October 25, 2024, by Benjamin von Deschwanden and Martin Keller, Acodis

Acodis together with data innovation alliance organized a webinar, diving into the essential process of turning complex documents into AI-ready data, setting the foundation for implementing Retrieval-Augmented Generation (RAG) in real-world scenarios.

You  can watch it on demand here https://www.acodis.io/webinar-the-role-of-documents-in-rag-applications

The webinar is designed for data and analytics professionals aiming to bridge the gap between their current data and the AI capabilities of tomorrow. You’ll discover the critical role documents play in RAG applications and gain practical insights to help you streamline data extraction, uphold data quality, and maintain traceability. With step-by-step guidance, you’ll leave equipped to elevate your organization’s data processes, ensuring every document can be harnessed as a valuable AI asset.

What You’ll Learn:

1. Mastering Document Complexity
   Not all documents are created equal; they vary greatly in format, structure, and language. This section of the webinar breaks down the different types of documents and offers techniques for managing complexity, enabling you to create a foundation for accurate data extraction.
2. Achieving High Data Accuracy and Traceability
   Clean, reliable data is critical to successful AI applications. You’ll learn advanced techniques for extracting high-quality data and ensuring traceability so your AI outputs are consistent, dependable, and ready for complex applications like analytics, intelligent automation, and advanced querying.
3. Implementing RAG in Your Organization
   RAG (Retrieval-Augmented Generation) has the potential to change the way your organization approaches data retrieval and interaction. In this segment, we cover actionable steps to incorporate RAG into your workflows, helping you maximize the value of your data and enhance AI-driven solutions for customer support, internal knowledge management, and more.

Why You Should Watch This Webinar

In an increasingly competitive market, being able to effectively harness data can be a defining advantage. The ability to transform documents into AI-ready data enables you to:

• Improve analytics and insights across departments
• Enhance the efficiency of internal processes
• Reduce time spent on manual data handling through automation

Ideal for data architects, analytics leaders, and digital transformation teams, this webinar provides a clear roadmap to navigate the complexities of document-based data and unlock its full potential with cutting-edge RAG applications.

To dive deeper into AI-ready data strategies, download our detailed whitepaper, AI-Ready Data Explained, covering more techniques and real-world examples for successful data transformations.

Watch the Webinar | Discover more about Acodis

October 18, 2024, by Jürg Meierhofer, ZHAW

The 2024 Smart Services Summit invited academics, industry experts, and practitioners to explore the transformative impact of digital technologies and artificial intelligence on value co-creation within service ecosystems. This year’s theme emphasized the critical intersections between technology and collaborative value-creation processes, highlighting how these elements reshape business models, customer experiences, and service management.

The summit highlighted the effective implementation of AI-powered value co-creation, especially in the development of smart product-service systems (PSS). Case studies demonstrated practical applications and benefits of this approach. Keynotes emphasized the importance of building a vision for smart services, both within and outside the factory. This vision includes profit sharing and risk management as essential components of value co-creation.

The concept of an industrial metaverse was explored, where, e.g., technicians can prepare for tasks using a digital twin environment, supported by AI-generated field service reports. Transformational leadership was identified as a key factor for the effective adoption of technology. This involves focusing on user-centric designs, multilingual communication, and continuous engagement.

Throughout the summit, several critical insights and discussions emerged, shedding light on various aspects of AI and its integration into different sectors. One of the primary topics was the ethical challenges that arise at the intersection of legal frameworks and value creation. This is particularly relevant in the context of AI, where balancing innovation with ethical considerations in big data-driven business is crucial. Privacy concerns in marketing were also a significant focus. Various case studies from retail companies illustrated different approaches and challenges in addressing these concerns. Discussions also covered the use of data analysis for global sustainability, integrating environmental, economic, and social wellbeing into value co-creation strategies.

Several emerging themes were identified during the summit. One such theme was balancing value creation between individuals and organizations, ensuring that business value complements individual value.

October 09, 2024, by Gundula Heinatz Bürki, data innovation alliance

The Swiss Conference on Data Science (SDS) is Switzerland’s premier event for applied data science. The conference brings together leaders and science and business experts to exchange ideas and drive innovation in products and services, with a focus on the Swiss market. The SDS2024 took place in Zurich on May 30-31 at The Circle Convention Centre, Zurich Airport. If you want to get an impression how it was, have a look at the SDS2024 Flashback Video!

The 2-day conference started with an interactive workshop day to provide in-depth, practical and application-oriented insights into the latest developments in the field of data science and Artificial Intelligence. Over 450 participants took advantage of these opportunities and were able to benefit from exciting and professionally prepared and conducted workshops. Six of the workshops were supported by the Innovation Booster Databooster to identify challenges and discuss possible ideas for radical solutions.

Real World Applications of LLMs for Business and Industry

The first workshop addressed challenges and solutions in the cleantech sector and was organized and moderated by D ONE (Gabriel Levaillant, Andrei Dmitrenko and Thanos Spinoulas).

This workshop aimed to delve into the real-world applications of Large Language Models (LLMs), targeting both technical and business professionals. The agenda included a balanced mix of hands-on coding and brainstorming sessions to apply LLMs in addressing modern business challenges. 

Participants got a comprehensive introduction to LLMs, and then moved into developing a web application using LLMs. Subsequent sessions focussed on performance and cost analysis, optimizing solutions, and exploring various applications. 

The attendees gained practical skills and strategies for using LLMs efficiently in diverse scenarios.

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Elevating Business Through Social Values – The Companies’ Perspective and Future Challenges

The 2nd workshop dealt with elevating companies through social values and related challenges. This workshop was organized by Jürg Meierhofer (ZHAW School of Engineering & data innovation alliance – Head Expert Group Smart Services) and Adrienne Schäfer (Lucerne University of Applied Sciences and Arts – School of Business).

Sustainable business practices focus on considering the impact on the environment, society, and the economy. While economic and ecological sustainability are already firmly anchored in practice, the social dimension of sustainability tends to be neglected. The participants discussed these challenges and the causal relationship between data-driven operations and social outcomes.

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AI in Action: A Practical Guide to Using Agents for Integrating Custom Knowledge With Large Language Models

The third workshop provided a practical guide about Agents for integrating custom knowledge with LLMs, organized by D ONE (Heiko Kromer and Philipp Warmer).

This workshop explored Retrieval Augmented Generation (RAG) in Large Language Models (LLMs), focusing on the integration of custom knowledge bases and the use of agents in the generation process.

Attendees learnt about the two main components of RAG: retrieval and generation. The workshop explained the role of agents, which are managed by an orchestrator that delegates tasks and condenses results into valuable answers for the user. 

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AI Standards: Navigating Compliance and Regulations for Responsible AI

The 4th workshop dealt with Compliance and Regulations for Responsible AI, one of the focus topics of the IB Databooster. This workshop was organized by ZHAW (Christoph Heitz and Ricardo Chavarriaga).

AI-related standards are a key element to comply with upcoming regulation of AI. This workshop provided an overview of the regulation process and important standards for AI innovation, and provided practical exercises on how to apply them in practice. More than 30 participants discussed this topics in detail.

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Predictive Maintenance & Time Series Anomaly Detection With Darts

The fifth workshop discussed the time Series Anomaly Detection With Darts, organized by Unit8 (Dennis Bader, Antoine Madrona, Aron Horvath and Samuele Piazzetta)

The hands-on workshop on predictive maintenance and anomaly detection using Darts more than 60 participants learnt how to use time series data to predict equipment failures and detect anomalies. To understand this topic better the moderators presented two real-world use cases from the healthcare and industrial sectors. 

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Data Science in Spatial Computing – Explore Your Data Using PlotAR

The sixth workshop addressed data science in spatial computing, also one of the focus topics in the Databooster. The workshop was organized by D ONE (Philipp Thomann, Shiva Farghar, Charlotte Cabane, Moritz Haag and Lucas Brunner)

The participants had an immersive experience: walking through the data, grasping it with their own hands. They made hands-on exercises the basics of PlotAR and explored it in more detail.

The day was concluded with a networking apero and the presentation of the Swiss Viz Awards.

By Reik Leiterer, Booster Manager

In open innovation, creating a safe space to share knowledge and ideas is vital for successful co-creation. This entails establishing a legal framework for open innovation by creating policies and guidelines that foster collaboration, protect intellectual property (IP) rights, ensure fair use, and maintain compliance with relevant laws. The following video explains how to enable a trust-building setting with rules of participation for an open innovation program and for collaborating teams.

How to set a legal framework for open innovation? (Video)

In the frame of Intellectual Property Management, create and/or follow guidelines on the ownership and sharing of IP created through open innovation, including e.g. joint ownership, licensing agreements, or IP transfer policies. Create understanding on how patents and trademarks will be handled, including the set-up of agreements on filing and maintaining IP protection. If necessary, use non-disclosure agreements (NDAs) to protect sensitive information shared during collaboration.

With regard to compliance with laws and regulations, be aware of data protection laws (e.g., GDPR, CCPA) when handling personal or sensitive data, comply with export control regulations that may affect the sharing of technology or information across borders, and avoid anti-competitive practices by ensuring that collaboration does not lead to market monopolization or unfair trade practices. May be consider using Creative Commons and open source licenses  (e.g., MIT, GPL) to facilitate and ensure legal sharing, contribution and reuse of creative works. 

We always recommend establishing ethical guidelines to ensure that innovations are developed and used responsibly. In addition, the incorporation of sustainability criteria into the innovation process could be something to think about to promote environmentally and socially responsible practices.