Artificial intelligence sounds like expensive high-performance computers and complex algorithms. But with the right data and technologies, it’s really easy to get started. Especially if you start with simple use cases and platforms.
Tags Machine Learning
Artificial intelligence: Many companies want to take advantage of this new trend. Especially but not only, AI-based application cases require the right data basis. A comprehensive data strategy also clarifies other questions related to processes or responsibilities. Such a strategy is fairly easy to develop and implement if you use the right approach.
AI applications in marketing, sales and product management. Use cases and recommendations for companies that want to use artificial intelligence.
Industrial companies are increasingly launching promising AI projects. But after the proof-of-concept, the process falters: important data is missing, the results are disappointing, or the concrete use case is not so clear after all. What you can do about it.
Given today’s flood of data, it is becoming increasingly difficult to evaluate all the information quickly and carefully. Intelligent systems can help by performing an initial analysis based on specific keywords and contexts.
Microsoft Ignite conference will kick-off in a few days. Here‘s my personal list of expectations, narrowed down to productivity topics and business applications for operations.
Modern sensors and ML algorithms can provide valuable services to ensure that people in old age are adequately cared for in the future.
Machine learning methods can be used to optimize production processes. A practical example shows how machine learning contributes to the detection of pseudo defects in quality assurance.