Rapid AI Models with Closed Loop Training
Christian Plaichner
CPO
Artificial intelligence (AI) is one of the most sought-after technologies today and with good reason. It has the potential to lighten the workload in virtually any industry, provide people with better decision-making abilities, and enhance outcomes whether that includes improving health or increasing profit margins. As helpful and beneficial as AI is, there are critical limitations to it, and working to resolve that can be essential.
That is where closed loop training, a technology developed by Anyline, comes into play. Before getting into the details of what it is and how it works, consider the following.
The Benefits of AI
No matter what application you apply it to, AI offers benefits. It takes complicated data, sorts it, and provides valuable insights from it. The benefits of AI, dependent on the application it is being used in, include the following:
- Improved accuracy: With fewer human-caused errors, AI is able to perform tasks with less risk of a mistake. In situations related to delicate decision making, that can be incredibly important.
- Digital assistance: AI allows companies to utilize technology for a wide range of tasks. By pulling those tasks out of the hands of people, they allow companies to free up those workers for tasks that people need to complete. That’s a better way to make the best use of your resources.
- Repetitive tasks faster: For tasks that are repetitive, AI can work to alleviate human demand and provide better results. Often, this eliminates tasks that take up too much time.
These are just a few of the many benefits that AI can offer. AI can also provide dozens of other benefits, from reducing labor costs, improving decision making accuracy, and reducing risk to people.
Traditional Method of AI Model Training
While AI promises to offer so many benefits and resources, it is dependent on having access to quality data. For AI to make decisions and perform tasks with such accuracy, it needs to have massive amounts of data available to it. More so, AI models take time to learn. It can take several months and tons of data to train AI models to accomplish the desired tasks.
It’s challenging for AI models to stay up-to-date and accurate. It is never going to be more accurate than the data it is trained on, though. In short, it needs that training to be able to achieve any of these benefits.
Closed Loop Training
This is where closed loop training (CLT) comes into play. This is a much faster method to develop and ready AI models for use. With this method, the comprehensive learning process that AI needs to work through is cut down from months to one or two days. It also does not require nearly as much data to be processed but provides the same level of accuracy.
This state-of-the-art AI-based software from Anyline utilizes a combination of tools including computer vision, optical character recognition, and machine learning. By utilizing these technologies, it can quickly and accurately capture visual information in digital form. Capturing surface depth, analog letters, numbers, and symbols, like those found on utility meters or vehicle parts, is challenging from traditional AI technology and learning methods. CTL improves outcomes by creating a faster and more efficient method for training models.
This allows for CTL to work to create highly accurate results in a smart, continuously improving method. This improves the accuracy of Anyline AI models. The result of CLT is that it creates accurate results with less data than traditionally required. That shortens the amount of time invested from months to just days.
Because accuracy is critical to the function and benefits of mobile data capture, having a way to improve accuracy to the next degree while also speeding up the process dramatically is critical. Anyline developed CTL over the previous three years. Anyline developed a CLT factory to create customizable AI-based computer vision solutions. The results are extraordinary, and anyone in a wide range of industries will quickly and easily see the value that CLT brings to the table.
