Teaching Apps To Think For You

Artificial Intelligence
& Machine Learning

Artificial Intelligence and Machine Learning is helping us make our machines and software smarter. Our AI and ML powered digital solutions have human-like intelligence and cognition and are capable of learning from data and past experiences to get smarter with time. Using these technologies, businesses can manage their available data efficiently and improve their operations and products based on the insights. When your software is able to think and improve, you are able to spend more time thinking about what matters the most- your customers.

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Artificial Intelligence

What is it

Artificial Intelligence and Machine Learning is helping us make our machines and software smarter. Artificial Intelligence is the science and engineering of making intelligent computer systems, software and mobile apps. Whereas, Machine Learning, an application of Artificial Intelligence, is a data analytics technique that teaches computers to do what comes naturally to humans: learn and improve from experiences. Using our digital solutions powered by AI and Machine Learning, businesses can manage their available data efficiently and improve their operations and products based on the insights. In some cases, our digital solutions are intelligent assistants that enhance our abilities as humans, and professional – making us more and more productive.

How it works

Artificial Intelligence uses computers to understand and learn human intelligence and cognition and make decisions and predictions. Machine Learning algorithms use computational methods to “learn” information directly from large amounts of input data without relying on a predetermined equation as a model. The algorithms adaptively improve their performance as the number of samples for learnings increase.

Software and apps can make calculated suggestions and/or predictions based on analyzing this information and perform tasks that are considered to require human intelligence. This includes activities like speech recognition, translation, visual perception, and more. This creates a dynamic feedback loop, which allow them to efficiently generate more models to gain further insights, even more accurately, without requiring additional resources or human interaction. ML uses the method of enabling machines by training algorithms such that they cannot only learn how to make decisions but make accurate predictions as well.

Use cases

The applications of AI and Machine Learning are not limited to a field or industry. With continuous advancement in this field, machines are becoming increasingly self-organized and self-disciplined, seamlessly producing greater value for businesses. For example, media sites rely on machine learning to sift through millions of options to give you song or movie recommendations. Retailers use it to gain insight into their customers’ purchasing behavior. These digital solutions are being used every day in making critical decisions in medical diagnosis, stock trading, energy load forecasting, and more.

In our SaaS solution, PackageX, the challenge was that computers did not do an efficient job of reading text from an image. Not only did we need to teach a model how to read text – even handwritten text – but also understand what it was reading. For example, package labels have multiple names on them, multiple barcodes, labels, and lots of extra information. Some people have nicknames, different companies have different labels, the problems and variations seemingly went on and on. Therefore, it was important that the model could learn and understand a label or handwriting it had never seen before. And using AI and ML, we were able to deliver a smart package tracking app, PackageX, that solved the challenges related to the last yard of package delivery.

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