Building a high-quality dataset is a critical step in developing accurate and effective deep- learning models for computer vision. However, collecting labeled data can be a daunting and expensive process,…
The traditional AI training method is rarely applicable in real-life business use cases simply because it requires an amount of data seldom available to businesses. However, AI agents can also…
Optimizing bed allocation in hospitals based on how patients (randomly) check in is a well-known and complex challenge for which multiple techniques have been used throughout the decades. So much…
A primary challenge for many manufacturers is maintaining quality while also running production fast enough to meet production targets. Achieving that balance requires constant production oversight from human inspectors. To…
There are multiple paths to solving business challenges using data. As the saying goes “for a hammer every problem looks like a nail”. This is also true for applying advanced…
AI agents create value through a variety of levers. Agents may increase quality, reduce costs, increase throughput, or do all the above and more. The value that an AI agent…
Industry 4.0, or the fourth industrial revolution, mostly refers to the shift to a new kind of smart factories and manufacturing end-to-end processes. They leverage a slew of new technologies…
In my last article, I showed you what happens in the second phase of a Bonsai project: Delivery and real-world trials. This included building a simulated environment, training, and validating…
