Reijo Silander, Emilio Marinone and Thorsten Jacobs visiting the Degree Project Fair at KTH Kista on Wednesday 9th October, 2019. We got the opportunity to meet a lot of students who are interested in writing their Master’s thesis in the field of Machine Learning.
A team of Seavus experts has relentlessly been working on the implementation of a new AI solution for LVI-Numero Oy (LVI-INFO). The new AI member of the team is a cost-effective solution that will reduce not only costs but also time and human resources. Read more about the whole implementation process and what it means to have AI in the business environment in this interview with Magnus Siren, the Managing Director at LVI-Numero Oy (LVI-INFO). He talks about the whole experience with AI and the challenges of creating a solution that will be a win-win solution for all parties involved.
AI projects require a different approach than traditional IT projects in order to succeed. This article covers the 5 main differences between AI and traditional IT projects that would help you adopt the right approach towards clients. First and foremost, specification is completely reversed. What this means is that instead of defining rules, you give the result as an input that will train the AI. This, in turn, means that you have to know the data you are working with. AI projects need to be conducted predictively, with a project design that supports predictive project development.
There are many AI solutions on the market – however, expecting AI solutions marketed as finished products should be taken with a pinch of salt. This article is dedicated to the steps that need to be taken, from AI algorithm to production solutions. All you have to do is make sure that you data is within your ecosystem. Once you have identified a spot where AI solution could be implemented, there are some steps you need to have into consideration. But no worries, a team of experts will help you go through each step.