**The Importance of Time Series**

Time series lie at the heart of many critical real-world applications. Financial data, energy consumption, user behavior data, industrial measurements, and weather forecasts—all of these scenarios generate information structured over time. Time series, in essence, represent data sequences recorded at regular intervals, forming one of the most pervasive and valuable data formats in modern applications. Their analysis enables understanding phenomena, identifying recurring patterns, and making predictions—essential for strategic decision-making in numerous sectors.

For businesses, understanding how a system will evolve over time or how a specific variable will influence future behavior can mean the difference between success and failure. This is why developing models capable of managing and interpreting these dynamic data effectively is crucial. Here, the power of advanced AI models like Transformers comes into play.

**The Transformer Revolution**

Transformers are a special type of neural network designed for processing data sequences. They have emerged as one of the most groundbreaking innovations in artificial intelligence in recent years, particularly in natural language processing (NLP). First introduced in 2017, these models have revolutionized how AI handles NLP, giving rise to advanced systems such as large language models (LLMs)—including GPT, BERT, and many others.

The core idea behind Transformers is the "attention" mechanism, which allows the model to focus on different parts of an input flexibly and effectively. By simultaneously considering relationships across all positions in a sequence, Transformers have proven extremely powerful in capturing long-term dependencies in sequential data. This makes them particularly well-suited not only for text but also for time series analysis.

**Why Transformers for Time Series?**

Time series can be viewed as sequences of data that evolve over time, much like text is composed of a sequence of words. Traditionally, models like recurrent neural networks (RNNs) and Long Short-Term Memory networks (LSTMs) have been used to model time series due to their ability to maintain temporal memory. However, these approaches face limitations when dealing with particularly long sequences or complex dependencies.

Transformers, with their self-attention mechanism, overcome these limitations by providing a broader and more contextualized view of the data. With Transformers, every point in a time series can relate to every other point, without the need to process the sequence rigidly as in RNNs. This enables Transformers to automatically and quickly identify complex patterns, even across significant time spans.

**Embedding and Prediction: How Transformers Work for Time Series**

Applying Transformers to time series involves several key steps. First, the time series are represented through embeddings—dense numerical representations capturing the salient features of the sequences. These embeddings serve as inputs to the Transformer model, which, through its attention layers, identifies patterns, trends, and relationships within the data.

This highly informative representation can be utilized in classification or prediction layers, depending on the final objective. If the goal is to classify an event (e.g., detecting anomalies in industrial data), the embeddings are fed into a classification layer. If the aim is to predict future values (e.g., monthly sales forecasts), the embeddings are used in a prediction layer.

Thanks to these characteristics, Transformers can tackle a wide range of time series analysis problems, enhancing both the accuracy of predictions and the ability to interpret underlying phenomena. Additionally, Transformer-based architectures can integrate external information or diverse contexts, further boosting the models' effectiveness.

**Opportunities for Businesses**

Using Transformers for time series analysis marks a significant step forward compared to traditional methods. With the ability to capture complex patterns and long-term relationships, these models offer new possibilities for forecasting and classifying temporal data, making AI applications in business and industrial contexts more effective.

At Deix, we have experience applying this approach to financial data classification to detect potential fraud and to forecasting time series from IoT sensors to estimate the remaining useful life of industrial components. However, the potential applications are even broader.

In a data-driven world, fully understanding and leveraging the power of time series provides businesses with concrete tools to improve their competitiveness and decision-making capabilities. Transformers stand out as one of the most promising solutions to address these challenges innovatively and effectively.

Using Transformers for Time Series Analysis

On November 28, 2024, we had the honor of participating in Matcher On Stage, the concluding event of Matcher Data-Driven Innovation - 2024 Edition. Organized by Art-ER and the Enterprise Europe Network, this international open innovation program aims to foster strategic business meetings between top companies from the Emilia-Romagna Region and international startups or scaleups.

Our Jacopo Corno, Head of Business Solutions at Deix, was among the key speakers at the roundtable titled "Data Analysis as a Key to Strategic Decisions." The event featured prominent organizations such as Fondazione ITL, Chiesi, Gruppo CAMST, and Rekeep, which together discussed the crucial role of data analysis in transforming business decisions into strategic opportunities.

The panel explored real-world cases and innovative solutions showcasing how leveraging data can enhance companies' decision-making capabilities, boost their competitiveness, and promote future-oriented strategies.

Deix's participation in Matcher On Stage marks another step forward in our commitment to driving innovation through Mathematical Intelligence and collaboration with prominent partners.

Deix at Matcher 2024

We are pleased to announce that Deix Srl has secured funding through a cascading grant from the PNRR, under Spoke 2 "Integrative AI" of the FAIR (Future Artificial Intelligence Research) project. This initiative, coordinated by the Bruno Kessler Foundation, aims to foster the integration of heterogeneous techniques that leverage both data-driven and model-based approaches, developing theories and solutions capable of addressing the challenges of Artificial Intelligence. Integrating mathematical models with data-driven techniques represents the key challenge of this call, a vision that reflects Deix's distinctive approach to Mathematical Intelligence: a blend that combines the rigor of mathematical modeling with the flexibility and power of data-driven AI.

Deix's project, named INTEGRA (INtegrative AI Technologies for Ergonomic Guidance and Risk Assessment), aims to improve workplace safety by combining advanced Artificial Intelligence techniques with physical models of human motion. This synergy will enable the automation of ergonomic risk assessments, using standard scales such as REBA, RULA, and OWAS, leveraging data acquired through motion capture technologies and image-based pose estimation.

Collaboration with the Bruno Kessler Foundation, a leader in the "Integrative AI" Spoke of the FAIR partnership, will provide Deix with the opportunity to develop cutting-edge solutions, benefiting from the expertise and resources of a center of excellence in Artificial Intelligence.

INTEGRA is a natural evolution of our [Varda-AI](https://www.deix.ai/en/solutions/products/varda-ai) platform, already used to monitor behaviors and movements in industrial environments. The integration of new functionalities for real-time ergonomic evaluation will reduce workplace injuries and improve workers' health, while also offering solutions applicable to fields such as healthcare and sports.

This project strengthens Deix's commitment to combining Artificial Intelligence and mathematical modeling to develop innovative and sustainable solutions, contributing to the digital transformation of companies and promoting a culture of prevention and workplace safety.

Innovation in Ergonomics Powered by Artificial Intelligence

Deix Launches the INTEGRA Project

On October 29 and 30, Deix participated in SMAU Milan, a key event for innovation in Italy, hosted at FieraMilanoCity. With the support of the Lombardy Region, we were present with our booth alongside other local excellence, representing the best of Lombard innovation.

The experience at SMAU allowed us to meet with prominent corporations interested in our Mathematical Intelligence solutions and our expertise in AI and mathematical modeling. These meetings opened up collaboration opportunities with organizations that share our goal: accelerating companies' digital transformation in an ethical, sustainable, and transparent way.

Participating in the workshops dedicated to innovation and artificial intelligence was fundamental for us to engage with emerging trends and, above all, with the main pain points of companies. Among the critical challenges discussed, the adoption of AI tools within companies stood out: bringing innovation also means overcoming cultural and structural barriers to ensure the effective and advantageous implementation of advanced technologies.

We also had the opportunity to participate in two speed-pitching sessions, where we presented our solutions to an audience of industry experts and decision-makers.


The two days at SMAU were intense but extremely productive, thanks to the entire Deix team—Jacopo, Fabio, Rossella, and Francesca—and our partners at Ottozerouno, Luca and Marco, for the great work done!

Deix at SMAU Milan 2024

We are proud to announce that Deix has received the DigiSafeWell Award.

This recognition is an important affirmation of Deix's commitment to creating advanced technological solutions for workplace safety, well-being, and sustainability. Our platform, [Varda-AI](https://deix.ai/en/solutions/products/varda-ai), awarded for its ability to monitor production environments and reduce risks through Artificial Intelligence, is an example of how we aim to transform corporate safety into an operational advantage.

Thank you to FAST, Enterprise Europe Network - Confindustria Lombardia, and all the organizers for this opportunity. Congratulations as well to the other winners who are driving incredible innovations in their respective fields!

[Watch the video interview](https://www.youtube.com/watch?v=tzSS1GcDupg)

Deix Wins the DigiSafeWell Award

From October 21 to 23, we were in Catania at the prestigious Monastery of the Benedictines to participate in the Research Exchange Forum organized by the Emblema Foundation. An unmissable event that brings together companies, startups, investors, universities, and research centers with the goal of fostering innovation and collaboration among these players.

During our plenary pitch, we had the opportunity to present our unique vision of innovation, based on **Mathematical Intelligence**, and shared some of our latest research projects in the field of Large Language Models (LLM) and Generative AI, which aim to make these tools more accessible and interpretable. These projects reflect our commitment to the democratization of AI and the creation of models that are not mere "black boxes" but transparent and ethical systems.

Returning from this experience, we bring back a network of partners with whom we can work to continue pushing the boundaries of innovation and applied technology, as well as a wealth of insights and valuable feedback to refine our proposals in the industrial sector and digital transformation.

Deix at the Research Exchange 2024

On July 15th, we had the pleasure of hosting a plenary day with our scientific committee at Deix's headquarters in Milan. It was a special occasion, not only to meet in person but also to discuss key topics for the company's future.

Professors from Rome and Florence actively participated in the discussion, offering valuable insights on many fronts. We covered updates on our current projects and those involving new clients, highlighting the progress made and future milestones. Among the main topics was Deix’s new direction towards Mathematical Intelligence, which combines mathematical models and artificial intelligence to provide unique and differentiating solutions. This new positioning represents an important step in communicating our external identity and the values that make us unique.

In addition to this, we shared updates on business development, participation in public tenders, and the excellent results achieved in communication activities, particularly regarding the growth of our presence on LinkedIn over the past six months. We also had a constructive discussion about marketing activities, including the creation of promotional materials and participation in industry events such as AI Week in Rimini and We Make Future in Bologna.

Finally, we reflected together on the outcomes of the Deix Reflections event in May, a brainstorming day that allowed us to focus on how to further improve our internal processes.

Meeting in person was essential: moments like these allow us to align on future goals, strengthen team cohesion, and continue building Deix’s future with enthusiasm.

The future of Deix in our plenary meeting

Mathematical Intelligence and New Goals

Between June 24 and 28, the DFOS 24 (Derivative-Free Optimization Symposium 2024) conference was held in Padua, an event of international significance in the field of derivative-free optimization. The conference featured the participation of global experts who shared their latest research and innovations. Deix was a sponsor of the event, and Giampaolo Liuzzi, a founding partner of Deix and a member of our scientific committee, played a prominent role as a member of the organizing committee.

**The Importance of DFOS 24**

From June 26 to 28, Padua became the focal point for the academic and industrial communities interested in derivative-free optimization. Derivative-Free Optimization (DFO) comprises techniques for optimizing complex objective functions without the need to compute derivatives. This approach is extremely useful in many industrial applications where the objective function is difficult to model or where derivatives are hard or impossible to calculate. Examples include the optimization of manufacturing processes, the design of complex engineering systems, and the resolution of problems with noisy or incomplete data.

**Contributions from Deix and Giampaolo Liuzzi**

Giampaolo Liuzzi presented several cutting-edge research papers on derivative-free optimization methods, demonstrating how these can be applied in practical contexts. For instance, among the projects he is responsible for, the BIODRONES project is one of the most interesting. This project aims to develop autonomous underwater vehicles with biology-inspired shapes and functions, using advanced simulation and optimization algorithms for efficient design.

At Deix, the fusion of academic research and practical applications is the cornerstone of our success. Our mission is to provide innovative, tailor-made solutions to our clients, enhancing their market competitiveness. We are proud to sponsor and actively participate in events like DFOS 24, which allow us to stay abreast of the latest trends and innovations in our field.

Participating in DFOS 24 has allowed Deix to consolidate its position as a leader in mathematical optimization and to strengthen its network of academic and industrial collaborations. We will continue to work with passion and dedication to drive innovation and develop solutions that truly make a difference.

Articles and news