Innova-tsn takes part again in the Smart Data Spain Summit

On Wednesday, April 3rd, Innova-tsn participated in the Smart Data Spain Summit 2024, which took place at Kinépolis in Madrid.

The Smart Data Spain Summitrebranded this year as #3SMadrid24, is a key professional gathering organized annually by IFAES. It brings together major companies from our sector to explore the latest and most innovative solutions in the field of data. The focus is on enhancing decision-making processes and identifying new business opportunities.

During this year’s event, more than 350 attendees and 30 speakers convened, emphasizing the practical application of analytics, with a special spotlight on generative artificial intelligence.

Additionally, for the first time, the 3rd edition of the Cybersecurity Expo Congress was held concurrently.

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“Taming the tech beast”

Innova-tsn had the opportunity to participate in the opening talk of the event with Dataiku. Our colleagues Carolina Martínez, Account Manager and Leyre Sánchez, Computational Linguist, shared space with Stephanie Griffiths, Field CDO de Dataiku and led an interesting discussion on the importance of taking the initiative, anticipating and governing responsible and ethical AI.

The key points that Stephanie Griffiths herself wanted to highlight from this talk are:

  1. Creating and Generating: The speakers emphasized that generative AI does not “create” in the strict sense of imagining something completely new; rather, it “generates” from existing knowledge. This implies that AI combines and restructures known ideas to form something that may appear novel but is rooted in pre-existing data. Particularly in image generation, this ability to combine existing elements is both astonishing and surprising.

  2. Impact on Work and Challenges of Generative AI: A debate ensued regarding the potential threat of generative AI to certain jobs, given its capacity to perform complex tasks such as writing code. However, it was observed that this technology learns from data available on the internet, which can be imperfect or suboptimal. Consequently, AI-generated responses are not always optimal, as they may perpetuate and amplify the limitations of the source data.

  3. Need for Governance and Data Quality: This engaging talk also underscored the importance of governance in AI management. Structuring input data and monitoring AI model results are critical aspects of ensuring effective outcomes.

  4. Fostering Curiosity: Finally, the three experts concluded their discussion by emphasizing the significance of cultivating curiosity and personal development within work teams. These qualities serve as essential channels for addressing the challenges posed by AI. In this context, valuing the unpredictable and leveraging imagination—an inherently human skill—remains beyond the reach of deep learning models.

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From left to right, Stephanie Griffiths, Carolina Martínez and Leyre Sánchez

“GENERATIVE AI: A revolution in the world of data”

On the other hand, after coffee break and networking, it was the turn of the Round Table that Innova-tsn, with the help of our Head of AI Strategy, Juan Ignacio Moreno, had the pleasure of moderating: “Generative AI: A revolution in the world of data”.

The participants who accompanied him, great experts in their different sectors, were: Luis Carlos Prieto, Head of AI Center of Excellence at Ferrovial, Jesús Oliva, Head of Data Science & IA at CEPSA, Noelia Álvarez, Big Data Specialist & Data Scientist at Grupo Santalucía, and Conrado Castillo Serna, General Manager at Rooter.

They all shared their valuable views with the attendees on how generative AI is transforming their respective fields, spanning from infrastructures and energy to insurance and education.

In summary, the key aspects discussed during this Round Table were:

  1. Impact and Necessity of AI: AI was not merely recognized as a competitive advantage; it was deemed a necessity. Companies that do not embrace these technologies risk falling behind. This sparks a debate on how AI adoption impacts businesses and what pitfalls should be avoided during its integration into corporate data strategies.

  2. Distinguishing Generative AI: The discussion delved into how generative AI reshapes business dynamics, sales, product and service development, and customer service. Understanding the differences between generative AI and predictive AI is crucial for organizations, as both models coexist within their operations.

  3. Applications of Generative AI: Each participant presented commercially valuable use cases for their customers. These included document classification, conversational chatbots for customer care services, article summaries, sentiment analysis, and customized content generation. These examples vividly illustrate the versatility and transformative potential of generative AI.

  4. Ethical and Responsible Development: All speakers unanimously emphasized the importance of ethics in AI. Transparency, ethical quality, equality, fairness, accountability, attribution, explainability, and sustainability are vital for the proper development of AI solutions. An ethical approach ensures trust and societal acceptance of AI technologies.

  5. Future Perspectives: Participants also shared their views on their companies’ future trajectories with the adoption and integration of AI into business processes. They highlighted the leverage of human expertise, the significance of machine learning (ML), and the personalization of services as key elements shaping the future.

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From left to right, Juan Ignacio Moreno, Luis Carlos Prieto,
Jesús Oliva, Noelia Álvarez and Conrado Castillo

Innova-tsn would like to express our gratitude to both the organizers and all the attendees who made this meeting possible. The enriching discussions centered around the latest trends and challenges in the field of generative Artificial Intelligence, serving as a catalyst for innovation.

Events like this not only promote knowledge and innovation within the sector but also foster collaboration and the exchange of ideas among professionals through networking spaces.