The Biological Computing Co. (TBC), a San Francisco-based applied biological computing company, has announced a collaboration with Amazon Web Services (AWS) to commercialize what it describes as the world’s first neuron-derived AI video model. Built on an open-source video generation model, the technology delivers 5x faster generation and 80% lower inference costs, while improving output quality compared with the original model, according to TBC. The collaboration will use AWS infrastructure and distribution capabilities to bring the technology to businesses and creators.
TBC’s technology uses insights from living neurons to develop software-based optimizations for conventional AI models. By studying how biological neurons process information, the company identifies computational principles that can be translated into algorithms designed to make artificial intelligence faster and more efficient.
The company’s optimized text-to-video model incorporates a proprietary software layer derived from measurements of living neural activity. This additional layer represents less than 0.1% of the underlying model and operates entirely on conventional AI infrastructure, eliminating the need for biological hardware or changes to existing customer workflows.
Under the AWS collaboration, TBC plans to deploy its optimized model on AWS Trainium, make it available for deployment through Amazon SageMaker AI, and pursue commercial distribution through AWS Marketplace. The arrangement will allow businesses to access TBC’s neuron-derived AI technology within their existing AWS infrastructure.
The collaboration addresses the growing computational demands and costs associated with generative AI. Video generation is particularly resource-intensive, requiring substantial processing capacity to produce high-quality content. By reducing inference costs and accelerating generation, TBC aims to help businesses serve more customers with their existing computing infrastructure while enabling creators to produce and refine content more quickly.
The optimized video model represents the first commercial product developed through TBC’s biological computing discovery process. Each experiment involving living neurons generates additional data about neural responses and biological computation, which the company uses to identify and develop potential optimization algorithms.
TBC intends to apply the same approach to additional AI models and architectures before expanding into other AI workloads. Its longer-term strategy involves developing new AI architectures informed by biological computation and eventually enabling real-time biological computing, where living biological systems operate alongside conventional silicon-based processors.
Headquartered in San Francisco, TBC brings together neuroscientists, biologists, AI researchers, and engineers to explore how biological computing can improve artificial intelligence. The company is currently accepting early-access requests for its neuron-derived AI model as it prepares for broader commercial deployment.
KEY QUOTES:
“Our partnership with AWS takes neuron-derived AI optimization to commercial scale. We’re turning discoveries from real neurons into faster, cheaper AI for businesses and creators. More importantly, biology gives us a fundamentally different engine for discovering better optimization strategies over time.”
Alex Ksendzovsky, CEO and Co-Founder of The Biological Computing Co.
“Nature solved the computing efficiency problem billions of years ago. TBC’s insight is that we can learn from the original computer, the human brain, to make AI faster, more efficient, and more economical. By building on the AWS AI stack and leveraging go-to-market channels like AWS Marketplace, TBC can move from discovery to commercial scale at startup speed. This is exactly the kind of bold, forward-leaning innovation we love to support at AWS.”
Jason Bennett, Vice President and Global Head of Startups and Venture Capital at AWS
“Compute is becoming one of the biggest constraints on AI. We need more infrastructure, but we also need to make every unit of compute dramatically more productive. Lower inference costs mean more companies can afford to build, scale and put powerful AI to work.”
Jon Pomeraniec, Co-Founder and COO of The Biological Computing Co.
