Cerebras $2.5B: Physical AI Enters the B2B Manufacturing Sector

The timeline: from a lone bet to a $1.525 billion exit

In 2015, Lior Susan founded Eclipse Ventures with a contrarian premise. While American venture capital chased SaaS and digital marketplaces, Susan was betting on the physical world. Robotics, semiconductors, industrial automation: sectors considered slow, capital-intensive, unglamorous.

Cerebras Systems was one of those investments. The company developed unusually large AI chips — the Wafer-Scale Engine — designed to accelerate the training and inference of large models. Furthermore, its positioning was explicitly an alternative to Nvidia: fewer commodity GPUs, more specialized architecture for intensive AI workloads.

In May 2026, TechCrunch reported that Eclipse considers this exit only the beginning. The thesis on the physical world is not exhausted—on the contrary, it is proving more relevant than ever.

Betting Architecture: Why Silicon Matters More Than Software

Cerebras has built a real competitive advantage. Its chip integrates billions of transistors on a single wafer, eliminating communication latency between separate chips. Therefore, for applications requiring fast inference—inline quality control, predictive maintenance, computer vision—this approach offers measurable benefits.

The distinction from traditional cloud AI is relevant. Models hosted on remote infrastructure introduce latency, connectivity dependence, and data sovereignty issues. In contrast, an on-premise or edge architecture allows for local processing, which is fundamental in industrial contexts where production data is sensitive.

So, Cerebras's value isn't just financial. It represents the maturation of an entire category: specialized AI hardware for physical applications. According to Gartner, By 2027, more than 40% of enterprise AI workloads will be run in edge or on-premises environments. The Cerebras deal is a step toward this trend.

Winners and losers: who really profits from this scenario

The most obvious winner is Eclipse Ventures. The firm has proven that investing in the physical world is not a romantic niche, but a thesis with concrete returns. Furthermore, the credibility gained will attract capital to other portfolio companies in AI hardware and robotics.

Cerebras itself is solidifying its position as a credible alternative to Nvidia. However, the road ahead remains challenging: Nvidia controls over 70% of the AI GPU market, according to industry estimates. Cerebras’ specialization is an advantage in specific segments, not a broad market conquest.

The ones at risk of losing ground are the SMEs that postpone decisions on AI infrastructure. In fact, while big industrial players—automotive, aerospace, and pharmaceuticals—are already evaluating on-premise AI architectures, medium-sized companies risk finding themselves at a structural disadvantage. Consequently, the competitive gap could widen in the next 18-24 months.

A Milanese agency's perspective: what we see in the Italian market

We of SHM Studio we work daily with Italian SMEs in the B2B and retail sectors. We observe a clear trend: the demand for AI solutions it is growing, but it often clashes with a still superficial understanding of the necessary infrastructure.

Many companies associate AI exclusively with cloud tools—ChatGPT, Copilot, SaaS platforms. However, for those operating in manufacturing, logistics, or supply chains, the real opportunity lies in AI applied to physical processes. This requires a focus on hardware, not just software.

The Cerebras-Eclipse deal is a market signal that Italian SMEs should also pay attention to. Therefore, those who are responsible for digital marketing And digital transformation cannot ignore the infrastructural dimension of AI. The two things — digital communication and technological infrastructure — are increasingly interconnected.

Operational Implications for Italian Manufacturing SMEs

What does this scenario concretely mean for an Italian manufacturing company with 50-500 employees? First of all, it is useful to distinguish between three levels of AI maturity.

• Beginner level Using cloud AI tools for marketing activities, copywriting, data analysis. Accessible today, with limited investment.
• Intermediate level: Integration of AI models into specific business processes — predictive CRM, customer segmentation, campaign optimization Google Ads e LinkedIn. Requires structured digital skills.
• Advanced level: On-premise AI for quality control, predictive maintenance, and machine vision. Requires hardware investment and specific expertise.

Furthermore, it is important to assess your current position before jumping to advanced solutions. A company that has not yet optimized its SEO positioning or their digital presence isn't ready for on-premise AI. Sequence matters.

For this reason, our approach in SHM Studio It always starts with an assessment of overall digital maturity. Only then can you identify where AI generates real value, and where it risks being a premature investment.

The Construction Site Still Open: Where the Game Will Be Played in the Next 24 Months

Eclipse Ventures' thesis doesn't end with Cerebras. According to founder Susan, the portfolio includes dozens of companies operating at the intersection of AI and the physical world. Therefore, in the coming years, we will likely see other significant exits in robotics, energy tech, and industrial automation.

At a macro level, McKinsey estimates that generative and applied AI could add up to $4.4 trillion annually to the global economy. A significant portion of this value will come from industrial and physical applications, not just digital ones.

In Italy, the context is specific. The production fabric is mainly composed of manufacturing SMEs with strong sectoral specialization. Therefore, the adoption of physical AI—even in less sophisticated forms than Cerebras chips—represents a real competitive opportunity. Particularly for those who export and compete in international markets.

Likewise, those who are responsible for web development Digital presence must start considering how on-premise AI will change data flows and integrations between physical systems and digital platforms. The line between IT and OT (Operational Technology) is rapidly blurring.

Next moves: three priorities for those who want to get ahead

Based on what has been analyzed, it's possible to identify three priority areas of action for Italian SMEs that want to prepare for this scenario.

First priority: digital maturity audit. Before evaluating any AI investment, you need a clear view of the current state. This includes SEO, web infrastructure, internal data quality, and analytical capabilities. Without this foundation, any AI investment risks being ineffective.

Second priority: internal training on applied AI. This isn't about becoming experts in chips or hardware architectures. It's about understanding which business processes can benefit from AI, and what skills are needed to evaluate vendors. Furthermore, training reduces the risk of decisions based on hype rather than analysis.

Third priority: technology partner selection. The B2B AI market is crowded with solutions. Choosing partners with vertical experience in your industry is crucial. Finally, it's useful to evaluate whether the proposed solutions are scalable—meaning they can grow with the company without requiring costly migrations.

To delve deeper into these topics or to start an assessment of your digital footprint, you can Contact the SHM Studio team to explore the contents of the our blog.