Despite the growing trend towards smaller seed rounds, the era of large seed rounds is far from over in the AI sector. In fact, a recent development highlights the continued interest in this space. CentML, a startup developing tools to decrease the cost and improve performance of deploying machine learning models, has announced that it raised $27 million in an extended seed round with participation from Gradient Ventures, TR Ventures, Nvidia, and Microsoft Azure AI VP Misha Bilenko.
A Brief History of CentML
CentML initially closed its seed round in 2022, but the company decided to extend the round over the last few months due to growing interest in its product. This decision brought the total amount raised by CentML to $30.5 million. The fresh capital will be used to bolster CentML’s product development and research efforts, as well as expand the startup’s engineering team and broader workforce of 30 people spread across the U.S. and Canada.
The Vision Behind CentML
CentML co-founder and CEO Gennady Pekhimenko, an associate professor at the University of Toronto, shared a vision with his co-founders Akbar Nurlybayev, Shang Wang, and Anand Jayarajan to create technology that could increase access to compute in the face of the worsening AI chip supply problem. Pekhimenko emphasized that machine learning costs, talent, and chip shortages are common challenges faced by many companies.
The Challenge of the AI Chip Shortage
Pekhimenko noted that the highest-end chips are often unavailable due to large demand from enterprises and startups alike. This leads companies to sacrifice on model size or result in higher inference latencies for deployed models. GPUs, which are heavily used in both training and inference, are no exception.
The Solution: CentML’s Software Platform
CentML’s software platform aims to address these challenges by optimizing the deployment of machine learning models. The company produces optimized code for a variety of GPUs, reducing memory needed to deploy models and allowing teams to deploy on smaller and cheaper GPUs.
Expanding Horizons: Inference Optimization
Pekhimenko sees inference optimization as a potential avenue of growth for CentML. By optimizing model deployment, the company can help teams run models more efficiently, leading to cost savings and improved performance.
Industry Trends and Implications
The AI chip shortage is not a new phenomenon, but it continues to be a pressing issue in the industry. The interest in CentML’s software platform highlights the need for innovative solutions that address these challenges.
Related Topics
- AI: The rise of AI has led to increased demand for high-performance computing resources.
- CentML: This startup is developing tools to optimize machine learning model deployment.
- Funding: Despite smaller seed rounds, larger funding rounds are still being raised in the AI sector.
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Conclusion
The AI chip shortage continues to be a challenge for companies in the industry. CentML’s software platform offers a promising solution, and its recent funding round highlights continued interest in this space.
Sources
- "CentML Raises $27 Million in Extended Seed Round" (TechCrunch)
- "Machine Learning Costs, Talent, and Chip Shortages" (Medium)
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