The Data-Centric Approach to AI: What It Is and How It Can Benefit Your Business
As industries continue to adopt AI solutions, it has become clear that a fundamental shift is needed to unleash AI's full potential. That shift is data-centric AI. In order to understand the benefits of data-centric AI, it's important to first understand what it is. Simply put, data-centric AI is a way of programming that focuses on data rather than code. Machine learning models have improved over the years, but they are still limited by the quality and quantity of data that is available. With a data-centric approach, businesses can focus on data instead of code, which will allow them to deploy AI and deep learning-based solutions in manufacturing scenarios more effectively.
The benefits of a Data-Centric AI Approach
There are many benefits of data-centric AI, but some of the most notable ones include improved accuracy, increased efficiency, and reduced costs. Machine learning models are only as good as the data that they are trained on, so by focusing on data instead of code, businesses can ensure that their models are always up-to-date and accurate.
Traditional Approach vs. Data-Centric AI
The Inefficient-Traditional Approach
The traditional approach to machine learning, comes with a few challenges:
- Its heavily relied on developers which results in delays to optimize performance and support AI models
- It's a workflow nightmare because different teams use different methods and manage data, making it difficult for them all work together efficiently without any standardization in their process
- Traditional approach relies on rules-based algorithms that can be challenged when it comes across inconsistencies in the data.
This may occur because of working with parts that have complex features or an unclearly defined part defect. In these cases, the Machine learning algorithm may not be able to identify the issue correctly and produce an incorrect output.
The NEW Data-Centric Approach
Data-centric artificial intelligence is the new frontier for computer scientists and data experts. These systems are designed to provide a systematic way for improving data, reaching agreement on its accuracy and consistency. Machine learning models are generated through a data-centric approach and are able to learn from data more effectively. This allows for Machine learning algorithms to be better at generalizing from limited data and making predictions.
How it Benefits Your Business
Improved Performance: The goal of a data-centric approach is to have quality, consistent information that can be used by the AI system. The more accurate and reliable this input becomes over time—the better it will perform in abilities such as learning new concepts or making predictions about future outcomes.
Promotes Collaboration: The data-centric approach to quality management promotes collaboration between managers, experts and developers. They can work together during the development process for defects/ labels that will be resolved by reaching consensus on them or building models before analyzing results so they may make further optimizations if needed.
Eliminate Wasted Time: The data-centric approach reduces development time by allowing teams to work in parallel and influence the AI system's accuracy. By eliminating unnecessary back-and forth among groups, this helps save valuable resources for other tasks that require more attention.
SORBA.ai Your Data-Centric Solution
The data-centric AI software platform by SORBA.ai helps ensure product quality and reduce false positives with industry firsts like standardizing deep learning solutions for faster deployment across multiple facilities, improving accuracy while cutting development time; ultimately increasing production rates to maintain or increase revenue levels!
If you want to learn more about how data-centric AI can benefit your business, contact SORBA.ai today and schedule a free discovery call! Our team of experts will be happy to answer any questions you may have.