sgai editorial interpretation · Data updated 2026-05-02

🔬 Research Quality

Is original research coming out?

Headline
Per-capita papers #1 globally
Benchmark
NTU AI #3 (after MIT/CMU) · NUS AI #9
Trend
→ → Flat

Target Progress

SEA-LION v4 (11 languages, 4B–33B params) + 100E (100+ projects) + ICLR 2025 hosted

Third-Party Ranking Anchors

Editorial Interpretation

Volume and university rankings are strong — per-capita papers #1, NTU AI #3, NUS #9, ICLR 2025 hosted, SEA-LION is one of the few non-US/UK/China foundation models at scale. But frontier-grade originality (FAIR / DeepMind tier) still trails by a step: first-author share at top venues, signature works with >1000 citations, market share of self-developed foundation models — all behind.

⚠️ Key Shortcoming

First-author share at top venues, citation counts, and self-developed foundation-model market share all trail by a step. Top PhD outflow is high. Research-to-industry transfer is strong for in-house enterprise use but weak as international export — no OpenAI / Anthropic-tier spinout. International visibility hinges on a small number of star professors.

Full Data

MetricValueSource / Date
AI papers per capita#1 globally (250 papers per million people, 2022)Wiley, 2024-09 ↗
NTU AI research ranking#3 globally (after MIT and CMU)Introl, 2025-08 ↗
NUS AI academic reputation#9 globallyIntrol, 2025-08 ↗
SEA-LION large language modelv4, 11+ languages, 4B-33B parametersAISG, 2025 ↗
100 Experiments100+ AI projects completed (2018-2025, archived)AISG ↗
ICLR 2025Hosted in SingaporeICLR, 2025 ↗
DBS AI models800+ models, 350+ use cases, S$750M economic value generated in 2024Introl, 2025-08 ↗