Samsung has co-led a $230 million Series A funding round for Dutch AI chip startup Euclyd, signaling a significant bet on alternatives to Nvidia's dominant AI hardware. The investment underscores the growing demand for specialized, cost-effective AI inference solutions.
TL;DR
- Samsung co-leads a $230M Series A round for Euclyd, a Dutch AI chip startup focusing on inference hardware.
- Euclyd aims to reduce the cost and energy consumption of AI inference with its craftwerk architecture.
- The investment highlights the increasing competition in the AI chip market, with specialized hardware emerging as a viable alternative to Nvidia's GPUs.
What happened
Samsung, alongside Somerset Capital Partners, the Scaleup Europe Fund managed by EQT, and Innovation Industries, co-led a $230 million Series A funding round for Euclyd. Other participants include Denmark's EIFO, imec.xpand, Brabant Development Agency, and Quadri. The funding will support Euclyd's engineering team, silicon development, systems roadmap, and preparations for commercial deployment, according to the company's official announcement.
Euclyd is focused on AI inference, the stage where trained AI models process requests and generate outputs. The company's craftwerk architecture aims to reduce data movement between memory and processors, potentially lowering energy consumption and costs. Euclyd claims its platform combines programmable ASIC computing, processor-memory co-design, and system-level optimization.
Samsung's involvement is particularly notable due to its expertise in memory and semiconductor manufacturing. Euclyd's CEO, Bernardo Kastrup, highlighted that Samsung could contribute engineering knowledge, systems expertise, supply-chain experience, and its industry network, not just financing. Samsung has been expanding its position in AI memory and semiconductor infrastructure, making this investment strategically significant.
Why it matters
This investment signals a growing trend of specialized AI hardware emerging as a viable alternative to Nvidia's GPUs. Companies like OpenAI, Etched, and Amazon are also developing custom AI chips for specific workloads, aiming to deliver better performance at lower costs and power consumption.
For AI/ML developers and startup founders, the rise of specialized inference hardware could lead to more affordable and efficient AI infrastructure. This could democratize access to AI, enabling a broader range of companies to deploy private AI systems.
For tech investors, the competition in the AI chip market presents new opportunities. While Nvidia remains a dominant player, the success of startups like Euclyd could reshape the AI hardware landscape, making it a sector worth watching.
Key facts
- Euclyd raised more than €200 million, roughly $230 million, in its Series A round.
- Samsung co-led the funding round alongside Somerset Capital Partners, the Scaleup Europe Fund, and Innovation Industries.
- Euclyd's craftwerk architecture aims to reduce data movement between memory and processors, potentially lowering energy consumption and costs.
- Euclyd expects to begin rolling out physical chip systems in 2028, with an ambition to serve thousands of enterprise customers by 2030.
- Samsung's first test chip for Euclyd was manufactured at Samsung and will be used to validate the startup's compute architecture, according to EQT.
- Euclyd plans to sell physical systems for enterprises and license its technology to other chip developers.
Context
The AI chip market is evolving rapidly, with a growing focus on specialized hardware for specific workloads. While Nvidia's GPUs have been the go-to choice for AI training and inference, the high costs and power consumption have spurred interest in alternatives.
The rise of foundation models and the increasing demand for AI services have highlighted the need for more efficient and cost-effective inference solutions. Startups like Euclyd are betting that specialized hardware can deliver better performance for specific tasks, making AI more accessible and affordable.
As the AI hardware landscape continues to evolve, the competition between Nvidia and specialized startups like Euclyd will be a key story to watch. The success of these startups could lead to a more diverse and innovative AI ecosystem, benefiting developers, startups, and investors alike.
