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Spingence's News
02.11
2023
Shaping Processes through Experience for Limitless AI Value on the Production Line
AINavi 2.0 integrates experience to shape processes,
enabling AI to be of unlimited value on the production line.
During the development and maintenance of AINavi, Spingence's development team has always been highly sensitive to market introduction trends. Our past observations have made us realize that as AI vision inspection technology continues to expand in the market, the product requirements are bound to keep changing.
For example, in 2020, we predict that 2022-2024 will be the stage of AI competition, with a large number of system integrators or small software companies due to the lowering of the entry threshold of AI technology. Through the previous phase of testing, users will be more concerned about the comprehensive value of software standardization and modularization, the actual application experience of AI technology in specific industries, as well as the long-term maintenance and future scalability of the products.（Recommended Article：Visual Transformation: Evolution and Trends in Industrial AI Visual Inspection）
At this point in time, we have also been working with our customers for a long time, and we are gradually able to piece together the needs of the next stage of use. Taking this opportunity, the Spingence team reorganizing the product structure and planning of AINavi at the end of 2022. In order to better meet the demands of the users, Spingence's R&D team has embarked on the ambitious AINavi 2.0 project.
In AINavi 2.0, we care about more than just AI implementation, we also look forward to solving our customers' long-term production and process problems and challenges. Therefore, we have transformed our past import experience into a software process, with a more flexible software architecture, to help users continue to iterate on AI models to better meet the needs of the production line, enabling AI to be of unlimited value. There are several highlights in this update, which are summarized below.
Project-based Management : Retain Maximum Flexibility in The Use of Assets
In AINavi 2.0, we have changed the way of model management to manage models and training sets independently, which retains the flexibility and reduces the memory burden at the same time. The purpose of this change is to facilitate users to utilize the training sets repeatedly or more diversely, and to quickly select the required graphics for different levels of model training.
In AINavi 2.0, we have changed the way of model management to manage models and training sets independently, which retains the flexibility and reduces the memory burden at the same time. The purpose of this change is to facilitate users to utilize the training sets repeatedly or more diversely, and to quickly select the required graphics for different levels of model training.
Flexible Model Iteration : Evolution from Experience
Turning experience into process is our core concept.AINavi 2.0 model iterations are not only based on software architecture innovations, but also on Spingence's past experience in various industries and factories. Regardless of your level of AI mastery, our process allows you to realize models that meet the needs of your production line.
Open Ecosystems : Compatible with Multivariate models
We understand that the power of innovation comes from diversity. Through an open ecosystem, we will support the import of third-party models in addition to the original Spingence algorithms optimized for industrial inspection purposes.
We believe that there is no such thing as the "best" generic model, only the one that best suits the needs of your production line. When you develop your own algorithms according to your needs, we are committed to providing excellent and convenient software to save your organization's resources and time for development and maintenance.
Personalized Inference Settings : Get the best judgement in real time
Every product's test standard is unique, and AINavi 2.0's inference settings help you make the best judgment. The interface is designed to allow you to easily adjust the inference thresholds to meet changing standards, no matter how they change.
Are these pain points bothering you when importing AI defect detection?
In the process of AI technology application, we understand that many users are often caught in the predicament of poor model performance, unable to optimize, and feel overwhelmed. AINavi 2.0 aims to change this situation, providing new tools and strategies to help users effectively improve the model performance, so as to achieve better detection results.
At the same time, we know that labeling data is time-consuming and labor-intensive. And we often have to start all over again, whether it's for modeling or inspection needs. AINavi 2.0 is equipped with easy-to-use marking tools such as box selection, polygon, and paintbrush. We have even launched a marking assistant - Quick Mark Widget, which is able to mark defects easily with one click this time.
In addition, during the production process, inspection standards often vary depending on line planning, which can lead to models needing to be re-calibrated and retrained.This is not only repetitive but also inefficient.
AINavi 2.0 is a solution to the pain points encountered by users in practical applications, such as modeling effects, time-consuming annotation, and inspection standard variations. Welcome to contact us to get AINavi 2.0 for trial!