Olypsys
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Pricing model
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Olypsys provides a cutting-edge smartphone-based solution for the accurate measurement and identification of O-rings using machine learning technology. This easy-to-use tool enables rapid and precise measurements, with data stored in a centralized database accessible through mobile and web applications. It is tailored for industrial users, large companies, and distributors seeking efficient, portable, and cost-effective O-ring measurement solutions. By integrating advanced technology with user-friendliness, Olypsys offers a valuable resource for enhancing accuracy and optimizing operations in manufacturing, maintenance, and engineering industries.
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Polycam is a smartphone app for 3D capture that allows users to produce high-quality 3D models from photos using any device and quickly scan spaces with a LiDAR sensor. It also provides the ability to edit 3D captures directly on the device and export them in multiple file formats, share them with friends and the Polycam community, and take measurements and create blueprints.
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Postshot, created by Jawset, is an AI-driven 3D scanning software that converts video clips into intricate 3D models through advanced methods such as Neural Radiance Fields and Gaussian Splatting. Users just need to record a video of an object with a smartphone, load it into the Postshot desktop application, and the program processes it into a detailed 3D model. This tool is especially attractive to designers, engineers, researchers, and 3D modeling enthusiasts for its user-friendly interface, advanced AI technology, and versatility for various purposes. Featuring an innovative approach and free beta access, Postshot provides an accessible, state-of-the-art solution for creating high-quality 3D models without the need for specialized equipment.
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Segment Anything AI (Meta) provides the Segment Anything Model (SAM), an AI tool capable of isolating any object within any image. SAM is promptable and exhibits zero-shot generalization to novel images and objects, utilizing a range of input prompts that allow seamless integration with other AI systems. It can also be trained to label images and enhance its dataset. The SAM model is crafted to be efficient and adaptable, optimizing its data engine's performance. Contributors to the project include Alexander Kirillov, Eric Mintun, Nikhila Ravi, among others. The code is accessible on GitHub, and users can subscribe to their newsletter for updates on their latest research advancements.