Coohom Cloud

#SyntheticData can greatly facilitate #AIModel development by reducing costs and accelerating inference speeds. However, the use of synthetic data may pose the potential risk of "#ModelCollapse", which means tails of the original content distribution disappear.?? To counter this, some researchers propose mixing synthetic data with #RealData for model training to lower the risk of model collapse. Coohom Cloud delivers high-quality, annotated 2D/3D #SyntheticDatasets, aiding in cost-effective and efficient AI model training. Read the article for more information: https://lnkd.in/erVyG3KN

In the realm of #AI and #MachineLearning, intelligent agents training relies heavily on vast datasets. However, #DataCompliance issues have become increasingly prominent, posing a critical challenge to AI agent development. ? Cleaning robot of iRobot was once involved in an incident where its in-built camera captured sensitive domestic scenes, including bathroom use, which raised privacy concerns among customers. The improper use of this private data for AI model training and its subsequent exposure online underscored the legal and regulatory risks of improper data collection by intelligent home devices. ?? Coohom Cloud addresses the compliance challenges of training data for robots with a robust data security review mechanism. ?? We offer #SyntheticData that are generated without the use of any real data, ensuring the anonymization of sensitive information to protect individual privacy. Furthermore, by clarifying data copyright assignments in our transactions, we provide a legally compliant, secure, and reliable data service, safeguarding against copyright disputes. Learn more about our data solution: https://2ly.link/1zQx4 #DataSecurity #Robotics #ModelTraining

Large and rich training data is important for robotic #AIModel performance. ?? AI models for intelligent robots must process complex tasks, such as natural language processing (#NLP) and tasks in computer vision such as object detection and semantic segmentation. Training these models requires a substantial dataset, often scaling into hundreds of thousands to millions of tokens. Coohom Cloud capitalizes on its extensive data resources to supply substantial synthetic datasets for #RoboticTraining. Boasting a Model library of 360 million 3D models and 18 million interior design schemes, Coohom Cloud provides ample training data for #RobotSimulation training, including home cleaning robots, thereby enhancing their generalization capabilities. Find out more about Coohom Cloud's database! https://2ly.link/1zICQ

Many multimodal large language models (MM-LLMs) do not have accurate "understanding" of the real physical world, which leads to many physical inaccuracies ?? when generating images, videos, and other content. Therefore, datasets that adhere to the laws of physics are crucial for enhancing the quality of image/video generation by #AIModels. #CoohomCloud provides high-quality 3D model datasets with robust physical deformation capabilities. For instance, it achieves the following: 1??Flexible deformation for bags, socks, wires, and other flexible bodies. 2??Simulate the scattering of nut shell-like models. 3??Simulate real-world model drop damage scenarios. By accomplishing a variety of morphological changes for models, Coohom Cloud delivers a substantial amount of physically-accurate #TrainingData for AI models at a reduced cost. ?? Find out more about our model capabilities! https://2ly.link/1zICQ #LLM #AITraining #ML #SyntheticData

A top-tier home cleaning robot company cooperated with #CoohomCloud to tackle edge scene data in #RoboticTraining. Offering comprehensive #SyntheticData solution, Coohom Cloud optimized cleaning robots' real-world adaptability. Learn more about our data solution: https://2ly.link/1zGG7 #RoboticSimulation #AI #MachineLearning

??Elevating #HomeRobot Intelligence with Physical Material Adaptation!?? Diversity of interior environments challenges performance of home robots, as lighting conditions and floor materials can vary significantly. Therefore, to enhance adaptability and generalization capabilities, home robot training must incorporate complex scenario data.?? As a #SyntheticData service provider, #CoohomCloud possesses Domain Randomization technology, which allows for flexible switching of model surface materials according to different training needs.?? For instance, we can replace marble floors with wooden ones, adjusting various floor materials to create different reflective effects. This enables virtual training environments to simulate the diversity and complexity of real world, making home robot training more realistic.?? Find out more about our capabilities! https://2ly.link/1zDsI #AITraining #RoboticSimulation #MachineLearning #ArtificialIntelligence

Real Data Or #SyntheticData? ?? Is the well of real data drying up? Join us in voting!?? 1. Real data is a bottomless pit – there's always more to discover. 2. The limits of real data are being reached. 3. Synthetic data can fully replace real data for AI training. 4. A blend of real and synthetic data is the key to AI's future. Comment below to share other thoughts about it! Learn more about #CoohomCloud's synthetic data solution: https://2ly.link/1zAKh

??Ensure data security and quality with #CoohomCloud's synthetic data! ?? The "unlearning" techniques aim to make #AI models "forget" specific undesirable information they have learned from their training data, such as sensitive private data or copyrighted material. However, the researchers found that while unlearning algorithms can make models forget certain information, they also impair the models' general question-answering capabilities, creating a trade-off. The implications of the findings from this article for #SyntheticData are significant. Coohom Cloud's extensive synthetic datasets can be used to protect data privacy, avoid legal disputes over the use of copyrighted materials in AI training. ?? Read the article: https://t.co/emcw20ucKS Contact us at: https://2ly.link/1z88V #AITraining #LLM #Dataset

??Empower Model Training with #CoohomCloud's Synthetic Data!?? Diversity of data formats is crucial for robotics simulation. High-quality datasets help to develop perception systems that can accurately interpret and respond to the real world. ?? Coohom Cloud offers a comprehensive range of data formats including Semantic, Albedo, Normal, Depth in our high-quality datasets, tailored to enhance your robotics' perception capabilities.?? Find out more! https://2ly.link/1yoDd #ComputerVision #SyntheticData #DataAnnotation #RoboticsSimulation

AI Training Data Costs Are Soaring: It's Time for Coohom Cloud's Synthetic Data Service? An insightful article written by Kyle Wiggers from TechCrunch reveals the above concern in AI development. The skyrocketing costs of training data are pricing out all but the tech giants, While quantity and quality of data both play crucial roles in training sophiscated AI systems. ?? Coohom Cloud's synthetic data solution stands out for its exceptional quality and affordability, democratizing AI innovation. ?? We offer realistic and physically accurate 2D and 3D interior datasets, significantly enhancing AI agents' learning and adaptability.?? Read the article: tcrn.ch/4aIAZRl Learn more about our data solutions: https://2ly.link/1yrKk #CoohomCloud #SyntheticData #ArtificialIntelligence