Industrial AI Podcast Pixel Komma Ton

Hochreiter's xLSTM paper was eagerly awaited. Now it is here. Quote: "We have enhanced LSTM to xLSTM by exponential gating with memory mixing and a new memory structure. xLSTM models perform favorably on language modeling when compared to state-of-the-art methods like Transformers and State Space Models. The scaling laws indicate that larger xLSTM models will be serious competitors to current Large Language Models that are built with the Transformer technology. xLSTM has the potential to considerably impact other deep learning fields like Reinforcement Learning, Time Series Prediction, or the modeling of physical systems."

Industrial applications in particular are eyeing xLSTM. The next step is the commercial distribution of the architecture. We met Timo Gessmann, CTO of Schunk, at the Hannover Messe. He uses a GenAI approach to accelerate labeling.

The Industrial AI Podcast reports weekly on the latest developments in AI and machine learning for the engineering, robotics, automotive, process and automation industries. The podcast features industrial users, scientists, vendors and startups in the field of Industrial AI and machine learning. The podcast is hosted by Peter Seeberg, Industrial AI consultant and Robert Weber, tech journalist.

Their mission: Demystify Industrial AI and machine learning, inspire industrial users.

The hosts:

Peter Seeberg is an Industrial AI and machine learning expert for the manufacturing industry. He worked over 25 years in IT (Intel) and 10 years in Automation. He co-initiated the Industrial Data Intelligence Startup (Softing) where he was responsible for managing machine learning projects in industrial environments. Today he advises companies when it comes to Industrial AI and machine learning. Together with Robert Weber, journalist for industrial topics, he discusses AI and ML applications, standards, and education topics, make or buy decisions as well as regulation for AI in manufacturing.

Zeki's insights are purely data-driven, based on a carefully curated dataset that brings together unique technologies and data to provide insights into 140,000 of the world's top AI scientists and engineers, all with advanced skills and expertise, most of whom are at the early stages of their careers.

The market for top AI talent is diversifying and deepening. Large companies hire five times more top AI scientists and engineers than the Big Five (Amazon, Apple, Google, Meta, Microsoft). New national AI champions are emerging outside the US.
The healthcare sector, particularly in Europe, has attracted twenty times more top AI talent over the past 10 years. The global market is also shifting away from the strong dominance of the US. National champions are emerging in some major economies, anchoring talent in their own countries. The characteristics of the best AI talent who choose to go abroad or stay close to home. There are consistent global trends that emerge early in the careers of top AI talent.

Thanks for listening. We welcome suggestions for topics, criticism and a few stars on Apple, Spotify and Co.

We thank our partner **SIEMENS** their Industrial AI approach -> [here ](https://www.siemens.com/global/en/products/automation/topic-areas/artificial-intelligence-in-industry.html)


Our guest: Thomas Hurd [more](https://www.linkedin.com/in/thomas-hurd-1128031b8/)

The report [more](https://www.thezeki.com/the-state-of-ai-talent-2024)

Many companies use GenAI to generate code. Josef Waltl and his team take the opposite approach. They have old code translated. Josef explains how they do this in the podcast interview.

Thanks for listening. We welcome suggestions for topics, criticism and a few stars on Apple, Spotify and Co.

We thank our partner **SIEMENS**
https://www.siemens.de/de/

Our guest Josef Waltl [more ](https://www.linkedin.com/in/josefwaltl/)

Fabian Bause was actually very sceptical at our AI in the Forest event, which was all about AutoML. Then he called us a few weeks ago and we were surprised. Beckhoff offers its customers and also non-Beckhoff users an AutoML tool. The automation company is thus breaking new ground. Has he changed his mind? And if so, why? Fabian explains it to us.

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.