Somite.ai Secures Strategic Investment from AMD Ventures to Advance Foundation Models for Cell Therapy

21 August 2025 | Thursday | News


The partnership integrates Somite’s capsule-based data generation platform with AMD Instinct™ GPUs, enhancing computational power to accelerate large-scale foundation models that could transform the development of next-generation cell therapies.
Image Source : Public Domain

Image Source : Public Domain

Somite.ai, a company pioneering foundation models for human stem cells,  announced a strategic investment from AMD Ventures, following Somite's $47M Series A closing led by Khosla Ventures in May. The collaboration pairs Somite's capsule-based data generation platform with industry-leading AMD Instinct™ GPUs, significantly boosting compute power to accelerate training of Somite's foundation models.

 

Somite is transforming cell therapy by building large-scale foundation models to rapidly accelerate the development of novel cell therapies, significantly compressing timelines and potentially benefiting millions of patients. The company's proprietary capsule technology generates differentiation data at approximately one-thousandth the cost of traditional methods, unlocking unprecedented scale and precision for training powerful predictive models.

 

"We are on the cusp of a true breakthrough in data generation for cell-state transitions. Our capsule-based platform provides dense, causal datasets essential for training transformative foundation models. AMD is uniquely positioned to help us deliver on our promise," said Dr. Micha Breakstone, Co-Founder and CEO of Somite.ai.

 

"Biology is experiencing a computational revolution similar to language and vision. Somite is clearly leading the way, and AMD Instinct GPUs are built for the demands of their ambitious models," said Sagi Paz, Head of AMD Ventures. "We are excited to collaborate with a company converting cutting-edge compute capabilities into meaningful therapies."

The collaboration will explore optimization of software tools for biological data and joint efforts to develop solutions tailored for next-generation foundation models.

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