Prompt Engineering to Beyond," we will invite people who have been pioneers in generative AI to discuss the use of in-house data through RAG (Search Augmented Generation) and the incorporation of generative AI into business processes. Let's think together about a concrete path toward the use of next-generation AI.
Rohto Pharmaceutical Co., Ltd.
Executive Officer CIO and Head of IT/AI Promotion Office
Mr. Yuichi Itabashi
Joined Fujifilm as a chemical engineer in 1985. In R&D, he developed a groundbreaking digital color printing technology using microcapsules. To commercialize the technology, he moved from R&D to the Imaging Division, and in the midst of the crisis of losing his main business due to the digitization of photography, he worked on business transformation through commercialization and marketing of digital cameras and digital printing systems, and also led the revival of the Instax business. He then contributed to the company's management transformation using digital technology as head of the Digital Marketing Office and ICT Strategy Office. In 2021, he joined Rohto Pharmaceutical and promoted the company's digital transformation and use of AI as Executive Officer CIO and Head of the IT/AI Promotion Office.
Digil Co., Ltd.
Representative Director and President
Mr. Keiji Taguchi
He has led strategic IT/DX initiatives at a major telecommunications company, a foreign information security company, a major retail company, and a real estate group company. He is currently engaged in support consulting for companies that continue to take on challenges, focusing on corporate transformation, DX promotion, and in-house organization construction.
Impress Corporation.
Editor-in-chief, IT Leaders Producer
Jun Taguchi
Joined Nikkei Business Publications in 1984. Covered the field of corporate information systems as a Nikkei Computer journalist. Served as editor-in-chief of Nikkei AI, Nikkei IT Professional, and Nikkei Computer. Left Nikkei Business Publications in 2008 and moved to the Impress Group, where he launched IT Leaders, a media outlet specializing in IT. Currently works as editor-in-chief and producer of IT Leaders at Impress. Other roles include chairman of the IT Skills Research Forum, director of the Japan Data Management Consortium, director of the Business System Initiative Association, director of the IT Education Business Association, member of the "DX Brands" committee, and hometown ambassador for Himeji City (born in Himeji City, Hyogo Prefecture).
Macnica
Deputy General Manager, Data & Application Division, Networks Company
Kosuke Ohnishi
Joined the company in 2005 as a new graduate. Belongs to the Networks Data & Applications Division. Since joining the company, he has been in charge of software products. He has been involved in data since 2013 and AI since 2020, and currently serves as deputy business manager, promoting business such as planning and market development of new products and services in the data and AI fields. We also discover and research overseas venture companies that handle cutting-edge products that meet market needs.
Annual growth achieved through generative AI
The challenge of reducing labor hours by 1.4 million hours
Yuta Okumura (left)
Nihon Kohden Corporation
Mr. Wataru Matsuzawa (center)
Macnica
Arisa Yamamoto (right)
The challenge of reducing labor hours by 1.4 million hours per year using generative AI
Nihon Kohden Corporation (hereinafter, Nihon Kohden) has decided to aim to "reduce 1.4 million man-hours per year" by utilizing generative AI as part of a company-wide profit reform. In this presentation, we will introduce the trajectory of the Business Strategy Department, which aims to create an environment where anyone can reduce man-hours by using generative AI, including how to handle a wide variety of internal data and how to make users adopt generative AI in order to effectively introduce and utilize it at the company.
Nihon Kohden Corporation
Leader, Generative AI Development Promotion Section, Business Strategy Department, Business Strategy Division
Mr. Yuta Okumura
In 2010, he joined Nihon Kohden Corporation, a medical equipment manufacturer. He developed the Holter ECG monitor as an electrical engineer for 11 years. After that, he was involved in process improvement based on TOC for the entire company. From 2023, he will lead the company-wide use of generative AI.
Nihon Kohden Corporation
Ogino Memorial Institute, AI Technology Development Division / Expert, Generative AI Development Promotion Division, Business Strategy Department, Business Strategy Division
Mr. Wataru Matsuzawa
Joined Nihon Kohden Corporation in 1997. Engaged in biosignal processing and medical AI development at the research institute.
Since 2023, he has been developing a generative AI system to improve the efficiency of internal operations.
The goal is to reduce labor hours by 1.4 million hours per year by fiscal 2026.
Macnica
Networks Company Data & Application Division Data & AI Platform Business Department Section 1
Arisa Yamamoto
Joined Macnica in 2021. He is engaged in proposing and supporting sales for the selection, implementation, and operation of data infrastructure that supports the utilization of data and AI, primarily for customers in the manufacturing industry.
Viewed from the perspective of the latest overseas technology
“Generative AI using in-house data
The road to application realization
Seio Ohara
"The path to realizing generative AI applications using in-house data" from the perspective of the latest overseas technologies
The realization of generative AI applications using in-house data is attractive to many companies, but the road to achieving this is not always smooth. While the importance of fine tuning and RLHF (Reinforcement Learning from Human Feedback) has been pointed out, in recent years, there are limitations to the accuracy of RAG (Retrieval-Augmented Generation) alone, and the use of it in combination with Knowledge Graph has attracted attention.
In this seminar, we will look back at how to create generative AI applications using in-house data, based on cutting-edge information from overseas, and introduce common challenges and the technologies that have emerged as solutions.
We hope you will take advantage of this opportunity to learn about the latest technological trends for introducing AI into enterprise environments.
Macnica Networks USA
Vice President
Seio Ohara
Started his career as an engineer, gained experience in sales, product manager, and launching new products, and currently works as a business developer in Silicon Valley, where he discovers and launches new products.
Accelerate your business by improving customer experience! A DX support specialist discusses the issue of "disconnected customer data" and how to solve it
Mr. Masaoki Ohashi (left)
Macnica
Daichi Seshita (center)
Macnica
Masashi Ikeda (right)
Accelerate your business by improving customer experience!
A DX support specialist discusses the issue of "fragmented customer data" and how to solve it
In today's world, life revolves around web services, and user expectations are rising. For this reason, many companies are focusing on utilizing customer data and improving services, aiming to "improve customer experience" as the key to growing their business. In this session, we welcome Mr. Ohashi from Flect, who will explain examples of companies that have worked to improve customer experience, and the best practices he felt through these examples. What is the "fragmented customer data" that companies are actually facing? This session is full of hints for improving business value. Please take this opportunity to participate.
Flect Co., Ltd.
Board Director and General Manager of Cloud Integration Division
Mr. Masaoki Ohashi
In 2004, he joined Sony Ericsson Mobile Communications, where he was involved in developing middleware for mobile phones. In 2007, he joined Flect, and became Board Director in 2009. He is in charge of the cloud integration business and has led its growth.
Macnica
Networks Company Data & Application Division
Daichi Seshita
Since 2021, he has been involved in zero trust-related work, providing support from upstream to operations.
After gaining experience as a systems engineer, he joined the Data field this year and is currently working as a dedicated sales engineer for Databricks, working hard to promote the penetration of a platform that makes Data+AI possible.
Macnica
Networks Company Security Division 3
Masashi Ikeda
Joined Macnica in February 2020. Started as a product sales representative for security products. Currently working in the ID field as a product manager for Okta Customer Identity Cloud.
Only one year left until the 2025 cliff!
- Advancing Japan's Digital Transformation with the help of IT powerhouse India -
Mr. Yoshiro Inoue (left)
Celebal Technology Co., Ltd.
Shino Kawagoe (center)
Macnica
Satoshi Otaki (right)
Only one year left until the 2025 cliff!
- Advancing Japan's Digital Transformation with the help of IT powerhouse India -
The term "2025 Cliff" was first used in the "DX Report" published by the Ministry of Economy, Trade and Industry in 2018. Are you ready?
In this session, together with Celebal Technologies, a technology company from India, which has now become an IT powerhouse, we will discuss the current state of Japan's DX when viewed from a global perspective, data technology, and global examples.
Celebal Technology Co., Ltd.
Senior Sales Manager
Mr. Yoshiro Inoue
He has over 30 years of experience in sales of networks, security, middleware, and cloud. He joined Celebal Technology in July 2023 and is mainly responsible for supporting the construction of data platform environments centered on Databricks and sales of migration services to Databricks.
Celebal Technology Co., Ltd.
Associate Consultant Sales
Shino Kawagoe
He studied Indian language and culture and went to Delhi to study abroad. After working for a major Japanese company, he participated in the launch of Celebal Technologies' Japanese subsidiary in 2022. He plays a central role in communication and relationship building with offshore companies. In May of this year, he spoke at a Databricks webinar and is expanding his activities in the sales and marketing fields.
Macnica
Networks Company Data & Application Division Data & AI Platform Business Department Manager
Satoshi Ohtaki
Since 2000, he has worked as a systems engineer at an SIer, supporting everything from upstream proposals to operations for networks, mobile utilization, and security. Since 2016, he has led the account engineering team and worked as a systems engineer for targeted attack countermeasure products at Macnica. He currently supports customers in utilizing data with products in the Data and AI fields.
What is needed to build and improve SCM in the VUCA era and look to 2030?
Three points
Shota Okazaki (far left)
BrainPad Inc.
Ryo Hayakawa (left)
BrainPad Inc.
Yusuke Awai (center)
Macnica
Norikazu Miyagi (right)
Macnica
Ryosuke Yoshida (far right)
Three points necessary for constructing and enhancing SCM with an eye on 2030 to survive the VUCA era
In this era of rapid global change and uncertainty about the future, establishing and enhancing supply chain management (SCM), particularly in the manufacturing industry, can be said to be an important measure.
In this session, Macnica, a company that provides technology-based consulting, and BrainPad, a pioneer in data utilization, will discuss key points for building and enhancing SCM with an eye to the future from three management perspectives.
① Agile data management that captures uncertainty
②Global risk management
3) Knowledge management for sustainable management
This book will be especially useful for those who will be building and enhancing SCM in the future, so we hope you enjoy it.
BrainPad Inc.
Senior Manager, Analytics Consulting Unit
Mr. Shota Okazaki
As a data scientist, he is in charge of projects in a wide range of industries using prediction and optimization techniques, and has recently been focusing on supply chain optimization projects.
BrainPad Inc.
Sales & Marketing Unit Enterprise Sales Lead
Mr. Ryo Hayakawa
As a sales lead for an account unit that mainly focuses on manufacturing and logistics companies, he participates in the creation and promotion of a wide range of data utilization projects.
BrainPad Inc.
Sales & Marketing Unit Alliance Lead
Mr. Yusuke Awai
After working at a specialized trading company, he promoted business as a business development manager at an IoT x AI startup for the manufacturing industry. After that, he joined Brainpad after going independent. Currently engaged in improving the value provided through collaboration with partner companies.
Macnica
General Manager, DX Consulting Division
Norikazu Miyagi
In order to promote initiatives that will lead to a digital future, he oversees the DX consulting department and also serves as an outside Board Director of Sustainable Pavilion 2025 Co., Ltd., which aims to continue using Osaka-Kansai Expo content with the web3 development office manager and Yoichi Ochiai.
Macnica
Assistant Manager, New Business Emergence Consulting Office, DX Consulting Division
Ryosuke Yoshida
He has been providing procurement and development support to Japanese industrial machinery and electrical manufacturers, mainly in the semiconductor business, for over 10 years, and is currently using that experience to support manufacturing companies in everything from formulating to implementing their DX strategies.
A successful strategy for using generative AI
~Risk management techniques~
Daichi Kakinuma
A successful strategy for using generative AI
~Risk management techniques~
Are you familiar with the term AI TRiSM, which has been gaining attention recently?
AI TRiSM is an abbreviation of Trust, Risk, and Security Management, and is an initiative to address AI risks and increase the reliability of AI.
As the adoption of AI progresses, various risks are becoming apparent, such as malicious attacks on AI models and unintended information leaks, making how to ensure the security and reliability of AI a major issue.
In this seminar, we will specifically introduce the risks contained in AI models and training data, and provide a detailed explanation of the latest measures and methods for protecting data privacy and improving the reliability of AI models.
Please join us for this opportunity to learn cutting-edge technologies for safely utilizing generative AI and enhance your business competitiveness.
Macnica
Networks Company Data & Application Division Data & AI Platform Business Department Section 2
Daichi Kakinuma
In the past, he worked as a sales engineer, support engineer, and training instructor for products, mainly data analysis platform products. He is currently engaged in sales activities in the fields of AI, machine learning, and data utilization.
Tips for introducing generative AI into your company, learning from common "failure patterns"
~The path to transforming technical support through LLM~
Kyoichi Sugimoto
Tips for introducing generative AI into your company, learning from common "failure patterns"
~The path to transforming technical support through LLM~
"We want to utilize generative AI technology to improve the efficiency of our operations."
These needs are increasing against the backdrop of the rapid development of generative AI in recent years. However, there are several hurdles to overcome in terms of system and business application in order to introduce and implement generative AI into actual business operations. In this presentation, we will provide hints on using generative AI, including common failure patterns and solutions, based on a case study of LLM use in a department in charge of customer inquiries about products handled.
Macnica
Networks Company Data & Application Division 1st Technology Department 1st Section
Mr. Kyoichi Sugimoto
Joined Macnica in 2021. He is in charge of technical support and customer training for integrated log management platform products. He currently coordinates the entire support team while also promoting customer and internal support work reform activities using generative AI.
Data structuring in the age of generative AI
- Image and text extraction practice using multimodal LLM -
Kazutaka Ikeda
Data structuring in the age of generative AI
- Image and text extraction practice using multimodal LLM -
One of the applications of generative AI, which has made rapid progress in recent years, is the extraction of structured data from unstructured data such as images and text. In this session, we will introduce a concrete example of the implementation of information extraction from fashion product images using multimodal LLM, and explain how to solve the problems of efficiency and personal dependency in creating structured data manually.
Macnica
Networks Company AI Business Department 2nd Division Chief
Mr. Kazutaka Ikeda
He is currently working in Bangalore, the IT city of India, developing AI products using large-scale language models (LLMs) and other technologies. He is responsible for everything from project management to requirements definition and implementation, and is driving the resolution of business issues. He has a track record of placing 6th alone and winning a solo gold medal at the global AI competition Kaggle.
Generative AI for utilizing confidential data that is difficult to use on the cloud
- Thinking about local LLM using NVIDIA as an example -
Kawabe Kuga
Generative AI for utilizing confidential data that is difficult to use on the cloud
- Thinking about local LLM using NVIDIA as an example -
It has been about two years since the appearance of ChatGPT, which shocked the world. Generative AI is at the center of the technology trend, and various companies are considering using generative AI.
On the other hand, due to data protection considerations, cloud services do not allow the use of valuable data such as personal and confidential information, and in some cases, the use of generative AI does not progress as expected.
In this session, we will discuss the current status of use of generative AI, as well as the challenges it faces, and discuss the key points to consider when building a local LLM in an on-premises environment using NVIDIA's SDK.
Macnica
Clavis Company, 1st Technology Division, 4th Technology Department, 1st Section
Mr. Soga Kawabe
He joined Macnica in 2023. He is currently promoting NVIDIA's embedded GPU Jetson and software development tools related to generative AI to companies in order to solve customer problems.
Generative AI
At the forefront of business process transformation
The key to adoption is creating a system for co-creation with users!
Masayuki Hayashi
At the forefront of business process transformation using generative AI
The key to adoption is creating a system for co-creation with users!
Generative AI is a powerful tool for streamlining and transforming business processes, but there are many hurdles to overcome when it comes to implementing it. In this session, we will explain the specific methods for using generative AI in business operations while clarifying the reasons and issues that have hindered its implementation, such as the reluctance of users to use generative AI and the challenges of using internal data. We will also explain the key points for maximizing the potential of generative AI, suggesting effective ways to use it, and promoting its use in business operations.
Macnica
General Manager, Incubation Office, New Business Headquarters
Mr. Masayuki Hayashi
After gaining experience in promoting AI development projects at major core software companies and e-commerce platform providers, he joined Macnica in 2020. Since 2023, he has been involved in promoting the company's generative AI project and developing a platform for utilizing generative AI for customers.
The key is in the edge!
What is needed to utilize data in the future?
"Collection" and "Analysis"
Tomoki Kawamura
The key is at the "edge"! "Collection" and "analysis" are essential for future data utilization
In today's world, where data exists in various places and in large quantities, many customers are likely to face the following challenges.
"We are not able to collect the data necessary to utilize it for business purposes." "There is a lot of noise in the data, so we are not able to analyze it effectively."
"Edge" is the key to solving these issues. Edge refers to a location close to the data source. In the future, it will be important to "collect" more types of data from the edge and "analyze" the data on the edge side.
In this session, we will explain how the "edge" can be used to solve modern data utilization issues, including specific use cases and solutions.
Macnica
Networks Company Data & Application Division 1st Technology Department 2nd Section Deputy Section Manager
Mr. Tomoki Kawamura
His main duties are proposing data utilization related ideas and planning and developing services. He is skilled at problem solving and planning based on his wide range of experience, and in the past he has been involved in activities such as discovering new products and planning and managing cyber attack/defense exercises for companies.
Event summary
- Name
- Macnica Data・AI Forum 2024 Autumn (MDAF2024 Autumn)
- event date
- October 7th (Monday) to October 11th (Friday), 2024
- Venue
- online
- Entry fee
Free/Pre-registration required
*We reserve the right to refuse your participation if you apply with a free email address, if you are a student, if you are a competitor, if you are a company that deals with competing products, or if there are circumstances that the Company deems inappropriate to participate in this seminar. There are cases.
- Organizer
- Macnica
- Recommended viewing environment
-
＜PC＞
- Windows：Chrome、Edge（Chromium）
- Mac：Chrome、Safari
*Correspondence regarding each latest version
*Not compatible with Firefox, Internet Explorer, etc.
<Smartphone>
- iPhone：Chrome、Safari
- Android：Chrome
