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Altera FPGAs Pushing the Boundaries of Innovation at the Intelligent Edge

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Newest Programmable Solutions Designed to Bring Custom AI Inference, Real-time Compute, and Low Latency to Embedded Systems

BANGALORE, India and NUREMBERG, Germany, March 11, 2025 /PRNewswire/ — Today at Embedded World, Altera Corporation, a leader in FPGA innovations, unveiled its latest programmable solutions tailored for embedded developers who are pushing the boundaries of innovation at the intelligent edge. Altera’s latest Agilex™ FPGAs, Quartus® Prime Pro software, and FPGA AI Suite enable the rapid development of highly customized embedded systems deployed across a broad range of edge applications, including robotics, factory automation systems, and medical equipment.

Altera’s programmable solutions meet the stringent power, performance and size requirements of embedded and intelligent edge applications. These hardware solutions, along with Altera’s FPGA AI Suite, enable machine learning engineers, software developers, and FPGA designers to create custom FPGA AI platforms using industry-standard frameworks such as TensorFlow and PyTorch, and development tools such as OpenVINO and Quartus Prime software.

Today’s announcements include:

Altera’s low-power, cost-optimized Agilex 3 FPGAs are available for ordering: Agilex 3 FPGAs bring high-performance capabilities to low-power, cost-optimized applications, delivering up to 1.9x higher fabric performance1 compared to the previous generation at up to 38% lower power1. The FPGA’s high-performance programmable architecture, along with built-in AI Tensor blocks and embedded processors, enables businesses to rapidly modernize their edge and embedded infrastructure by deploying customized AI solutions that deliver the low latency, energy efficiency and agility needed for system longevity.

In robot control systems, Agilex 3 FPGAs bring real-time control to multi-axis robot arms by fusing machine learning capabilities into multi-sensor pipelines. And in smart factory cameras, Agilex 3 FPGAs improve defect detection by using fine-grained parallel processing and CNNs trained for object recognition to analyze vast amounts of data.

Customers can place orders now for production-quality Agilex 3 devices, development kits, selected partner boards and system-on-modules.

Altera shipping Agilex™ 5 E-Series FPGAs in production: The first wave of Agilex 5 FPGAs E-Series devices are now fully qualified and released for high-volume production. Compared to the Agilex 5 D-Series FPGAs, the Agilex 5 E-Series FPGAs are optimized for more power-sensitive applications that require high-performance with smaller form factors and logic densities. Agilex 5 E-Series FPGAs, with AI-infused fabric, bring high levels of integration and improved computing capabilities for intelligent edge applications, including video, industrial, robotics, and medical systems.

Altera expanding MAX® 10 FPGA with high I/O density packages: In a continued effort to enhance its cost-optimized product portfolio, Altera is expanding the MAX 10 FPGA family with new package options. The MAX 10 10M40 and 10M50 product lines are now offered in VPBGA-610 packages. This new package option significantly increases the value of these highly integrated devices by reducing form factor while maintaining a high IO count, resulting in a lower total cost of ownership for users. Customers can place orders now for engineering samples of MAX 10 FPGAs in the VPBGA-610 package, with production silicon available in Q3 2025.

Software and Ecosystem Support

Support for Agilex 3, Agilex 5 E-Series, and MAX 10 FPGAs is available through a no-cost Quartus software license. For AI developers, Altera’s FPGA AI Suite release 25.1 supports Agilex 3 and Agilex 5 FPGA development for AI inference using familiar industry-standard frameworks (TensorFlow and PyTorch). 

Altera provides users the resources needed for seamless FPGA development from its extensive network of partners. Through the Altera Solution Acceleration Partner (ASAP) Program, Altera helps users accelerate their FPGA AI development process and get to market faster.

“With today’s announcements, we continue to expand our leadership programmable portfolio by offering an even broader range of end-to-end solutions built on decades of expertise and a strong ecosystem of partners,” said Sandra Rivera, Altera CEO. “With our latest FPGA products and development tools, we provide embedded developers a seamless approach to deliver high-performing and high-quality intelligent edge solutions for the era of AI.”

Altera at Embedded World 2025

Altera is showcasing its latest FPGA innovations and development tools at Embedded World 2025. These programmable solutions are designed to deliver real-time compute, AI acceleration, and low-latency performance in applications like industrial IoT and smart manufacturing. Some of Altera’s technologies on display include:

High-performance 8K video & vision processing powered by Agilex™ 7 FPGAsReal-time robot control with ROS 2 using Agilex™ 5 SoC FPGAsLow-latency, low-power defect detection and object recognition powered by MAX® 10 FPGAs and Altera partner solutions.

Altera’s booth is located in Hall 5, Booth 343, in the NCC Ost Convention Centre.

About Altera 

Altera is a leading supplier of programmable hardware, software, and development tools that empower designers of electronic systems to innovate, differentiate, and succeed in their markets. With a broad portfolio of industry-leading FPGAs, SoCs, and design solutions, Altera enables customers to achieve faster time-to-market and unmatched performance in applications spanning data centers, communications, industrial, automotive, and more. For more information, visit www.altera.com.

1Performance varies by use, configuration and other factors. Learn more at www.intel.com/PerformanceIndex . Performance results are based on testing as of dates shown in configurations and may not reflect all publicly available updates.

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

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42 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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Video: CNPC offers green chemical answer

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42 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.

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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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42 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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