Breaking Free from POC Purgatory: Transitioning AI Projects to Production
Transitioning a promising AI Proof-of-Concept (POC) into a fully operational production environment is a critical, and often challenging, step in realizing the value of AI investments. The panelists of the “AI-Driven Process Optimization: Achieving Faster Turnarounds and Higher Margins” session
What does it take to work with Generative AI Models
The world of AI is evolving rapidly, and if you're a machine learning engineer, you might already feel drawn towards generative AI. Generative models are more than just a trend—they represent a leap towards a more creative AI future. But
Time Series Data as the Backbone of Smart Grid IIoT Solutions
The smart grid transformed modern energy management by integrating digital technology into traditional power grids. It enhances real-time monitoring, control, and optimizes energy distribution and consumption. This change is crucial for meeting the growing need for reliable, sustainable, and efficient
[White paper] Vibration Monitoring On-Device with Machine Learning
In the cutting-edge realm of vibration monitoring and predictive maintenance, this white paper written by Polyn Technology delves into how machine learning and neural networks revolutionize the way industrial and vehicular environments predict and prevent equipment failures. Highlighting the transition from
Machine Learning and Data Engineering Applications in Agriculture
"In God we trust, all others bring data." William Edwards Deming In this article, we show the importance of interference between Machine Learning, Data Engineering, and Agriculture. The main problems that farmers face on an everyday basis, such as climate changes,
Machine Learning in agriculture: challenges and solutions
In recent years, machine learning has become one of the most promising technologies. And while it's often associated with consumer applications like smartphone personal assistants and social media recommendations, its potential extends far beyond that. Agriculture is a great example of
Leveraging IIoT, AI and Machine learning to optimize operations in manufacturing and infrastructure
Manufacturing is poised to play a critical role in shaping the economy for the next decade and beyond. The opportunities are endless if the advanced manufacturing industry can strengthen its innovation vision and embrace the reality of end-market disruption, but
Why a closed loop is key for machine learning
By now, the positive impact of digitalization in manufacturing environments is widely recognized — reduced costs, improved operational efficiency and greater productivity. But digitalization is not fulfilled by making just a single change. It is a continuous cycle of updates
Ensemble Modeling: How to Improve Machine Learning
What is Ensemble Modeling? Ensemble Modeling is a technique used to improve the results of Machine Learning projects. This Ensemble Modeling technique allows to obtain a better predictive performance compared to the models from which it is made up, thanks to