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HKU and Getech Launch Industrial AI Joint Laboratory to Advance AI Innovation Through Industry-Academia Collaboration

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HONG KONG, April 18, 2025 /PRNewswire/ — The University of Hong Kong (HKU) and Getech Technology, a leading industrial AI solutions provider under TCL Industries, signed an agreement on April 16, 2025, to establish the HKU-Getech Industrial AI Joint Laboratory. Under the agreement, Getech will invest tens of millions of Hong Kong Dollars over the next five years to fund the lab’s operations, focusing on industrial AI innovation and real-world applications. As part of the collaboration, HKU’s Vice-President (Research) Professor Zuo-Jun (Max) Shen has been appointed as Getech’s Honorary Chief Scientist and will provide strategic R&D guidance and advice. The signing ceremony, held at the HKU campus, was attended by HKU President Professor Xiang Zhang and TCL Founder and Chairman Dongsheng Li, both of whom delivered keynote addresses at the event. Other attendees included Prof. Shen, Associate Vice-President (Research and Innovation), Professor Stephanie Kwai Yee Ma, as well as TCL Industries Vice President and Getech CEO Jun He.

The collaboration will draw on HKU’s research expertise and advanced capabilities in AI to accelerate the development of commercially viable, high-quality industrial AI technologies. The partnership aims to support the commercialization of academic research outcomes and foster growth in the industrial AI sector. Jointly managed by both parties, with Professor Shen serving as Director, the lab will focus on research into innovation and real-world applications of industrial AI, including optimization engines for supply chain operations; AMHS intelligent material handling and scheduling systems; the deployment of AI agents and hyper-automation; and the development of large language models (LLMs) and industrial big data platforms. The initial project, currently in the planning stage, will involve the development of an intelligent AMHS handling and scheduling system. HKU’s research team will collaborate with Getech Technology’s AMHS engineers to advance AI algorithms capable of managing over 1,000 overhead hoist transports (OHTs), with the goal of enhancing the performance of intelligent equipment. The planned research efforts align with Getech Technology’s vision of empowering smarter industries, while also underscoring HKU’s commitment to enhancing its competitiveness in the AI sector.

In his opening remarks, Prof. Zhang expressed his optimism about the partnership, “The formal agreement with TCL marks the official launch of our collaborative efforts in AI, with particular emphasis on industrial applications. HKU has made significant strides in foundational research across disciplines, backed by a cohort of distinguished researchers. We are now committed to translating these academic results into practical industrial applications and commercialization with the aim of advancing industrial development through new and emerging technologies.”

LI Dongsheng, Founder and Chairman of TCL, expressed strong support for the collaboration. He commented, “AI is a strategic priority for TCL. In 2024 alone, our AI initiatives delivered a measurable financial impact of 540 million yuan. The establishment of the lab led by Prof. Shen represents a milestone in TCL’s AI strategic roadmap.”

During the project briefing session, Mr. He outlined the lab’s framework and key initiatives planned for Phase 1. He said, “Getech is aligned with the Hong Kong government’s development roadmap by establishing our R&D center here to accelerate innovation in industrial AI. This initiative aims to position Hong Kong as a new international hub for supply chain management with the mission of driving intelligent transformation across both Chinese and global manufacturing sectors. In addition, the partnership lays the groundwork for the continued integration of industrial resources as we pursue smart manufacturing opportunities worldwide.”

In his concluding remarks, Prof. Shen, widely recognized as a leading researcher in his field, stated, “The HKU-TCL partnership represents a seminal advancement in AI, particularly for industrial applications. As AI emerges as the defining technological paradigm, HKU has remained at the forefront through initiatives such as establishing the School of Computing and Data Science to pioneer cutting-edge research. Our vision extends beyond foundational research to cross-disciplinary AI integration with global educational impact. Under Mr. Li’s leadership, TCL has consistently demonstrated its role as a ‘Technology Change Leader’ through sustained innovation. The collaboration will combine HKU’s academic excellence with TCL’s industrial expertise to create a laboratory with global impact that will drive progress in manufacturing and supply chains worldwide. As the lab’s director, I will work closely with TCL while engaging HKU faculty, students, and investors to collectively shape the future of industrial AI.”

Since the early stages of this AI wave, the Hong Kong government has demonstrated forward-looking leadership. The Hong Kong Innovation and Technology Development Blueprint published in 2022 identified AI as a priority sector, establishing strategic directives and action plans to strengthen the local AI ecosystem. Building on this vision, the 2025/2026 Budget proposed a HK$1 billion allocation to establish the Hong Kong AI Research Institute and approved five flagship projects led by local universities and research organizations to accelerate the development of several LLMs.

With the establishment of the joint lab, HKU will leverage its business partners’ real-world operational environments and R&D funding to sharpen its focus on addressing industrial needs and challenges through new technologies and applied research. Capitalizing on Hong Kong’s strategic position as a hub in Southeast Asia, the lab’s “technology R&D – scenario testing – global deployment” model will provide Southeast Asian manufacturers with replicable intelligent transformation pathways. Furthermore, Hong Kong’s international talent pool will enhance the lab’s capabilities in implementing depth-focused projects. These initiatives are expected to generate a substantial number of research roles for Hong Kong and neighboring areas, bringing together leading researchers and R&D engineers to build a strong industrial AI talent pipeline and reinforce the foundational ecosystem for AI-driven industrial transformation.

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SOURCE Getech Technology Co., Ltd

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JAMS Launches AI for Enterprise Job Scheduling: JAX and JAMS MCP, on the Model You Choose

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July 24, 2026

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A new AI agent and an open-standard connector let IT teams query, diagnose, and manage automation in plain language, on the model they choose, with operational data staying inside their own network

LONDON, July 24, 2026 /PRNewswire/ — JAMS Software, an orchestration solution for scheduled and event-driven automation, today announced the general availability of two AI capabilities for enterprise job scheduling: JAX, an AI agent built into the JAMS Web Client, and JAMS MCP, a connector built on the open Model Context Protocol standard that brings JAMS into external AI coding tools. Both capabilities ship at no additional cost as part of JAMS Web.

Automation environments grow faster than the teams that run them. Jobs multiply across SQL Server, Azure Data Factory, Airflow, SAP, JDE, and Banner, and when one fails, finding the root cause often means searching several consoles at once, frequently outside business hours. At the same time, IT leaders carry pressure to adopt AI while staying accountable for where operational data goes. JAX and JAMS MCP close both gaps together.

Full details on how JAX and JAMS MCP work, including the control model behind every action, are available at jamsscheduler.com/product/ai.

JAX is an AI agent that runs inside the JAMS Web Client. It finds jobs, troubleshoots failures, and answers how-to questions in plain language, with each response grounded in the JAMS user guide and checked against a built-in glossary. JAX acts only when a user asks it to. Reads flow freely, and every write action pauses for the user’s explicit approval before it runs. JAX does not learn between sessions, and conversations are not retained on the server.

JAMS MCP is a connector, built on the open Model Context Protocol standard, that brings JAMS into the AI tools engineering teams already use, including Cursor, VS Code with Copilot, Claude Code, Claude Desktop, and Codex. Users query jobs, investigate failures, and manage runs in plain language without leaving their tool.

Both capabilities run inside the customer’s own network and act as the signed-in user, with that user’s exact JAMS permissions. There is no elevated AI account: whatever a user cannot do in the JAMS interface, JAX and JAMS MCP cannot do on that user’s behalf. Every JAX and MCP operation is recorded in its own dedicated log, and changes made through the JAMS API land in the JAMS audit trail like any other change. Customers choose their own AI model, whether a commercial provider such as OpenAI or Anthropic or a model running entirely on their own hardware, and JAMS never trains on customer data. In the current release, neither feature edits or deletes a job, folder, schedule, or agent definition. For teams that must keep operational data within a defined boundary, JAX runs on a local model entirely inside the customer’s own network, so nothing leaves at all.

“Adopting AI usually means giving something up, most often visibility into where your data goes,” said Pete Hegland, Chief Executive Officer of JAMS Software. “We built JAX and JAMS MCP so that trade does not have to happen. Every action runs as the signed-in user, every change waits for approval, and the model itself can run entirely inside your own network.”

“IT teams across the United Kingdom and EMEA tell us the same thing: they want the benefit of AI without losing sight of where their data goes,” said Greg McLaughlin, Account Executive for EMEA at JAMS Software. “JAX and JAMS MCP let them keep operational data inside their own network and still get answers in plain language. That combination is what makes this practical for the teams I work with.”

JAX and JAMS MCP are available now to all JAMS Web customers across the United Kingdom and EMEA, with no separate licence, SKU, or additional cost. AI-assisted creation of new jobs and workflows from a plain-language description is on the roadmap for a future release, gated by the same approvals and permissions as every other action.

Learn how JAX and JAMS MCP work at https://jamsscheduler.com/product/ai.

Fast facts

JAX is an AI agent built into the JAMS Web Client for job scheduling and workflow automation.JAMS MCP is a connector built on the open Model Context Protocol standard, for Cursor, VS Code with Copilot, Claude Code, Claude Desktop, and Codex.Both act as the signed-in user, with that user’s exact JAMS permissions, and there is no elevated AI account.Customers choose the AI model, including a local model that runs entirely inside their own network.JAMS never trains on customer data.Both are available now at no additional cost as part of JAMS Web.

About JAMS Software

Founded in 1987, JAMS Software is an orchestration solution that helps IT teams centralize, automate, and manage scheduled and event-driven jobs across complex, hybrid environments. Over 850 customers rely on JAMS to run their automated workloads. JAMS Software, LLC is headquartered at 108 Patriot Drive, Suite A, Middletown, DE 19709.

Media Contact
Bobby Schmidt, Vice President of Marketing
press@jamssoftware.com
800.261.4267

 

 

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View original content:https://www.prnewswire.co.uk/news-releases/jams-launches-ai-for-enterprise-job-scheduling-jax-and-jams-mcp-on-the-model-you-choose-302833908.html

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Video: CNPC offers green chemical answer

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July 24, 2026

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BEIJING, July 24, 2026 /PRNewswire/ — A news report from chinadaily.com.cn:

Located on the edge of the Taklamakan Desert in Northwest China’s Xinjiang Uygur autonomous region, the Tarim 1.2 MTA Phase II Ethylene Project and its supporting green and low-carbon demonstration facility of PetroChina Dushanzi Petrochemical Company, a subsidiary of China National Petroleum Corporation, are offering a new example of China’s low-carbon industrial transformation.

Watch the video to discover how CNPC is exploring a cleaner and more circular future for the industry.

View original content to download multimedia:https://www.prnewswire.com/apac/news-releases/video-cnpc-offers-green-chemical-answer-302834036.html

SOURCE chinadaily.com.cn

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Shanghai Electric showcases embodied intelligence robot matrix and AI-native smart factory solutions at WAIC 2026

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July 24, 2026

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Featuring humanoid robots with 41 degrees of freedom, pipe‑inspection robots with ±1mm positioning accuracy, and 51 industrial‑grade AI agents

SHANGHAI, July 24, 2026 /PRNewswire/ — Operations in high-end equipment manufacturing often involve confined spaces, complex objects, and fine manipulation tasks that demand sustained and stable precision. At the recent 2026 World Artificial Intelligence Conference and High-Level Meeting on Global AI Governance (WAIC 2026), Shanghai Electric (SEHK: 02727, SSE: 601727) showcased its comprehensive portfolio of embodied intelligence solutions tailored to a range of industrial scenarios.

Themed “AI for All: Smart Squad, Shining Without Limits,” Shanghai Electric highlighted its capabilities across embodied AI robots, robot core components, and AI-native smart factory solutions, demonstrating end-to-end capabilities spanning complete robot systems, critical parts, industrial software, and smart factory architecture.

“The true value of embodied intelligence lies in understanding real industrial tasks: combining the strength, precision, and stability of machines with human experience and judgment to drive a genuine paradigm of ‘machine-assisted, human-machine collaboration,'” said Wang Chunlei, deputy general manager of the Robotics Business Unit at Shanghai Electric Automation Group.

Shanghai Electric’s robotics portfolio covers five key industrial scenarios: connector insertion, electrical operations, flexible sorting, intelligent assembly, and pipe processing. Highlights include:

“SUYUAN” bipedal humanoid robot: With 41 degrees of freedom for enhanced mobility, it is equipped with a multimodal visual sensing system on the head and torso, along with a dual-battery hot-swap system. It is well-suited for inspection, material handling, and assembly tasks.”TUOYUAN” industrial wheeled humanoid robot: Powered by an embodied intelligence foundation model and force-position hybrid control, it is capable of multi-spec connector insertion, material sorting, and loading/unloading of automotive sheet metal parts.”Mermaid” bionic wheeled humanoid robot: Capable of autonomously identifying buttons, knobs, and air switches, it generates real-time operation paths.Autonomous pipe inner-wall chamfering robot: Designed for confined spaces, it can position and process thousands of hole edges with accuracy within 1 millimeter while transmitting data in real time.

Shanghai Electric also showcased its portfolio of core components ranging from power-output to end effectors. Among them, the planetary roller screw offers more than three times the load capacity of traditional ball screws, while the DexHand dexterous hand is designed to meet diverse gripping and manipulation requirements.

Shanghai Electric launched 51 AI models and agents under its “StarCloud Intelligent Manufacturing” series across three domains: R&D and design, production and manufacturing, and operations and maintenance—covering critical equipment processes such as process optimization and wind power facility maintenance.

These industrial agents are embedded in robotic decision-making systems and the operational logic of AI-native smart factories, transforming industrial expertise into digitized, reusable capabilities. They support production-line scheduling, quality inspection, and predictive maintenance, driving the evolution of manufacturing systems from experience-driven to data-driven operations.

Shanghai Electric also released the “AI-Native Smart Factory Technology White Paper,” proposing an active evolution architecture that enables real‑time, closed‑loop optimization of production data, giving the factory self‑perception, self‑decision, and self‑execution capabilities. Built on First Principles, the AI‑native smart factory vertically integrates process flows, industrial software, agents, and smart equipment to dismantle traditional hierarchies while horizontally bridging data silos. The architecture features three core layers: the AI factory brain as the “control center,” industrial agents and embodied robots as the “execution network,” and the physical twin as the “digital mirror.”

Leveraging its deep industrial expertise and comprehensive solution capabilities, Shanghai Electric will continue to drive the implementation of AI in industrial settings, tackle technical challenges facing embodied intelligence in complex scenarios, accelerate the large‑scale deployment of AI‑native smart factories, and deliver replicable solutions across diverse manufacturing environments.

SOURCE Shanghai Electric

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