46 min
52. Markus Keiblinger - Texterous - Building custom LLM Solutions Austrian Artificial Intelligence Podcast
-
- Technology
# Summary
For the last two years AI has been flooded with news about LLMs and their successes, but how many companies are actually making use of them in their products and services?
Today on the show I am talking to Markus Keiblinger, Managing partner of Texterous. A startup that focus on building custom LLM Solutions to help companies automate their business.
Markus will tell us about his experience when talking and working with companies building such LLM focused solutions.
Telling us about the expectations companies have on the capabilities of LLMs, as well on what companies need to have in order to be successfully implementing LLM projects.
We will discuss how Textorous has successfully focused on Retriever Augmented Generation (RAG) use cases.
RAGs is a mechanism that makes it possible to provide information to an LLM in a controlled menner, so the LLM can answer questions or follow instructions making use of that information. This enables companies to make use of their data to solve problems with LLMs, without having to train or even fine-tune models. On the show, Markus will tell us of one of these RAG projects and we will contrast building a RAG system based on Service Provider offerings like OpenAI or self hosted open source alternatives.
Last but not least, we talk about new use cases emerging with multi-modal Models, and the long term perspective that exists for custom LLM Solutions Providers like them in focusing on building integrated solutions.
## AAIP Community
Join our discord server and ask guest directly or discuss related topics with the community.
https://discord.gg/5Pj446VKNU
## TOC
00:00:00 Beginning
00:03:31 Guest Introduction
00:06:40 Challenges of applying AI in medical applications
00:17:56 Homogeneous Ensemble Methods
00:25:50 Combining base model predictions
00:40:14 Composing Ensembles
00:52:24 Explainability of Ensemble Methods
## Sponsors
- Quantics: Supply Chain Planning for the new normal - the never normal - https://quantics.io/
- Belichberg GmbH: Software that Saves the Planet: The Future of Energy Begins Here - https://belichberg.com/
### References
- Markus Keiblinger: https://www.linkedin.com/in/markus-keiblinger
- Texterous: https://texterous.com
- Book: Conversations Plato Never Captured - but an AI did: https://www.amazon.de/Conversations-Plato-Never-Captured-but/dp/B0BPVS9H9R/
# Summary
For the last two years AI has been flooded with news about LLMs and their successes, but how many companies are actually making use of them in their products and services?
Today on the show I am talking to Markus Keiblinger, Managing partner of Texterous. A startup that focus on building custom LLM Solutions to help companies automate their business.
Markus will tell us about his experience when talking and working with companies building such LLM focused solutions.
Telling us about the expectations companies have on the capabilities of LLMs, as well on what companies need to have in order to be successfully implementing LLM projects.
We will discuss how Textorous has successfully focused on Retriever Augmented Generation (RAG) use cases.
RAGs is a mechanism that makes it possible to provide information to an LLM in a controlled menner, so the LLM can answer questions or follow instructions making use of that information. This enables companies to make use of their data to solve problems with LLMs, without having to train or even fine-tune models. On the show, Markus will tell us of one of these RAG projects and we will contrast building a RAG system based on Service Provider offerings like OpenAI or self hosted open source alternatives.
Last but not least, we talk about new use cases emerging with multi-modal Models, and the long term perspective that exists for custom LLM Solutions Providers like them in focusing on building integrated solutions.
## AAIP Community
Join our discord server and ask guest directly or discuss related topics with the community.
https://discord.gg/5Pj446VKNU
## TOC
00:00:00 Beginning
00:03:31 Guest Introduction
00:06:40 Challenges of applying AI in medical applications
00:17:56 Homogeneous Ensemble Methods
00:25:50 Combining base model predictions
00:40:14 Composing Ensembles
00:52:24 Explainability of Ensemble Methods
## Sponsors
- Quantics: Supply Chain Planning for the new normal - the never normal - https://quantics.io/
- Belichberg GmbH: Software that Saves the Planet: The Future of Energy Begins Here - https://belichberg.com/
### References
- Markus Keiblinger: https://www.linkedin.com/in/markus-keiblinger
- Texterous: https://texterous.com
- Book: Conversations Plato Never Captured - but an AI did: https://www.amazon.de/Conversations-Plato-Never-Captured-but/dp/B0BPVS9H9R/
46 min