Needs to capture Samsung”s investment in Euclyd and the goal of challenging Nvidia.
Round led by Samsung, along with Somerset Capital Partners, Scaleup Europe Fund (managed by EQT), and Innovation Industries.
Euclyd develops AI chips with a non-GPU architecture focused on AI inference.
The goal is to reduce power, memory, and cost requirements for data centers.
Nvidia currently dominates the AI chip market with GPUs, but big tech (OpenAI, Google, AWS, Meta) and startups are developing alternatives.
Euclyd's chips (like Jalapeño by OpenAI mentioned in August) aim for high speed and efficiency.
Samsung brings more than capital: memory manufacturing, engineering expertise, supply chain, and a global network.
Euclyd partners with ADTechnology (Korean) using Samsung Foundry.
Euclyd's business model: selling physical hardware/rack systems for internal AI inference, and licensing IP to companies building their own chips.
Formatting:
Title: Samsung Backs Dutch AI Chip Startup Euclyd in €200M Funding Round to Challenge Nvidia
Keywords: Samsung, Euclyd, AI Chips, Artificial Intelligence, Nvidia, AI Inference, Data Centers, Semiconductor Supply Chain, Series Funding.
Overview
Samsung has backed the Dutch technology startup Euclyd in a €200 million (approximately $230 million) funding round as investments surge into developing alternatives to Nvidia’s dominant artificial intelligence processors. The round was co-led by Samsung alongside Somerset Capital Partners, the EQT-managed Scaleup Europe Fund, and Innovation Industries, with participation from several other investors. The capital will accelerate the development of Euclyd's specialized AI infrastructure.
Non-GPU Architecture for AI Inference
Founded in 2024, Euclyd is developing an AI chip system based on an architecture distinct from traditional Graphics Processing Units (GPUs). The technology is specifically designed for AI inference—the process of running pre-trained models to execute user tasks.
By integrating the processor and memory architecture, Euclyd aims to address critical bottlenecks in modern data centers: escalating power consumption, memory requirements, and infrastructure costs associated with deploying AI models at scale.
The Competitive Landscape and Samsung's Strategic Role
Euclyd enters a market heavily dominated by Nvidia, whose GPUs have become the industry standard for AI training and inference. However, rising computational demand has prompted major tech players (including OpenAI, Google, AWS, and Meta) and emerging startups to develop proprietary silicon to reduce reliance on a single supplier. Euclyd’s business model targets this growing demand through two main avenues: selling physical hardware systems for secure, in-house AI inference, and licensing its intellectual property to companies developing their own custom chips.
Euclyd CEO Bernardo Kastrup highlighted that Samsung brings strategic value far beyond capital. As a global leader in memory manufacturing, Samsung provides extensive engineering expertise, deep knowledge of semiconductor supply chains, and a global network to help the startup scale from development to mass production. This investment builds upon Euclyd's existing technical collaboration with Korean firm ADTechnology to develop data center chip solutions utilizing Samsung Foundry's advanced manufacturing processes.Title: Samsung Backs Dutch AI Chip Startup Euclyd in €200M Funding Round to Challenge Nvidia
Keywords: Samsung, Euclyd, AI Chips, Artificial Intelligence, Nvidia, AI Inference, Semiconductor Industry, Data Centers, Hardware Investment.
Overview
Samsung has backed the Dutch technology startup Euclyd in a €200 million (approximately $230 million) funding round as capital continues to flow into developing alternatives to Nvidia’s dominant artificial intelligence processors. The round was co-led by Samsung alongside Somerset Capital Partners, the EQT-managed Scaleup Europe Fund, and Innovation Industries, with participation from several other investors. Euclyd stated the new capital will accelerate the development of its specialized AI infrastructure.
Non-GPU Architecture for AI Inference
Founded in 2024, Euclyd is developing an AI chip ecosystem based on an architecture distinct from traditional Graphics Processing Units (GPUs). The technology is specifically optimized for AI inference—the process of running pre-trained models to execute tasks for end-users.
By closely integrating the processor with the memory architecture, Euclyd aims to resolve critical bottlenecks facing modern data centers: escalating power consumption, massive memory requirements, and prohibitive infrastructure costs associated with scaling AI workloads.
Strategic Alignment and the Competitive Landscape
Euclyd is entering a market heavily dominated by Nvidia, but one where major tech entities—including OpenAI, Google, AWS, and Meta—are increasingly seeking proprietary silicon solutions to reduce hardware dependency. Euclyd's dual-track business model targets this shifting landscape by selling physical hardware rack systems for secure, on-premise AI inference, and by licensing its intellectual property to companies developing their own custom chips.
Euclyd CEO Bernardo Kastrup highlighted that Samsung brings strategic value extending far beyond financial capital. As a global leader in memory manufacturing, Samsung provides deep engineering expertise, supply chain leverage, and a global network crucial for moving from prototype to mass production. The investment builds upon an existing technical collaboration between Euclyd and Korean design house ADTechnology to develop data center solutions utilizing Samsung Foundry's advanced manufacturing processes.