AI infrastructure firm Infinity announced on Monday that it has successfully raised $15 million at a valuation of $100 million, attracting investment from firms such as Touring Capital, Principal VC, and experts from renowned companies like OpenAI and Anthropic.
Infinity is focused on developing software that simplifies the implementation of AI models on AI chips. The dominance of Nvidia in the market is attributable not only to its powerful chips but also to its CUDA software (Compute Unified Device Architecture), enabling its GPUs—initially designed for graphics processing—to operate as general-purpose CPUs. Popular AI development frameworks like PyTorch and TensorFlow are built on CUDA, which allows developers to create applications using widely-used programming languages such as Python, resulting in seamless operation on Nvidia hardware.
Many startups in the application space lack the expertise or resources to create their own kernels, the fundamental software that drives hardware, or to adapt their applications for various AI chips. Infinity aims to create an alternative kernel software compatible with a diverse range of chips, including SRAM, GPUs, mobile processors, and Systolic Arrays. This initiative is part of a broader trend where startups are systematically challenging Nvidia's market supremacy.
Infinity is working towards a universal inference library capable of functioning across different chip brands, enabling these chips to automate the replication of cutting-edge research results.
Founded last year by Jeremy Nixon, a former researcher at Google Brain and the creator of the AGI House hacker network community, Infinity emerged from Nixon's fascination with the concept of “automated invention.” He envisions AI systems as a transformative meta-technology. Nixon developed a machine learning algorithm named Omega, which autonomously generated and evaluated new algorithms within a feedback loop.
Inspired by this success, he explored applications in hardware, believing that automated systems could similarly produce the fundamental code necessary for enhanced chip performance.
Infinity’s AI research agent, Ignition, is designed to create the low-level code essential for AI inference on alternative chips to Nvidia. It autonomously tests, debugs, and assesses the hardware's performance with the generated code, adjusting it as needed to optimize speed. This self-optimizing system continuously learns and adapts to different chip architectures, regardless of proprietary constraints, according to Nixon. Infinity claims it has developed a software stack comparable to CUDA.
Infinity's client roster includes D-Matrix, an AI chip manufacturer positioned as a competitor to Nvidia, and Nixon mentioned ongoing discussions with other major chip and cloud providers.
While the agent handles the more labor-intensive tasks, human oversight remains essential for providing strategic direction. In one instance, the startup noted that the agent significantly outperformed human efforts, condensing a potentially years-long project into just hours or days. Infinity doesn't impose an upfront licensing fee; instead, it earns a portion of the performance improvements and cost savings, based on changes measured in tokens per second.
Currently, Infinity employs 26 staff members across design, operations, and engineering roles.
