A better way for AI to learn


A better way for AI to learn

The learning process for AI and Machine Learning can be costly and time-consuming – so what if you could train your model by yourself?

Artificial Intelligence (AI) and Machine Learning (ML) have revolutionised so many industries and sectors. However, even today, the process of training programmes on what they need to know with algorithms and vast amounts of data can take time and effort.

This extended process of training the AI decision making model with the advice and support of a specialist consultancy can also be expensive. If the AI/ML technology is required to perform a different task, then new data and use cases need to be inputted for learning purposes.

Imagine, for instance, that you have an AI/ML system checking bottles coming off a production line to ensure that there are no cracked or broken items, that labels are correctly applied and that the lids are secured. This could be working well – until the shape and design of the bottle are changed, in which case the system will have to learn something new by looking at examples of the updated product. Such a change might also require modification of the code.

In other situations, the machine would have to learn to recognise objects that are dirty or damaged in a wide variety of ways. Exactly how does a dirty container, for instance, compare with a clean one? The machine would have to learn from hundreds of examples.


To overcome the problem of having hundreds of examples available and updating them to train new models, Konica Minolta has created AI Studio. This solution for automated inspection in manufacturing and warehouse is benefitting a growing number of companies. Traditionally, the setup and long-term operation of such systems require AI experts to perform the analysis, initial configuration, and update of the inspection system any time a new product is introduced, a defect identified, or conditions changed. However, AI Studio enables customers to set up and update the system themselves with a simple, intuitive interface whenever the storage of manufacturing changes.

With Konica Minolta AI Studio the training process involves the machine itself collecting images. The next stage is annotation. Here, training metadata is added to the images, and this is accelerated by AI Studio annotation suggestions. In the third part of the process, the training stage, the model is both trained and then tested before finally, it is deployed, using AI Studio’s one-click deployment or download.


One client of Konica Minolta’s AI Studio is a bakery in Croatia called Mlin I Pekare. The company had a requirement for production statistics, specifically, to recognize different product types among 12 different varieties. Here, AI Studio counts each product type and provides a set of reports for managers.

As manufacturers and other companies find themselves having to move more quickly in these economically uncertain times, clients also appreciate the speed with which AI Studio can be up and running – usually within hours of the camera being installed.

Thanks to this rapid installation and AI Studio’s ability to learn by itself, R&D experts can get ahead of the competition by focussing on new product features. Models created using AI Studio are compatible with other Konica Minolta-based solutions and common AI frameworks.


The current economic challenges faced by businesses as well as difficulties with supply chains and rising energy bills mean that organisations need to be more agile and cost-effective than ever before. This is where Konica Minolta AI Studio can help to improve efficiencies and agilities and enable businesses to thrive in these challenging, uncertain times while maintaining margins and developing a competitive advantage.

Don’t waste your time: our AI Studio is ready for you to try it.

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