AI server stocks are staging a comeback, but Super Micro faces an earnings report that must answer hard questions about shrinking margins, export control legal trouble, and whether a record order backlog can actually translate into profit.
GenRobot AI closed a $100M Series A+ to supply robot training data. Here is the founder lesson hiding inside the round. The post Robotics Startups Need Data: GenRobot AI Raises Series A+ appeared first on Under30CEO.
Current growth is driven mainly by the Ansys acquisition; AI/IP contributions are expected to be gradual, with royalties not materializing until 2028. SNPS faces capex risks from hyperscalers, elevated net debt ($7.23B), and limited impact from buybacks due to high share-based compensation.
Marvell is paying in stock for Lumentum's lasers. Lumentum shareholders will receive 4.5 Marvell shares per share owned, representing a 23.9% premium before talks leaked.
The companies expect the deal to close by the end of the year, subject to what onsemi described as customary closing conditions. Onsemi said it entered into an agreement to acquire Ferric as part of a broader push into power delivery for next-generation AI processors,
Apple has unveiled the revolutionary Spatial Reframing feature in the Photos app with iOS 27. This AI-powered tool allows users to change the capture angle and rotate photos with a single touch to make them look as if they were taken from completely different angles, while intelligently generating missing parts to make the photo look natural. Although it is still in its beta stage and shows some strange facial bugs, it promises a qualitative leap in the world of visual editing.
General-purpose mobile manipulation requires a combination of capable robot hardware, scalable demonstration collection, expressive whole-body control, and effective policy learning. Yet these components are often developed independently, creating mismatches that limit the capabilities of the complete system. We present Pixel, a co-designed full-stack system for learning general-purpose mobile manipulation. Pixel combines a low-cost wheeled humanoid with human-aligned kinematics and compliant grippers, multiple teleoperation and robot-free human data-collection interfaces, a unified whole-body controller, and a common policy learning pipeline across human and robot demonstrations. A hierarchical learning stack further enables language-conditioned visuomotor control and long-horizon task execution. We evaluate the system across hardware, data collection, and policy learning, and demonstrate mobile-manipulation behaviors requiring dexterity, active perception, navigation, and whole-body coordination. We hope that Pixel provides an integrated and extensible foundation for studying how robot hardware, data, control, and learning can be designed together for robot learning. More…
Idol turns one picture of an object into a 3D Gaussian splat. Give it a render, a generated image or a photo: it removes the background, frames the object and generates up to 1,048,576 Gaussians, written as a standard 3DGS .ply. It runs on consumer GPUs, using 7.2 GB of VRAM…
Demand for advanced chips is rising. The processes to build them are getting more complex. And the margin for error is shrinking. For engineers, understanding how a process change will behave, how a material will interact with a new step, how a defect maps back to a root cause…
FarmerChat is Digital Green's farm advisory service for smallholder farmers. When something looks wrong with a crop, the farmer takes a photograph and sends it, and that photograph is the whole question: no symptom described, no crop named, often no text at all. The service has…
Fine-tuning Vision-Language-Action (VLA) models commonly relies on human teleoperation demonstrations, while reinforcement learning (RL) with sparse binary rewards faces an exploration challenge when successful trajectories are rarely sampled. We propose SynthDemo-RL, a…
Hamiltonian normalizing flows are attractive generative models because their phase-space maps are invertible and volume preserving, but most neural constructions are formulated in Euclidean space. We introduce Riemannian Neural Hamiltonian Flows, which combine the fixed kinetic…
Financial time-series forecasting must capture price dynamics across heterogeneous assets while incorporating news available at prediction time. We introduce DualCast, a dual-path framework that extends a frozen language model with a discrete financial vocabulary. Each…