Machine learning for a more secure and productive steel business

Speaker: 

Gregorio Ferreira, ArcelorMittal

Date: 

31/01/2019 - 13:00

Machine learning and AI has been a trending topic for many years already. However, it is well known the challenges companies are facing to deploy robust solutions taking advantage of this kind of algorithms. The gap between R&D and IT-organisation is still latent, and until both of them don't get to a common point in which the cost and complexity of deploying AI-based solutions are well understood, the possibilities to extract all the value from data are diminished.

In this talk, I will share different cases in which using Machine Learning provided a considerable improvement in existing solutions or just created a new range of possibilities that with traditional techniques was not possible. You will also have the opportunity to see how using computer vision based solutions we are helping the metal business to be more secure and productive.

Historia zmian

Data aktualizacji: 21/01/2019 - 10:36; autor zmian: ()

Machine learning and AI has been a trending topic for many years already. However, it is well known the challenges companies are facing to deploy robust solutions taking advantage of this kind of algorithms. The gap between R&D and IT-organisation is still latent, and until both of them don't get to a common point in which the cost and complexity of deploying AI-based solutions are well understood, the possibilities to extract all the value from data are diminished.

In this talk, I will share different cases in which using Machine Learning provided a considerable improvement in existing solutions or just created a new range of possibilities that with traditional techniques was not possible. You will also have the opportunity to see how using computer vision based solutions we are helping the metal business to be more secure and productive.

Data aktualizacji: 21/01/2019 - 10:20; autor zmian: Jarosław Miszczak (miszczak@iitis.pl)

Machine learning and AI has been a trending topic for many years already. However, it is well known the challenges companies are facing to deploy robust solutions taking advantage of this kind of algorithms. The gap between R&D and IT-organisation is still latent, and until both of them don't get to a common point in which the cost and complexity of deploying AI-based solutions are well understood, the possibilities to extract all the value from data are diminished.

In this talk, I will share different cases in which using Machine Learning provided a considerable improvement in existing solutions or just created a new range of possibilities that with traditional techniques was not possible. You will also have the opportunity to see how using computer vision based solutions we are helping the metal business to be more secure and productive.

Data aktualizacji: 21/01/2019 - 10:19; autor zmian: Jarosław Miszczak (miszczak@iitis.pl)

Machine learning and AI has been a trending topic for many years already. However, it is well known the challenges companies are facing to deploy robust solutions taking advantage of this kind of algorithms. The gap between R&D and IT-organisation is still latent, and until both of them don't get to a common point in which the cost and complexity of deploying AI-based solutions are well understood, the possibilities to extract all the value from data are diminished.

In this talk, I will share different cases in which using Machine Learning provided a considerable improvement in existing solutions or just created a new range of possibilities that with traditional techniques was not possible. You will also have the opportunity to see how using computer vision based solutions we are helping the metal business to be more secure and productive.

Data aktualizacji: 21/01/2019 - 10:17; autor zmian: Jarosław Miszczak (miszczak@iitis.pl)