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AI and Machine Learning, Data Science and Big Data

Use methods of the future to improve your business results today! We know artificial intelligence, machine learning, data science, big data and their different applications.

The field of information technology has achieved considerable progress with the help of artificial intelligence, machine learning, data science and big data. These tools allow companies to effectively generate significant customer and business value.

On the other hand, the wrong investments may prove costly and will not provide the desired results. This is why it is especially important to choose a development partner who can realistically predict the costs and results of the project.

Our customer references

ABB, Atostek and Telia have developed the first industrial 5G AI application to help users assemble frequency converters.

Atostek has delivered machine-learning software to Destia for e.g. the identification and classification of certain objects found at road settings.

For Lassila & Tikanoja, Atostek delivered a data analytics project that allowed the company to significantly increase the efficiency of their waste collection operations.

Artificial intelligence research projects at Atostek

Atostek has invested in artificial intelligence and its various applications also via publicly funded research projects. The international ITEA3 Oxilate project aims to develop machine learning systems of the future for industrial environments.

Atostek’s Jasmine project, funded by Business Finland, is searching for AI-based solutions that would allow health care services to utilize large health data sets in the context of their work. Using e.g. Findata’s health and social data pool for secondary use, the project aims to develop new types of software that fit the classification for medical devices.

Artificial intelligence

Artificial intelligence is a broadly defined field of information science. It covers all efforts to make computers or software function as though they were intelligent.

Definition of artificial intelligence

1a branch of computer science dealing with the simulation of intelligent behavior in computers

2the capability of a machine to imitate intelligent human behavior

Machine learning

Machine learning is a subtype of artificial intelligence. Machine learning aims to achieve its goals using learning either by training an algorithm in advance with training data, or by designing an algorithm that continuously learns more as it is used. Sometimes, these two methods can be combined. Machine learning is the most common subtype of artificial intelligence applied in practice today, and it can be based on e.g. neural networks.

Definition of machine learning

1the process by which a computer is able to improve its own performance (as in analyzing image files) by continuously incorporating new data into an existing statistical model. The company is curating the overall topics manually, but Twitter will be relying on machine learning to intelligently populate the topics themselves so that the tweets can stay up to date. – Lucas Matney (Merriam-Webster)

2the branch of computer science dealing with the creation and use of computer software that employs machine learning. An entire subspecialty known as machine learning is devoted to building algorithms that allow computers to develop new behaviors based on experience. – Adam Piore (Merriam-Webster)

Data science and Big data

Data science and big data are concepts that are closely related to one another and to machine learning and big data. The training of machine learning algorithms requires data, which is used as training material. This is why the processing of data, the separation of essential information and other related activities are considered their own field of study. Big data means working with data pools that are so big that conventional database solutions are simply not sufficient.

Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains. Data science is related to data mining, machine learning and big data. (Wikipedia)

Definition of big dataan accumulation of data that is too large and complex for processing by traditional database management tools. (Merriam-Webster)

How to utilize data in decision making

Many companies constantly produce a huge amount of data, but the data may not be utilized in an optimal way. Understanding the data can actually make decision making easier. What to consider when utilizing data-based information?

Download our white paper and learn more about data-driven decision making!


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