If you’ve been with us for a while, you probably remember Una Spremuta dal Web. That version of the newsletter took a pause to reflect a deeper transformation: the evolution from SED Web to Babini Mazzari.

Above trends, beyond insights is not just a rebrand. It’s a shift in perspective: less noise, more signal.

We’ll also show up more often - not monthly, but when it matters.

Europe’s gigafactory gamble

In a bold move to secure technological sovereignty and compete with AI powerhouses in the U.S. and China, the European Commission has unveiled its InvestAI initiative, committing €20 billion to build up to five AI gigafactories across the continent by the end of 2025.

These facilities—each expected to house over 100,000 high-performance processors—will serve as pan-European hubs for developing “very large” AI models, underpinning applications in healthcare, robotics, and scientific discovery while reinforcing Europe’s strict data privacy and safety standards (InvestAI press release; Reuters).

From a business perspective, this massive public-private partnership aims to level the playing field for European AI startups and research institutions that today struggle to access cutting-edge compute; by offering shared infrastructure and subsidized access, Brussels hopes to spur homegrown innovation and attract private investments in semiconductors and cloud services.

Governance implications are equally significant: while the AI Act (fully in force by 2027) already imposes tight rules on high-risk AI systems, the gigafactory rollout will compel regulators to balance environmental and energy considerations—each facility could consume hundreds of megawatts of power—against Europe’s net-zero targets and the need for water-efficient cooling (The Guardian).

While skeptics warn of rapid obsolescence in a field defined by Moore’s Law and of the challenge of securing enough chips, proponents argue that stitch-together networks of mid-sized data labs and shared R&D clusters can create an “AI CERN” effect—pooling talent, data, and resources to drive breakthroughs that single nations or companies might struggle to achieve alone.

Looking ahead, corporate leaders should prepare for a new wave of European AI consortia, seek early partnerships for co-funded research, and monitor how member states integrate national champions—such as deep-tech startups in France, Germany, and the Nordics—into this pan-EU infrastructure.

Establishing clear governance frameworks around energy sourcing (favoring green hydrogen or renewables) and chip procurement (prioritizing domestic fabs) will be critical to ensuring that InvestAI translates into sustainable competitive advantage rather than stranded assets.

TREND TRACKER

Small models, big impact

As the AI landscape matures, “edge AI” powered by Small Language Models (SLMs) is emerging as a transformative trend that promises lower latency, enhanced privacy, and reduced operating costs.

SLMs can run locally on embedded devices, such as smartphones, industrial sensors, or automotive controllers, enabling real-time language understanding, anomaly detection, and predictive maintenance without constant connectivity to the cloud.

This shift is driven by three converging factors: breakthroughs in model compression and quantization have reduced many NLP and computer-vision models to under 500 MB; regulatory pressures, particularly in healthcare and finance, mandate that sensitive data remain within corporate firewalls; and investments in energy-efficient silicon (e.g., RISC-V-based AI accelerators) are lowering the cost of running these models at the edge.

For European enterprises, adopting SLMs enables tighter control over data sovereignty while unlocking new customer-facing use cases - think real-time translation kiosks at airports or intelligent diagnostics tools in remote clinics. Moreover, by offloading inference from centralized servers, companies can slash cloud spend and carbon footprint: early adopters in manufacturing report up to a 40 percent reduction in operational latency and a 30 percent drop in energy consumption per inference compared to cloud-based pipelines.

Want to learn more?

• Power of Small Language Models (IBM)

• The Rise of Small Language Models: Powering Real-Time Intelligence at the Edge (The Fast Mode)

• Could Small Language Models Be the Key to Unlocking AI Value in 2025? (TechFinitive)

QUICK INSIGHT

Green software engineering: how to

Optimizing software for energy efficiency is becoming a strategic imperative for cloud-driven businesses aiming to meet regulatory sustainability targets and control spiraling compute costs.

According to a May 2025 Tech Mahindra report, up to 20 percent of cloud carbon emissions can be recouped simply by refactoring code and architecture. Here’s how to get started:

1. Consolidate underutilized microservices. Identify low-traffic services via telemetry dashboards; merge or decommission them to reduce idle compute.

2. Implement efficient caching layers. Leverage distributed caches (e.g., Redis, Memcached) to cut down repeated API calls and disk I/O.

3. Adopt event-driven, serverless patterns. Transition batch-processing jobs to on-demand cloud functions (AWS Lambda, Azure Functions) to ensure compute runs only when needed.

4. Choose energy-optimized languages and frameworks. Favor languages such as Go or Rust for CPU-intensive components; benchmark runtime energy profiles before standardizing.

5. Embed energy metrics into CI/CD pipelines. Integrate tools that measure power draw (e.g., CodeCarbon) and enforce efficiency checks during pull requests, making “green” a team KPI.

6. Incorporate efficiency clauses in vendor contracts. Require SaaS and cloud providers to disclose their PUE (Power Usage Effectiveness) and carbon intensity, shifting workloads to greener regions when possible.

By systematically applying these practices, organizations can achieve a 15–25 percent reduction in cloud energy consumption within six months, bolstering both sustainability reporting and the bottom line.

WHO IS BABINI MAZZARI

Our Value Proposition

Babini Mazzari is the strategic IT partner for European companies looking to navigate digital transformation in a structured, pragmatic, and sustainable way.
We don’t just deliver technical solutions — we work as an extension of your internal team, helping you integrate systems, optimize processes, and lead change with clarity and competence.

Our approach is built on listening, transparency, and a strong results-driven culture. Whether you're scaling, modernizing, or rethinking your operating model, we support every client with the right tools, clear methodology, and long-term vision.
Above Technology. Beyond Solutions.

📎 [Our services]
📎 [Our Manifesto]