Category robotics

A high-tech district in the Chinese capital is opening an all-service robot store on Friday to push a national drive to develop humanoid robots.

A flexible robotic sheet that can grasp objects and move across surfaces has been created by a team of researchers led by Jung Kim from the Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology.

The robotic gripper has three “fingers,” each made of a soft, pliable material. When a “tendon” — in this case a guitar string — is pulled, the fingers retract.

Genie 3 can generate dynamic worlds that you can navigate in real time at 24 frames per second, retaining consistency for a few minutes at a resolution of 720p.

Genie 3 can generate dynamic worlds that you can navigate in real time at 24 frames per second, retaining consistency for a few minutes at a resolution of 720p.

Genie 3 can generate dynamic worlds that you can navigate in real time at 24 frames per second, retaining consistency for a few minutes at a resolution of 720p.

Capital investments in advanced manufacturing environments require careful consideration, especially if that investment is for a new process or technology. If you are looking at investing in OLP here are some things to consider about the potential return on investment (ROI).

This is a test

Game Arena is a new, open-source platform for rigorous evaluation of AI models. It allows for head-to-head comparison of frontier systems in environments with clear winning conditions.

Game Arena is a new, open-source platform for rigorous evaluation of AI models. It allows for head-to-head comparison of frontier systems in environments with clear winning conditions.

Game Arena is a new, open-source platform for rigorous evaluation of AI models. It allows for head-to-head comparison of frontier systems in environments with clear winning conditions.

A POSTECH research team has developed a thin, flexible robotic actuator inspired by human muscle proteins. As thin as paper, yet capable of generating strong forces, this robot can maneuver through tight spaces and manipulate objects, making it suitable for a wide range of applications—from surgical robots to industrial equipment. The study has been published in Nature Communications.

When planning cycles stall, business outcomes suffer. Static forecasts and slow collaboration keeps teams from responding to change, leaving businesses a step behind. 

SAP provides a powerful foundation for enterprise planning and operations. But as market conditions shift faster than ever, teams need new ways to respond with speed, precision, and adaptability.

Agentic AI introduces intelligent, self-adaptive automation into the picture, enhancing existing planning processes so teams can move faster and make better decisions.

Now, with the SAP® Endorsed App from DataRobot, organizations can bring that intelligence directly into their SAP environment, extending the value of their investment and enabling more responsive, future-ready planning. 

What’s new, and why it matters

AI Apps and Platform by DataRobot are now SAP® Endorsed and available on the SAP Store.

This designation is more than a badge. It’s a mark of technical excellence and proven customer value. Earning it means DataRobot has met SAP’s premium certification standards, including security reviews, cloud integration tests, and static code analysis.

For customers, this opens a clear, low-risk path to adopting agentic AI with confidence, including:

• Avoiding workarounds or patchwork integrations
• Keeping your existing systems. No rip-and-replace required
• Running AI securely and natively inside your SAP environment, from day one
  

A smarter path to enterprise planning

Many SAP customers face similar planning roadblocks:

• Fragmented systems and rigid workflows slow down decisions and force manual workarounds
• Disconnected roles and teams struggle to align or respond quickly when conditions change
• Slow, complex data integration makes it hard to adapt plans in real time
• AI investments get stuck in pilots, never delivering value at scale
  

SAP customers are already managing complex data and planning processes across finance, operations, and supply chain. But as needs evolve, many teams are looking for new ways to respond faster to change, extract insight from growing data sets, and operationalize AI across business functions.

To close these gaps, SAP customers are turning to agentic AI apps that can adapt, automate, and scale alongside their existing workflows.

Agentic AI modernizes enterprise planning by:

• Empowering business users with intuitive agentic AI interfaces
• Delivering more accurate, self-adapting forecasts across use cases, from demand and headcount to resource allocation and beyond
• Reducing dependency on manual updates and isolated workflows, accelerating planning across functions

The agentic AI Apps and Platform that DataRobot provides are designed to complement SAP, layering intelligent decision support, automation, and learning into the tools your teams already rely on.

Agentic AI planning for finance teams

Finance leaders face increasing pressure to forecast, advise, and act faster than ever, with tighter margins and greater precision. Agentic AI helps them meet the moment.

With the SAP Endorsed App from DataRobot, finance teams can:

• Predict cash flow gaps early to free up working capital
• Catch financial anomalies before they impact the bottom line
• Automate invoice validation to reduce errors and accelerate approvals
• Confidently model revenue scenarios to guide strategic decisions
• Assess credit risk in real time to avoid delays and disruptions

This shifts finance from reactive to strategic, enabling faster insight, earlier action, and better decision-making that helps the business stay ahead.

Supply chain teams: prevent delays, reduce waste, and move faster

Modern supply chains can’t afford blind spots. From demand planning to delivery, even minor delays can ripple across the business.

SAP already plays a central role in planning and supply chain execution. With agentic AI, teams can go further, adapting in real time, anticipating disruptions, streamlining decisions, and simplifying operations.

With this combination, supply chain teams can:

• Forecast demand more accurately to reduce stockouts and excess inventory
• Use real-time signals to manage delays and minimize disruptions
• Optimize production schedules to maximize output and resource use
• Plan labor more efficiently to align staffing with operational needs
• Predict maintenance needs early to prevent costly downtime

With agentic AI layered into SAP, supply chain teams adapt faster without adding new systems or complexity.

Explore what’s possible: Agentic AI that integrates, accelerates, and delivers

This isn’t a bolt-on demo or shadow tool. It’s an enterprise-grade AI platform designed to work inside your SAP environment.

It connects directly to SAP data and workflows, delivering: 

• Agentic AI decisions embedded in your SAP data layer
• Prebuilt apps and customizable templates for real-world use cases
• End-to-end governance and control built for enterprise standards
• Expert support to help you build, deploy, and scale agentic AI safely

The result: faster outcomes, more resilient planning, and a practical way to run your business.

Our SAP Endorsed App goes beyond technical alignment. They represent a new planning experience: one that’s intelligent, inclusive, and adaptive by design. It’s a shared vision for enabling intelligent enterprises, where planning isn’t just faster, but smarter, more adaptive, and more connected to real outcomes.

Explore our agentic AI apps on the SAP Store

The post Plans change. The SAP® Endorsed App from DataRobot keeps up. appeared first on DataRobot.

Precision robotics manufacturing is slowly becoming normalized because of its irrefutable positive impact on organizations. However, the journey to create error-free machinery never stops.

Two of the most critical success factors in the manufacturing industry are time to deployment and cycle time. Despite this, the design and deployment of robotic workcells has long remained a surprisingly manual and time-consuming process. Realtime Robotics is aiming to change that with Resolver, a cloud-based optimization engine that introduces industrial-scale automation into the earliest stages of robotic system planning.

At its core, Resolver addresses some of the most persistent engineering challenges in workcell design: motion planning, robot task allocation, target sequence optimization, and layout validation. Traditionally, these steps require iterative tweaking, deep domain expertise, and a significant investment of time and resources to get right and be able to deliver on time. Resolver replaces that trial-and-error approach with intelligent automation. As it runs, the engine explores thousands of potential options to deliver an increasingly optimized result; one that balances performance, accuracy, and feasibility – and does so within minutes.

This kind of computational efficiency opens new doors for how teams approach the design process. Rather than being limited by what’s manually achievable, engineers can let Resolver handle the mechanical complexity and instead focus on higher-level goals such as throughput, safety, or flexibility. Resolver adapts to a range of use cases, from greenfield line builds to individual cell retrofits, making it broadly applicable across industries and production scales. And it can do all this in mere minutes – faster than what’s humanly possible.

Recent integrations with leading 3D simulation platforms including Siemens Process Simulate, Visual Components, and Mitsubishi Electric’s MELSOFT Gemini, enable users to access Resolver’s capabilities directly within their preferred simulation environments. This embedded approach reflects a broader shift toward interoperability and hybrid workflows in advanced manufacturing, where simulation, design, and optimization are increasingly converging.

Early adopters, particularly in automotive manufacturing, have already reported cycle time improvements ranging from 15% to 40%, along with faster deployments and fewer errors. These outcomes suggest that Resolver is not just a point solution, but part of a larger movement toward AI-assisted engineering. A future where decision-making is augmented, not replaced, by automation.

Post provided by: Realtime Robotics – www.rtr.ai

.

——————————————————

Terms of use:

Copying or republishing of our content is not allowed without written permission from us. We make dated records and keep originals of our posts and images. The content in this website may be incorrect or incomplete. User assumes all liability and risk as a result of using this website. Also see our Terms page.