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Unique Friend | Integer Intelligence’s Lin Qunshu: Data Engineering Is Worth Going All-In on in the AI Era

Unique Research · Insight / Unique Friend Q&A · January 18, 2024 · Guest: Lin Qunshu, founder & CEO, Integer Intelligence (整数智能)

Inventory type remains insight (Unique Friend series — not partner welcome).

Guest

Lin Qunshu — founder & CEO, Integer Intelligence; PhD Computer Science, Zhejiang University; Forbes China 30 Under 30 (2023).

Integer Intelligence IT (Hangzhou) spun out of Zhejiang University’s Computer Innovation Technology Research Institute — aims to be the data navigator for the AI industry. Member of China AI Industry Development Alliance, ASAM, and Zhejiang AI Industry Tech Alliance. Offers intelligent data-engineering platform ABAVA Platform and dataset-build service ACE Service for dozens of scenes: autonomous driving, AIGC, smart healthcare, security, smart city, industrial manufacturing, speech, public administration. 1,000+ top tech firms and labs worldwide; dozens of IP assets; frequent contributor to AI standards and white papers.

Q&A

1. Product and core scenes?
ABAVA Platform + ACE Service for data needs across autonomous driving, AIGC, healthcare, security, smart city, industry, speech, public admin and more.

2. R&D / GTM — 2023?
Strong products in intelligent annotation tooling and frontier 4D annotation — recognized and paid by autonomous-driving customers.

3. Opportunities vs. past waves?
From a data-services view, the AIGC wave brings large demand for text and multimodal data procurement.

4. Are LLMs still too weak?
Yes — hallucination blocks serious / high-accuracy scenes. Selectively pick scenes that today’s tech can land — just as pre-AGI AI still shipped well in face-recognition security.

5. 2024 tech to watch?
Multimodal capability.

1 CN image; attach on ingest. Signup CTA in CN omitted. Shortest piece in batch (~629 CJK); Q&A preserved without padding.

— END —

Editorial English edition by Unique Research, published on UniqueCapital on January 18, 2024. This translation is based on an earlier Chinese article; the Chinese source is credited separately and is not treated as a line-by-line mirror.

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