Hi Francesco! In June, Aidia turns three years old: it has been three years full of changes. During this period, Aidia has grown a lot, in spaces, in projects, but especially in the team, which now consists of over 20 people. What do you think about this growth, the results achieved?

I am incredibly grateful for where we have arrived. In part, I admit, I was confident that we would make it. I knew, for example, that people are essential for a tech company: it is their skills and technical knowledge that allow the company to expand and carry out increasingly challenging projects. So yes, I hoped that sooner or later we would reach 20. But I couldn’t imagine that we would get there so quickly, in just three years! I mean, I still remember our first office: it was me, Riccardo, and Luca in a small room where not even three desks could fit, and it seems like only a few months have passed.

From the project side, what has given you the most satisfaction?

Personally, besides the general satisfaction of seeing Aidia grow, I am very happy to see how we put theoretical notions into practice that would otherwise remain confined to the academic field. Being able to materialize the most cutting-edge ideas, especially in the field of Artificial Intelligence – making them useful, functional, in improving something concrete – yes, I think this is the greatest satisfaction.

Within Aidia, you are the COO, that is, you are in charge of operations. Can you explain a bit about what you specifically do?

The official term is Chief Operating Officer, but in daily life, I am a hybrid figure, straddling business management and technical project coordination. On one hand, I deal with company technology – I keep myself updated on the latest news (from research but not only) and try to keep up with the latest progress, to ensure that our solutions are the best on the market. On the other hand, I cultivate relationships with clients, listen to their requests, and manage resources, coordinate development teams, to meet their needs.

In short, you follow the development of projects closely: can you tell us what your modus operandi is? How does the development process work?

For any type of solution, first of all, we start with a feasibility study: to understand the client’s needs, the work environment, and whether it is necessary to create integrations with existing software or tools. Following the initial study, we design the architecture and start development, which proceeds in constant listening to the client – if possible, in direct contact with the company’s IT department. We develop tailor-made solutions, proprietary and customized software, and for this, it is essential to maintain continuous dialogue with the client.

At Aidia, but also in your academic career, you have dealt with Machine Learning and AI in various forms. What do you like about this technology?

The passion for this specific branch of computer science, I believe, comes from a generalized passion for innovation, for technology – and the desire to find new answers to problems. Machine Learning combines these two aspects: on one hand, it is a new field, totally to be explored, very challenging, constantly evolving; on the other hand, it encompasses great potential, the possibility of achieving useful results for people’s work.

In your experience, you have long dealt with Natural Language Processing, what do you think of the latest developments in the field?

The development of so many high-quality language-oriented models can only be positive. It has been a rapid evolution, which has seen the quality of generated outputs increase drastically, in just 2-3 years – this renewed capacity for analysis and automation opens up many interesting scenarios for businesses. I think even just about administrative management, analysis processes, or after-sales services: having this type of generative AI, which can handle customer requests, generate reports, or classify documents, will allow many repetitive tasks to be automated. On the other hand, I believe that the current hype is generating some confusion: some of the most talked-about functions are far from being a reality, while other capabilities are being exaggerated beyond their objective usefulness. We are at the peak of attention on the topic, and distorted information about the actual potential is spreading.

From a business perspective, what are the biggest challenges in the sector, in your opinion?

As I said before, probably the most complicated thing at the moment is conveying the right message to clients: some do not grasp the full potential of AI, while others tend to overestimate the most celebrated and well-known abilities. AI works very well for analysis, for example, or to simplify some steps of a process, but it cannot completely replace a person or disregard the business idea of the company itself.

What advice would you give to a company that wants to adopt a new Artificial Intelligence solution?

I think it depends a lot on what type of company we are talking about. Medium to large companies, in fact, can embark on larger industrial projects and seriously impact overall productivity – drastically increase productivity, reduce costs, optimize resource use. With a lot of data available and more resources, they can invest in complex developments; they can obtain proprietary tools that make company efficiency very simple. Smaller companies, on the other hand, often do not have the datasets or resources for such massive developments – but they can still gain several advantages from the technology: integrate preconfigured models and update their company technology with existing tools. So I would suggest seeing AI as a flexible technology, which can adapt to different needs and objectives – you just need to know well the bottlenecks of your company: among these, there is certainly some process or connection that could be made more efficient thanks to AI!