BUILD LEGO CREATIONS: This innovative app is here to make custom Lego creation fun and accessible for everyone, whether you're a seasoned builder or just getting started. By using advanced artificial intelligence and mobile scanning technology, Brick My World opens up a world of creative possibilities. 'OUR HOLIDAY GIFT': OpenAI released its text-to-video artificial intelligence model, Sora, this week after the completion of its testing phase. The OpenAI logo is being displayed on a smartphone with the Sora text-to-video generator visible in the background in this photo illustration, taken in Brussels, Belgium, on February 16, 2024. GRANNY FIGHTS BACK: Daisy is an artificial intelligence-powered grandma developed by Virgin Media O2 to interact with scammers.

Lego and McLaren collaborated on a fully drivable, life-sized replica of the McLaren P1 hypercar made almost entirely out of Lego Technic pieces. Imagine being able to turn any object into a Lego masterpiece with just your phone. Well, that's exactly what Brick My World offers. This innovative app is here to make custom Lego creation fun and accessible for everyone, whether you're a seasoned builder or just getting started. By using advanced artificial intelligence and mobile scanning technology, Brick My World opens up a world of creative possibilities.

High-quality 3D ground-truth shapes are critical for 3D object reconstruction evaluation. However, it is difficult to create a replica of an object in reality, and even 3D reconstructions generated by 3D scanners have artefacts that cause biases in evaluation. To address this issue, we introduce a novel multi-view RGBD dataset captured using a mobile device, which includes highly precise 3D ground-truth annotations for 153 object models featuring a diverse set of 3D structures. We obtain precise 3D ground-truth shape without relying on high-end 3D scanners by utilising LEGO models with known geometry as the 3D structures for image capture. The distinct data modality offered by high-resolution RGB images and low-resolution depth maps captured on a mobile device, when combined with precise 3D geometry annotations, presents a unique opportunity for future research on high-fidelity 3D reconstruction. Furthermore, we evaluate a range of 3D reconstruction algorithms on the proposed dataset. Project page: http://code.active.vision/MobileBrick/

Assembly sequence planning (ASP) is the essential process for modern manufacturing, proven to be NP-complete thus its effective and efficient solution has been a challenge for researchers in the field. In this paper, we present a graph-transformer based framework for the ASP problem which is trained and demonstrated on a self-collected ASP database. The ASP database contains a self-collected set of LEGO models. The LEGO model is abstracted to a heterogeneous graph structure after a thorough analysis of the original structure and feature extraction. The ground truth assembly sequence is first generated by brute-force search and then adjusted manually to in line with human rational habits. Based on this self-collected ASP dataset, we propose a heterogeneous graph-transformer framework to learn the latent rules for assembly planning. We evaluated the proposed framework in a series of experiment. The results show that the similarity of the predicted and ground truth sequences can reach 0.44, a medium correlation measured by Kendall's $\tau$. Meanwhile, we compared the different effects of node features and edge features and generated a feasible and reasonable assembly sequence as a benchmark for further research. Our data set and code is available on https://github.com/AIR-DISCOVER/ICRA\_ASP.

The ability to reason about parts that make up objects and the structural relationships between them is essential for the ability to build tools, solve problems and manipulate the world. Firstly, a learning agent is presented with a previously unseen LEGO model and can disassemble and inspect it to learn more about its structure. Then, the agent is presented with an empty scene and must use the information gathered to rebuild the model from scratch. Researchers present a new simulator and dataset that allow interactive learning agents to build and manipulate LEGO models. Transformer-based network architecture is designed to make progress on this task.

Volvo is eager to bring self-driving technology to construction crews, but it's taking a decidedly unusual route to get there. The automaker has unveiled an autonomous wheel loader prototype, the LX03, that's based on a Lego model -- 42081 Lego Technic Concept Wheel Loader Zeux, if you're looking for it. The machine can haul 5 tons and can make its own decisions in a wide variety of situations, including team-ups with human workers. The LX03 is also uniquely modular. Volvo can make "just one or two changes" to produce a larger or smaller loader to meet a customer's demands.