A US technology company is 3D-printing futuristic holiday homes starting from $100,000 (£75,000) that fit in a back garden. Mighty Buildings, based in Oakland, California, says it can manufacture a 350 square-foot studio unit in less than 24 hours, providing owners a peaceful hideaway or a holiday cabin to accommodate guests. The firm is offering a variety of units on its website, ranging from a dinky studio to a luxury family home, which are printed with liquid synthetic stone that hardens almost instantly. The buildings are constructed at the company's facilities, transported to the customer's property on a truck and placed in a back garden with a massive crane. Units could also be leased out by property owners to help tackle the housing crisis, or big companies could also buy them to house employees while they're looking for something more long-term.

It is sure now, Artificial Intelligence is part of our future and already allowing to create really advanced devices. But do you know that the 3D printing technology can also make the most of AI? 3D printing is a game-changing technology, constantly evolving and finding new ways to improve itself. It now includes new amazing technologies like Artificial Intelligence. This combination of Artificial Intelligence and 3D printing could lead to new amazing applications of the additive manufacturing technology. Find all the answers to your questions in this blog post.

Humans are innately capable of performing complex movements with their hands via the articulation of their endoskeletal structure. These movements are made possible by ligaments and tendons that are elastically connected to a fairly rigid bone structure. Researchers at University of California- Santa Cruz and Ritsumeikan University in Japan have recently designed and fabricated a robotic finger inspired by the human endoskeletal structure. This biomimetic robotic finger, presented at this year's International Conference on Ubiquitous Robots and Ambient Intelligence (URAI), was assembled using a multi-material 3-D printer. "Developing a robotic hand that has hard and soft components, just like the human hand, is a research topic that I wanted to explore for years," Maryam Tebyani, one of the researchers who carried out the study, told TechXplore.

Organoids 3D printing has quickly become one of the leading segments of the 3D printing industry in terms of innovation. Until recently, the market was primarily focused on North America, however many companies, laboratories, and universities around the world are exploring this field as well. Thanks to 3D printing techniques, cells and biomaterials can be combined and deposited layer by layer to create biomedical developments that have the same properties as living tissues. During this process, various bio-links can be used to create these tissue-like structures, which have applications in the fields of medical and tissue engineering. Of course, it is more than knowing that the goal of all these developments is to successfully bioprint a fully functional human organ.

Oak Ridge National Laboratory is behind the development of a new type of artificial intelligence (AI) software called Peregrine, meant to improve the quality of functional parts being produced via powder bed 3D printers. Peregrine requires no "expensive characterization equipment," yet possesses the ability to evaluate parts during manufacturing. "Capturing that information creates a digital'clone' for each part, providing a trove of data from the raw material to the operational component," said Vincent Paquit, leader of advanced manufacturing data analytics research as part of ORNL's Imaging, Signals and Machine Learning group. "We then use that data to qualify the part and to inform future builds across multiple part geometries and with multiple materials, achieving new levels of automation and manufacturing quality assurance." Oak Ridge National Laboratory researcher Chase Joslin uses Peregrine software to monitor and analyze a component being 3D printed at the Manufacturing Demonstration Facility at ORNL (Image: Luke Scime, ORNL, U.S. Dept. of Energy) The software is based on a convolutional neural network that imitates the human brain, rapidly evaluating images from cameras during printing.

Image Source: PIXABAY This AI software can assess 3D printing quality in real time. A team of US researchers has developed artificial intelligence (AI) software for 3D printers that assesses the quality of parts in real time, without the need for expensive characterisation equipment. The software, named Peregrine, supports the advanced manufacturing "digital thread" being developed at Oak Ridge National Laboratory (ORNL) that collects and analyses data through every step of the manufacturing process, from design to feedstock selection to the print build to material testing.

Here's an attention-grabbing idea: Deploying cellular-enabled Industry 4.0 solutions can generate a 10-20x operational cost-savings ROI (return on investment) over the course of five years. This is according to a joint research study from ABI Research and Ericsson. The research also suggests Industry 4.0 solutions can generate up to 8.5% in operational cost savings, which, for a factory or industrial site, can equate to an operational cost savings of up to $600 per square meter per year. Industry 4.0, also known as the fourth industrial revolution, is the idea that connectivity, automation technologies, and digitization are creating the fourth major revolution in the business of manufacturing. Thanks to trends like leveraging the IoT (Internet of Things), including wireless networking and sensors to collect machine data and enable predictive maintenance, as well as 3D printing, robots and cobots on the factory floor, machine learning and AI (artificial intelligence), 5G, and digital twins, among other trends, the Industry 4.0 market is projected by MarketsandMarkets to reach almost $157 billion by 2024. A big part of Industry 4.0 is the use of AI technologies to enable smarter machines that can take on tasks like self-monitoring and diagnosis autonomously.

Traditional methods for solvability region analysis can only have inner approximations with inconclusive conservatism. Machine learning methods have been proposed to approach the real region. In this letter, we propose a deep active learning framework for power system solvability prediction. Compared with the passive learning methods where the training is performed after all instances are labeled, the active learning selects most informative instances to be label and therefore significantly reduce the size of labeled dataset for training. In the active learning framework, the acquisition functions, which correspond to different sampling strategies, are defined in terms of the on-the-fly posterior probability from the classifier. The IEEE 39-bus system is employed to validate the proposed framework, where a two-dimensional case is illustrated to visualize the effectiveness of the sampling method followed by the full-dimensional numerical experiments.

We are pleased to announce the second edition of our book Data Mining and Machine Learning: Fundamental Concepts and Algorithms, Second Edition, by Mohammed J. Zaki and Wagner Meira, Jr., published by Cambridge University Press, 2020. The entire book is available to read online for free and the site includes video lectures and other resources. New to this edition is an entire part devoted to regression and deep learning. The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners.

Robots and AI are going to do many things for us. They will be saving lives by revolutionizing the medical field.