Tomorrow
Academia

Beijing, China

Tsinghua University

Most of China's open-weight model lineage runs through Tsinghua labs and their spinouts — the supply side of the China column in this catalog.

AIRoboticsChipsOfficial site
2 key findings0 timeline milestones2 sources to follow

Key findings

  1. 2019

    Tianjic — hybrid neuromorphic chip

    Luping Shi and team

    A single chip running both spiking and artificial neural networks, demonstrated on an autonomous bicycle. Nature cover.

    Why it matters here · The clearest signal that China's accelerator strategy includes non-GPU architectures, not just GPU substitution.

  2. 2021

    GLM — a bilingual pretraining objective

    Du, Tang et al., KEG

    An autoregressive blank-infilling objective unifying understanding and generation, released with open weights.

    Why it matters here · The base of the GLM/Zhipu product family tracked here, and a template for other Chinese open releases.

What to follow

Institute for AI Industry Research (AIR)

Research lab · Continuous

Applied AI research bridging Tsinghua and Chinese industry, including autonomous driving and health.

Knowledge Engineering Group (KEG)

Research lab · Continuous

The GLM model family and the research line behind Zhipu AI.

How to cite this page

Free to cite and reuse under CC BY 4.0. Permalink: https://tomorrow.aliensquad.ai/academia/tsinghua

APA
Tomorrow. (2026). Tsinghua University — key findings and research feeds [Research tracker entry]. AlienSquad. Retrieved 2026-09-17, from https://tomorrow.aliensquad.ai/academia/tsinghua
BibTeX
@misc{tomorrow-academia-tsinghua,
  author       = {{Tomorrow}},
  title        = {Tsinghua University — key findings and research feeds},
  year         = {2026},
  publisher    = {AlienSquad},
  howpublished = {\url{https://tomorrow.aliensquad.ai/academia/tsinghua}},
  note         = {Accessed: 2026-09-17}
}