Realtime AI News
Shandong Releases Seven Vertical-Domain AI Models Covering Equipment, Chemicals and More
At an AI vertical-model event in Jinan on Oct. 14, Shandong released seven industry-specific large models — Hairuo, Tianzhi, Xingji, Yunding, Xinggang, Shangzhi and Qizhi Kongming — spanning high-end equipment, chemicals, light industry, metallurgy, mining and port logistics. Provincial officials said 389 models have passed third-party evaluation after 100 priority vertical models were selected for promotion earlier this year.
Shandong released seven vertical-domain AI models at a dedicated event in Jinan on Oct. 14, according to China News Service. The models — Hairuo, Tianzhi, Xingji, Yunding, Xinggang, Shangzhi and Qizhi Kongming — cover key sectors including high-end equipment, chemicals, light industry, metallurgy, mining and port logistics.
Chen Fei, head of the Shandong Provincial Department of Industry and Information Technology, said the province has focused on the vertical-domain intelligence track, treating “discovering, cultivating and promoting large models” as a key lever for AI development.
Chen said 389 models have so far passed third-party evaluation in the province. In the first half of this year, Shandong selected and published 100 priority vertical models for promotion, weighing technical performance, economic benefit, social recognition, industry track and real deployments — and the seven newly released models were chosen on top of that base.
One of them, COSMOPlat's Tianzhi industrial model, was described as China's first vertical model built on a national-level dual-cross industrial internet platform. Chen Lucheng, chairman of COSMOPlat IoT Technology, said the company uses Tianzhi as a base to redefine the capability core of the industrial internet with AI, splitting its AI-native organizational upgrade into three levels.
At the factory level, a “plant-manager digital human” coordinates agents for flexible line changeover, equipment management and quality; at the enterprise level, a “CEO digital human” anchors agents for metric definition, ontology governance and business decisions; and in energy, an “energy-station digital human” links scheduling, zero-carbon and virtual power plant agents.
Taken together, the seven models reflect a local-government approach that favors deep vertical work over stacking general-purpose models, using third-party evaluation and a priority-promotion list as filters. What to watch next is how these models perform in real deployments across Shandong's equipment and chemicals industries, and whether the approach yields a replicable commercialization path.
Why it matters
A provincial government releasing vetted vertical models at scale signals that China's model race is shifting from general capability toward industrial deployment and regional ecosystems.
Nearby Updates
All10/14, 19:00
Scimplify raises $25M to take on critical materials with AI
Scimplify has raised $25 million to attack China's grip on critical materials using AI, according to TechCrunch. The company's annualized revenue run rate has tripled to $200 million as it eyes U.S. expansion.
10/14, 19:05
Anthropic Opens Singapore Office and Signs AI Agreement
Channel NewsAsia reports that Anthropic has opened an office in Singapore and signed an AI agreement there. The move extends the AI lab's push into Southeast Asia, where clearer regulation and high enterprise digitisation make the city-state a common landing point.
10/14, 19:42
Pi 1.0 Coding Agent Goes Open Source, Claiming 40% Token Savings
Pi 1.0, a coding agent, has been released as open source, with coverage claiming it cuts token consumption by around 40%. Because token usage directly drives the cost of running coding agents, that figure has become the release's headline selling point.
10/14, 19:47
Anthropic executive warns open-source AI models carry more safety risk
An Anthropic executive has publicly warned that open-source AI models carry more safety risk, according to Quartz. The statement puts the open-weight safety debate back in the spotlight and raises the question of whether regulators should treat open and closed models differently.