@siemenssoftware AI infrastructure is pushing thermal and power systems to their limits.
Using digital twins to simulate and optimize data center performance before deployment can help avoid costly failures and improve long-term reliability.
@airoa_org Interesting initiative.
Combining diverse real-robot data collection with foundation model development is exactly what robotics needs to move from isolated demos to more general-purpose deployment. π€
@Huawei AI infrastructure is evolving https://t.co/QLov7XmlWI AI workloads grow, storage, networking, compute, and data management all need to work together as one integrated system to support large-scale intelligent operations.
@Ronald_vanLoon High-payload bipedal robots could become very valuable in logistics environments built around human movement and workflows.The combination of mobility, balance, and dual-arm manipulation is what makes these systems especially interesting for real-world operations. π€
@lukas_m_ziegler@AllonicRobotics This is a fascinating approach to robotic hands.
If 3D tissue braiding can make end-effectors cheaper, faster to iterate, and more compliant, it could help unlock dexterous manipulation at scale. π€π§¬
@Siemens Strong achievement.Consistent improvement in ESG performance and maintaining a top sustainability ranking shows long-term commitment, not just short-term initiatives. π
@EMR_Automation Reliable valve actuation is critical for process control.
Solutions that improve response, durability, and efficiency help reduce downtime and keep operations running consistently. βοΈ
@AGIBOTofficial Competitions like this are important for the robotics ecosystem.
Standardized real-world evaluation helps move embodied AI beyond impressive demos toward measurable progress on reasoning, manipulation, and autonomy. π€
@humanoidsdaily This is where world models become truly useful for robotics.
The important shift is not generating realistic video, it is generating physically consistent environments that robots can actually learn from and transfer into the real world. π€
@asimovinc Good engineering tradeoff.Sometimes removing complexity improves reliability, manufacturability, and training. Fewer contact points can mean a simpler model, better simulation alignment, and more stable real-world behavior. π€
@XSquareRobot Open-source robotics is moving fast.
If pretrained models can show useful real-world manipulation before task-specific fine-tuning, that is a major step toward more scalable and reusable robot intelligence. π€
@IlirAliu_ Sometimes innovation is not about a brand-new idea. It is about the moment technology finally catches up to it.
Makes you wonder how many concepts ahead of their time are still waiting for the right materials, tools, or manufacturing methods to become possible. π€
@AssemblyMag1 Carbon nanotubes are fascinating, especially for lightweight and high-performance applications.
But replacing copper and aluminum at scale will depend on cost, manufacturability, reliability, and long-term performance in real-world electrical systems. β‘
@automation_com OT cybersecurity is becoming a core requirement, not a checkbox.
ISA/IEC 62443 certification helps create a common language for security, risk reduction, and trust across industrial systems.
@Haas_Automation Good value for shops getting started or upgrading.
Having the right tooling ready from day one saves setup time and helps get the machine productive faster. βοΈ
@Ronald_vanLoon@StarSnap_1 Healthcare robotics is advancing quickly.
Precision, consistency, and assistance during complex procedures like spine surgery could significantly improve outcomes while supporting surgical teams. π€π₯
As traditional scaling slows down, techniques like LogicFolding aim to improve performance through smarter circuit architecture and timing optimization rather than relying only on smaller transistors.
The future of computing growth will likely come from a combination of architecture, packaging, memory, and process innovation. β‘
@humanoidsdaily Different engineering philosophies, same outcome.
One approach solves the problem through dexterity and contact control, the other through environmental adaptation and tooling. In robotics, both can be valid paths to reliable automation. π»π€
@FANUCAmerica Simplifying robot programming is a huge step for adoption.
Reducing training time and making interfaces more intuitive helps manufacturers deploy automation faster and scale it more easily.
@asimovinc Open-source humanoid development is moving fast.
Testing locomotion in real outdoor environments is where stability, balance, and robustness really get validated. π€