When and at what time will the seminar be held online?

It will be held on Tuesday, April 21, 2026, from 13:00 to 14:00.

Who is the host of this manufacturing seminar?

NEC NEXSolutions is the host organizing the seminar.

During which period is the archive distribution of the seminar planned to be available?

It is planned from Wednesday, April 22, 2026, to Wednesday, March 31, 2027.

What challenges are manufacturing sites facing according to the seminar details?

They face supply chain disruptions, rising raw material costs, skilled labor shortages, and delayed decision-making.

What excuses do companies make that cause them to hesitate to adopt Generative AI?

They hesitate because they lack learning data or think they cannot use it unless the data is clean.

AI News NQ Analysis

[April 21 (Tue) Held] "Generating AI to Transform Manufacturing: New Production Management and Future Strategies" Seminar

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N1 Content Completeness 5

AI Summary (NQ-processed)

NEC NEXSolutions is hosting an online seminar on April 21, 2026, focused on transforming manufacturing through Generative AI. The event will cover practical AI adoption steps, data preparation, and system integration to address industry challenges like labor shortages and data fragmentation, with an archive available afterward.

AI Analysis

Frequently Asked Questions

Q: When and at what time will the seminar be held online?: A: It will be held on Tuesday, April 21, 2026, from 13:00 to 14:00.
Q: Who is the host of this manufacturing seminar?: A: NEC NEXSolutions is the host organizing the seminar.
Q: During which period is the archive distribution of the seminar planned to be available?: A: It is planned from Wednesday, April 22, 2026, to Wednesday, March 31, 2027.
Q: What challenges are manufacturing sites facing according to the seminar details?: A: They face supply chain disruptions, rising raw material costs, skilled labor shortages, and delayed decision-making.
Q: What excuses do companies make that cause them to hesitate to adopt Generative AI?: A: They hesitate because they lack learning data or think they cannot use it unless the data is clean.