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Iván Hernández Dalas: Flex and Teradyne expand partnership to scale physical AI

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Flex is working with robotics and AI to help customers accelerate data center deployment. | Credit: Flex With a vision to standardize automation on a global scale, Flex and Teradyne Robotics have expanded their long-term partnership to accelerate the deployment of physical AI and intelligent robotics across the manufacturing sector. The collaboration establishes a dual-track strategy where Flex serves as both the manufacturer of Teradyne’s core robotics components and a primary testing ground. Flex plans to deploy collaborative robots and autonomous mobile robots ( AMRs ) from Teradyne units Universal Robots ( UR ) and Mobile Industrial Robot ( MiR ), respectively, across its own production facilities worldwide to drive operational efficiency. The expansion signals a strategic pivot from traditional hardware support to the front lines of physical AI , where the boundary between robot manufacturer and end user is increasingly blurred. By integrating Teradyne Robotics ‘ cobots and ...
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Iván Hernández Dalas: Apptronik’s new CPO hire a major step in right direction

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Appronik is preparing for a major growth phase as it begins manufacturing and selling its Apollo humanoid robot. | Credit: Apptronik Apptronik has signaled its transition from experimental robotics to commercial powerhouse by tapping Daniel Chu, the visionary behind Waymo’s autonomous ride-hailing launch, as its new chief product officer. By securing a leader who successfully navigated the leap from lab-bound AI to real-world infrastructure, Apptronik is positioning its humanoid robots as the next great frontier in scalable, mass-market technology. Daniel Chu will lead Apptronik’s product roadmap. | Credit: Apptronik The addition of Chu—and veterans from Amazon, Boston Dynamics, and Paramount+—marks a pivotal shift for the Austin-based startup from ambitious R&D to aggressive market entry. Backed by a fresh $935 million Series A and the impending reveal of its flagship humanoid, Apptronik is no longer just building robots; it is building the commercial infrastructure to int...
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Iván Hernández Dalas: Appetronix acquires Cibotica to automate restaurant kitchens

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Cibotica, now part of Appetronix, offers Remy, an automated salad and bowl assembly line that can work with a range of ingredients. | Source: Appetronix Appetronix today announced it acquired Cibotica, which develops ingredient dispensing and portioning technology. The acquisition opens new doors for Appetronix, which has focused on establishing standalone, autonomous restaurants. The acquisition will bring Cibotica’s flagship product, an automated bowl and salad assembly system, to Appetronix’s restaurants. The companies did not disclose the financial details of the deal. “With Cibotica, what they’ve done is created this amazing equipment that’s very modular,” Nipun Sharma, the CEO of Appetronix, told The Robot Report . “It goes into existing restaurants. It automates a big percentage of tasks that are done in current restaurants. They’ve already done the work. We already have an infrastructure that we can benefit from the technology, because our machines can use what they’ve dev...
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Iván Hernández Dalas: Gradient-based planning for world models at longer horizons

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By Michael Psenka , Mike Rabbat , Aditi Krishnapriyan , Yann LeCun , Amir Bar GRASP is a new gradient-based planner for learned dynamics (a “world model”) that makes long-horizon planning practical by (1) lifting the trajectory into virtual states so optimization is parallel across time, (2) adding stochasticity directly to the state iterates for exploration, and (3) reshaping gradients so actions get clean signals while we avoid brittle “state-input” gradients through high-dimensional vision models. Large, learned world models are becoming increasingly capable. They can predict long sequences of future observations in high-dimensional visual spaces and generalize across tasks in ways that were difficult to imagine a few years ago. As these models scale, they start to look less like task-specific predictors and more like general-purpose simulators. But having a powerful predictive model is not the same as being able to use it effectively for control/learning/planning. In practice...
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