Industrial AI Podcast Pixel Komma Ton

We can't give anything away yet, but anyone who was at our AI in the Forest event will remember. You'll have to be patient until Monday. See you at the fair.

Silo AI and TurkuNLP are developing a family of multilingual open source LLMs with the aim of strengthening Europe's digital sovereignty and democratising access to LLMs. Developing baseline models that are in line with European values is crucial to this effort to ensure that they are based on data and information that accurately represents the different languages, citizens, organisations and cultural landscape of the European Union. This approach is not only in line with European values, but also enables sovereignty over how downstream applications and value are created.

The success was attributed to the combination of the low-resource Finnish language with resource-rich languages. The team worked to determine the optimal frequency of data reuse for low-resource languages during training, and integrated translated text pairs from English and Finnish. This strategy, which relies on a cross-linguistic signal to improve the model's understanding of the relationships between the languages, proved crucial in achieving excellent performance in the low-resource languages without compromising performance in English.

AINode is the third internal node after ConfigNode and DataNode in Apache IoTDB. This node extends the capability of IoTDB to perform machine learning analysis on time series data by interacting with the DataNode and ConfigNode clusters. AINode allows the integration of existing machine learning models by registering them and executing time series analysis tasks through simple SQL statements on specified time series data. This seamlessly combines model creation, management, and inference within the database engine. The framework currently supports common machine learning algorithms or proprietary models for typical time series analysis scenarios like time series prediction and anomaly detection.

In his group they conduct research to create intelligent systems, which can work autonomously and in collaboration with humans to increase the safety, reliability, and productivity of industrial plants and processes. For this purpose, they leverage process modelling, model predictive control, optimization, and machine learning.

In the podcast, we talk about the architecture of the Industrial Copilot, how Schaeffler wants to use it, why the customer provides data, how it is used and what the next steps are in the area of Industrial AI and GenAI.

In this episode, Peter Seeberg talks to Stefan Suwelack about RAG for industry, the role of data and the Data Centric Approach and about the Industrial AI Canvas. Stefan works for Renumics. He and his team work for companies like Rehau, Festool or Polytec.

We thank our partner **HANNOVER MESSE**
https://www.hannovermesse.de/de/

Job offering: Heilbronn is looking for a professor
https://cdn.hs-heilbronn.de/ce3c0933328f570c/d9e7413e6a15/232-P-IT.pdf

Stefan Suwelack https://www.linkedin.com/in/stefansuwelack/