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Rutgers-Newark Launches Institute on Improving Communities Through AI and Interdisciplinary Data Work

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Lt. Gov. Tahesha Way: ‘The Work Done Here Will Have a Lasting Impact on Our State, Nation and Beyond.’

NEWARK, N.J., April 18, 2025 /PRNewswire/ — Rutgers-Newark announced the launch of the Institute for Data, Research and Innovation Science (IDRIS), a groundbreaking effort that explores how AI and other technologies can improve healthcare, education, public safety, and other aspects of community well-being.

“IDRIS is interested in asking, how does this impact the community and the human experience?” said Fay Cobb Payton, Executive Director of IDRIS and Professor of Mathematics and Computer Science at Rutgers-Newark. She was part of the state task force that compiled last year’s report on AI for Gov. Murphy.

The event included keynote remarks from Lt. Gov. Tahesha Way, in addition to corporate and university leaders from Rutgers and Princeton University.

“This program is in lockstep with our administration’s efforts to reclaim New Jersey’s rightful place as the center of innovation history,” said Way. “It also underscores the importance of addressing risk, privacy concerns and workforce innovation. The work done here will have a lasting impact on our state, nation and beyond.”

IDRIS examines how AI data is gathered, incorporated, and applied. It focuses on ethical questions surrounding AI and how it can be used to advance equity and overcome challenges in urban communities. The institute will also explore additional technologies, including virtual augmented reality and wearables, such as smart watches and headsets. It will also help train undergraduate and graduate students in research and data literacy.

“In Newark and elsewhere, there are complex problems that situate themselves across all facets of a community: public administration, criminal justice, social work, the environment, healthcare, and education. These require interdisciplinary approaches and collaboration,” said Payton.

IDRIS, which spans research and healthcare efforts across Rutgers, includes partnerships with community organizations and state and local government, including the The Newark Public Safety Collaborative at Rutgers-Newark, Rutgers-New Brunswick,  and New Jersey Medical School. Corporate partners are also involved as stakeholders.

Gustavo Abreu, Global Head of Securities Operations Technology for Inventory and Position Management at Barclays, emphasized the growing need for institutions to stay attuned to increasingly sophisticated consumers and the transformative potential of interdisciplinary collaboration hubs like IDRIS.

“We are entering an era where the consumer is not only more informed but expects solutions that are intuitive, inclusive, and adaptive,” he said. “To meet that challenge, we must lead with empathy, apply design thinking, and co-create with the very communities we aim to serve. The key is not just solving problems, but understanding them deeply—and using the right tools to design for impact.”

IDRIS also aims to increase public data literacy and knowledge of AI and tech data, with a goal of helping to inform policy and programs in New Jersey – a focus of the governor’s AI report, which was released in November.

The report was part of Gov. Murphy’s plan to improve state government through AI and how it can be used to stimulate economic growth, create jobs, and enhance training and talent development, especially for low-income residents. IDRIS will also examine some of the problems and ethical issues linked to AI.

“Many of the recommendations from the report are being adopted by this program,” Way said.

One focus of Payton’s work, and the mission of IDRIS, has been the potential and limitations of AI algorithms used in healthcare and other fields. Her research has examined biases in AI technology that can lead service providers to rely on data that perpetuates generalizations about people of color and others, failing to incorporate their cultural background and day-to-day living circumstances. The limitations, in part, stem from an overreliance on data and rules that are misinformed and have gone unchecked, Payton said.

“The question becomes, who is collecting the data and how is it collected? Who is curating it?” asked Payton.”That’s important.”

But IDRIS will also examine the vast potential of AI to empower citizens to use data to improve their communities. They could potentially monitor local changes to the environment, such as droughts and air pollution–along with climate emergencies–and share data with officials and others that could help  improve conditions. AI can also be used to help communities enhance public safety, improve social services., and foster entrepreneurship.

“We intend IDRIS to apply those skills to the moment and the work that is here before us…to make sure that human lives in the future are better than they are right now,” said Jacqueline Mattis, Dean of the School of Arts and Sciences-Newark, who helped lead the formation of IDRIS.

Said Rutgers-Newark Interim Chancellor Jeffrey Robinson, “The research highlighted today is about how we can create knowledge for social good. Here at Rutgers Newark, it’s something we cherish deeply.”

ABOUT IDRIS

The Institute for Data, Research, and Innovation Science (IDRIS) is an organizing hub for applied, social, ethical, and responsible scholarship in data science and emerging technologies at Rutgers University–Newark.

ABOUT RUTGERS-NEWARK

Rutgers University–Newark (RU-N) is a diverse, urban, public research university that is an anchor institution in New Jersey’s cultural capital. It is exceptionally well positioned to fulfill higher education’s promise as an engine of discovery, innovation, and social mobility. With its legacy of producing high-impact scholarship, Rutgers-Newark is in and of a city and region where its work on local challenges, undertaken with partners from many sectors, resonates powerfully throughout our urbanizing world. RU-N brings an incredible diversity of people to this work—students, faculty, staff, and community partners—making it more creative, more engaging, and more relevant for our time and the times ahead.

View original content to download multimedia:https://www.prnewswire.com/news-releases/rutgers-newark-launches-institute-on-improving-communities-through-ai-and-interdisciplinary-data-work-302432630.html

SOURCE Rutgers University – Newark

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

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32 minutes ago

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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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32 minutes ago

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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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32 minutes ago

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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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