DAENET - Creating Education and AI Solutions through Workshops
DAENET not only offers workshops for further education but also provides a platform for companies to sensibly develop and implement AI solutions. Our workshops serve as guides to introduce customers to the world of AI and assist them in creating innovative solutions for their businesses.
An outstanding example is the ACP-Copilot that we present in our workshops. This Copilot solution provides access to internal content management platforms, a portfolio finder, and interactive chat functions for various roles within the company. Sales representatives can specifically prepare for client meetings, while service desk personnel can handle specific inquiries and tickets.
Our Workshop Initiative
The workshops are not merely educational events but also practical training sessions for implementing AI solutions. We demonstrate how companies can utilize innovative technologies like the ACP-Copilot to optimize their internal workflow and increase efficiency.
Through practical examples and interactive exercises, we showcase how AI tools like the ACP-Copilot can be employed across different business sectors. This enables employees to structure their work better and cater more precisely to their customers’ needs.
How Can You Participate?
Visit our academy page or the Azure Marketplace to explore our workshops and learn more about integrating DAENET’s AI solutions into your company. Expand your knowledge and discover the possibilities that AI offers to streamline your business processes.
For specific information about offered workshops and solutions, please visit the official DAENET website: https://daenet.de/de/academy/ and the Azure Marketplace.
What are large language models and how do they work?
Large language models are advanced artificial intelligence models trained on extensive datasets to develop a deep understanding of language. These models use complex neural networks to comprehend, process, and generate natural language.
“Prompts” and what’s behind them?
Strategies for Prompts Prompts are text fragments or instructions presented to an AI model to trigger specific types of responses or behaviors. Strategies for prompts involve precisely formulating requests or instructions to obtain particular results from a language model.
“Embeddings” – Meaning and Application
Embeddings are representations of words or sentences in a vector space that reflect the semantic relationships between them. These are used to represent words or sentences in a form that can be more easily processed by AI models.
Integration with proprietary data and systems Integrating large language models with proprietary data and systems enables companies to develop tailored AI applications that align with their specific requirements. This allows leveraging existing information to achieve more precise and relevant results.
Relevant technologies and concepts: “RAG,” tools, plugins, orchestration, copilots
RAG (Retrieval-Augmented Generation) is an approach that combines the benefits of information retrieval and text generation. Tools, plugins, and orchestration solutions are essential for efficiently integrating large language models into enterprise systems. The copilot provides additional functionality and interaction in various corporate workflows.
Model customization options (prompts, adaptations, fine-tuning) Large language models offer the ability to adapt to a company’s specific requirements by refining prompts, making adaptations, and fine-tuning models based on enterprise data and requirements.
So-called “Open Source” models and Local language models
Open-source models are models whose source code is freely available to the public. Local language models refer to models specifically designed for processing and understanding a particular language or region.
Multimodal models, image generation, and other digital content
Multimodal models integrate various types of data like text, images, and sound to create more comprehensive and versatile AI models. These models enable generating images and other digital content based on text descriptions or vice versa.
These topics are crucial components of how large language models function and are applied, offering insights into the diverse possibilities for deploying these models across various domains.
Our Conclusion
We strongly believe that in companies, it’s crucial to alleviate employees’ fears regarding AI solutions and instead highlight the benefits of empowerment and liberation from monotonous administrative tasks. The introduction of AI not only offers the opportunity to create more efficient processes but also creates space for creative, conceptual work and a stronger focus on interpersonal relationships.
By automating repetitive tasks, AI enables employees to concentrate on more challenging, inspiring activities that require human thinking, empathy, and decision-making. The time previously spent on tedious, routine tasks can now be utilized for innovation, collaboration, and developing solutions for complex problems.
It’s important to emphasize that in the future, only those employees in a thriving work environment will thrive who are willing to embrace change and harness the opportunities presented by AI. It’s not about replacing people with technology but empowering them to elevate their skills to a higher level and advance their professional development in a changing work landscape.
By dispelling fears about AI solutions and focusing on empowering employees, we create an environment where innovation and creativity can thrive. It’s time to embrace transformation and prepare employees for a future where collaboration with AI is an integral part of a successful business.