The generative AI boom is driving the demand for AI chips, which are purpose-built to train and run generative AI models. And major players, from VCs to startups, are scrambling to get in on the ground floor.
SoftBank’s Masayoshi Son is reportedly looking to raise $100 billion for a chip initiative that would compete with tech giant Nvidia. OpenAI, meanwhile, is said to be in talks with investment firms to launch an AI chip-making venture.
AI chip startup Axelera has kept a comparatively low profile. Nevertheless, it’s managed to win over backers including Samsung in part by focusing on a niche within the burgeoning AI chip market: chips that run AI on edge devices.
“There’s no denying that the AI industry has the potential to transform a multitude of sectors,” Fabrizio Del Maffeo, one of the co-founders of Axelera and its CEO, told TechCrunch in an interview. “However, to truly harness the value of AI, organizations need a solution that delivers high-performance and efficiency while balancing cost.”
Axelera — headquartered in the Netherlands, with a roughly 180-person workforce spread across offices in Belgium, Switzerland, Italy and the U.K. — designs AI-running chips and systems for applications like security, retail, automotive and robotics that it supplies to partners manufacturing B2B edge computing and internet of things products.
Axelera was borne out of an effort led by Del Maffeo and a group at Imec, the Belgium-based technology lab, along with Evangelos Eleftheriou and a group of Zurich-based IBM researchers to build a highly efficient AI chip architecture. The founding team incubated much of Axelera within Bitfury Group, a blockchain company specializing in Bitcoin hardware.
The defining characteristics of Axelera’s AI hardware stack are the instruction set architecture (ISA) RISC-V and in-memory computing.
Instruction Set Architectures (ISAs) are technical specifications that define how software interacts with a chip’s hardware. Typically, chip designers license an existing ISA from major chipmakers like Arm or Intel. However, RISC-V offers an open, royalty-free alternative. In-memory computing, on the other hand, involves performing calculations within a system’s RAM to minimize latency caused by storage devices.
Axelera is not the first to explore in-memory and RISC-V-based architectures for AI chips.
NeuroBlade is developing chips that integrate both compute and memory into a single hardware block for data processing. Companies like MemVerge, GigaSpaces, Hazelcast, and H2O.ai also provide in-memory hardware solutions for AI and data analytics. Additionally, Tenstorrent, supported by Hyundai Motor Group and Samsung, offers AI processors and related intellectual property based on RISC-V.
Axelera has distinguished itself by offering both chip hardware and software to manage and deploy AI models on that hardware. This strategy seems to be paying off.
On Thursday, Axelera announced the closure of a $68 million Series B funding round, bringing its total funding to $120 million. Investors included the European Innovation Council Fund, Innovation Industries Strategic Partnership Fund, Invest-NL, and Samsung Catalyst Fund.
According to Del Maffeo, the new funds will be used to expand into new markets ahead of the full production of Axelera’s flagship Metis AI platform in the second half of 2024. Axelera is also eyeing the data center chip market, with initial plans to fund R&D for chips targeting high-performance computing applications.
“Metis entered full production in Q2 and will be delivered in volume in Q3,” Del Maffeo said. “Axelera AI is now developing a new generation of products for computer vision, large language models, and large multimodal models. This new product family will be unveiled later this year and enter full production in 2025.”
The challenge will be scaling up the production of its AI chips and competing with numerous other players in the AI chip market. Many competitors have significant backing; a Crunchbase report from June indicates that VC-backed chip startups have raised nearly $5.3 billion in just 175 deals this year.
However, the potential rewards are substantial. According to Statista and Market.us, the AI chip market could generate up to $67 billion in revenue by 2027. While Axelera is unlikely to dethrone established vendors like Nvidia anytime soon (Nvidia holds an estimated 70% to 95% share of the AI chip market, according to Mizuho Securities), capturing even a small portion of the market would be a significant achievement.
“The funding supports our mission to democratize access to AI, from the edge to the cloud,” Del Maffeo said, noting that Axelera has “tens” of enterprise customers. “By expanding our product lines beyond the edge computing market, we can address industry challenges in AI inference and support current and future AI processing needs.”