FFplus Interview with Salvatore Palange, AI Senior Lead at BitBang
In this FFplus interview, we spoke with Salvatore Palange, AI Senior Lead at BitBang, an Italian innovation-driven consultancy company, specializing in data analytics and AI.
We explored the most transformative trends currently reshaping production and supply chain industries and examined the growing role of AI—particularly generative AI—in driving this change. We also discussed BitBang innovative business experiment titled GenAI4Add, developed within the FFplus project.
Salvatore Palange, AI Senior Lead at BitBang
Copyrights: BitBang
Salvatore Palange is Senior AI Lead at BitBang, with over 10 years of entrepreneurial experience in the AI field. Combining deep expertise in artificial intelligence, IT, and business management, he has led innovative projects in Deep Learning, Generative AI, and Agentic AI, and previously served as a Senior Researcher at CNR. He holds an Executive MBA from Bologna Business School and is also the founder of AI Intelligenza Artificiale Italia, one of the largest Italian community dedicated to AI.
To start, could you briefly introduce BitBang?
SALVATORE:
Bitbang is an independent data consulting firm with over 20 years of experience, dedicated to empowering clients to become insights-driven by transforming marketing, customer, and production data into actionable strategies. Through cutting-edge partnerships and modern data architectures, we deliver tailored solutions that accelerate business growth using analysis, insights, and artificial intelligence.
From your perspective, what are the most transformative trends currently reshaping industry sectors through digital transformation—particularly in production and supply chains? Which innovations or shifts do you see having the greatest long-term impact?
SALVATORE:
Certainly, Robotic Process Automation (RPA), robotics, and the ongoing AI revolution are among the most transformative forces reshaping production and supply chains. Additionally, the rise of Natural Language interfaces as a standard for human-machine interaction holds the potential to unlock entirely new forms of innovation that we can’t yet fully envision.
BitBang is a data consulting company specialising in digital transformation and customer-centricity. How are you integrating AI into your workflows for data analytics or custom-built predictive models?
SALVATORE:
At BitBang, we place the client’s goals at the center of every solution we design, tailoring data pipelines and technologies to deliver measurable impact. AI plays a pivotal role in this process—it enables us to build predictive models and analytics workflows that were either impossible or prohibitively complex just a few years ago, unlocking new levels of efficiency, personalization, and strategic foresight.
Let's now talk about your experience with the participation in the FFplus sub-project. Could you briefly introduce your use case – what challenges does it address and what innovative solution you have been developing?
SALVATORE:
Our project, GenAI4Add, is a bold and forward-looking initiative aimed at establishing a foundational model for time sensor prediction in additive manufacturing, using cutting-edge Generative AI techniques. By leveraging High-Performance Computing (HPC), we’re building the backbone of a specialized model that interprets 3D printing sensor data and outputs—addressing complex challenges and pushing the boundaries of what’s currently possible in industrial AI applications.
What key business outcomes do you expect the solution to deliver once the sub-project is completed? How do you see it impacting your operations, competitiveness, or market opportunities?
SALVATORE:
Through GenAI4Add, we’re gaining deep expertise in the manufacturing sector, particularly in 3D printing processes—learning how data flows through the pipeline, identifying constraints, and tackling the unique challenges of this domain. Our ultimate goal is to develop a SaaS solution that enables companies to better monitor and forecast their printing operations, positioning BitBang as a leading player in industrial AI and opening up new market opportunities in advanced manufacturing.
The sub-project has been running for a few months now. As the sole partner working on this case, have you encountered any specific challenges—and how have you approached solving them?
SALVATORE:
Yes, we’ve faced several challenges, particularly during the initial data collection phase. Since additive manufacturing is a highly specialized domain and we started with limited expertise, we had to rely solely on data provided by our partners, which led to issues like data scarcity and misalignment. These constraints forced us to rethink some of our initial approaches. On the positive side, access to High-Performance Computing (HPC) has allowed us to experiment with state-of-the-art AI models—such as generative time series forecasting and diffusion models—giving us valuable insights and accelerating our learning curve in this complex field.
As a newcomer to HPC, could you share some insights from your experience so far? What HPC infrastructure have you been using during the experiment, and what key takeaways or lessons have you gained along the way?
SALVATORE:
We’ve been working with the Leonardo supercomputing infrastructure by Cineca, and we were genuinely impressed by its computational power and surprisingly user-friendly interface. One key takeaway has been adapting our development practices: while the system is incredibly fast and efficient for running complex algorithms, the lack of interactive debugging required us to rethink and streamline our coding habits, which has ultimately strengthened our approach to working in high-performance environments.
Let’s wrap up the interview with some final thoughts. What advice would you give to other SMEs that haven’t yet explored the use of HPC and AI in their business?
SALVATORE:
I would strongly encourage other SMEs to explore HPC and AI, these technologies open the door to experimenting with bold, visionary ideas that traditional infrastructures simply can't support. Now is the perfect time to innovate fearlessly and embrace the transformative potential of high-performance computing.