Can you build an optimized MLOps for your next AI project like a tasty layered cake? | Marek Tatara

2024-09-12

Download

We’ve covered episodes about AI in logistics in the past. Let’s now focus our attention to manufacturing. Some AI applications in this sector include predictive maintenance, quality assurance using computer vision, anomaly detection, and digital twins. Building these solutions takes time and requires accuracy. If developed and operated manually 100%, this approach risks making more errors in your ML models and datasets. Rather than relying on grit, we can automate the entire process and let the AI solution run like cloc...

Building these solutions takes time and requires accuracy. If developed and operated manually 100%, this approach risks making more errors in your ML models and datasets. Rather than relying on grit, we can automate the entire process and let the AI solution run like clockwork.

MLOps (machine learning operations) automates the ML process together with the help of a feedback loop system. It can be divided into layers, like a layered cake. Some of its layers include experiment tracking, dataset monitoring, qualitative tests and explainability layer.

In this episode, we talk to Marek Tatara, Chief Scientific Officer of DAC.digital as he tells us more about how MLOps works, and their experience in building a customized MLOps for the semiconductor industry under a large cooperative EU-funded project.

Listen to our episode if you want to make your ML project more effortless and more reliable at a larger scale.

Who is Marek Tatara?

Marek Tatara, PhD - Chief Scientific Officer and Tech Lead of the AI team at DAC.digital, Assistant Professor at Gdańsk University of Technology, AI/ML Expert at M5 Technology, Member of the Polish Society For Measurement, Automatic Control And Robotics. At DAC.digital, he works on the research agenda of the company and on the implementation of both EU-funded and commercial R&D projects from the field of Computer Vision (especially multi-camera setup, 3D reconstruction, and object detection and tracking), Machine Learning (mainly for computer vision, e.g., object detection, DNN optimization, semantic segmentation), and Embedded Systems (wireless communication for IoT devices and medical devices implementation.

Where to find Marek:

DAC.Digital website
LinkedIn

Resources:

Book recommendation: Modern Control Theory by William Brogan
Aims50 - Artificial Intelligence in Manufacturing leading to Sustainability and Industry 5.0

Time Stamps

(00:00:00) Trailer

(00:01:08) Who is Marek Tatara?

(00:01:50) AI in Manufacturing: Applications

(00:04:18) Concepts behind MLOps

(00:08:18) Custom vs pre-made tools for MLOps

(00:10:41) Building an MLOps project is like building a layered cake

(00:17:08) Adopting MLOps among small and medium manufacturing companies

(00:19:26) Working in an EU funded ML project

(00:21:06) Advice on AI adoption and implementation for SMEs
(00:26:11) Final remarks and book recommendations

--- More on G.M.S.C. Consulting

Follow us on our socials: