The Biological Computing Co. partners with AWS to sell its neuron-derived AI video model

The Biological Computing Co. (TBC), a San Francisco startup that grows living neurons to improve AI models, has partnered with Amazon Web Services to bring its first commercial product, a neuron-derived AI video model, to paying customers. The text-to-video model is tuned with software based on how those cells process information.

TBC built the model on an open-source video generator it has not named. The company says it produces video five times faster and at 80% lower inference cost than the base model, with better output, though it has not published benchmarks and we couldn’t verify the figures.

The neurons themselves stay in the lab. TBC uses them during discovery, then turns what it learns into a lightweight software layer that adds less than 0.1% to the underlying model, unlike the neuron-powered server rack switched on in Singapore in August.

That design means customers need no biological hardware and no change to how they work. The optimized model runs on standard GPUs and cloud accelerators, at the same capacity a company would rent for any other generative model.

Under the partnership, TBC plans to run the model on Amazon’s Trainium chips, offer it for deployment in Amazon SageMaker AI, and list it on the AWS Marketplace, so customers can access it from within the AWS environments they already use.

“Our partnership with AWS takes neuron-derived AI optimization to commercial scale,” said Alex Ksendzovsky, TBC’s chief executive and co-founder.

He described biology as a fundamentally different engine for finding better optimization strategies as the company runs more experiments.

“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,” said Jason Bennett, Vice President and Global Head of Startups and Venture Capital at AWS.

TBC’s commercial case rests on unit economics. Cheaper outputs let a platform take on more users without adding servers, quicker generation shortens the creative loop, and fewer unusable clips mean less compute burned on work nobody keeps.

“Compute is becoming one of the biggest constraints on AI,” said Jon Pomeraniec, co-founder and COO of TBC. “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.”

Each experiment on living cells feeds a growing library of neural-response data and candidate algorithms at TBC. After video, TBC wants to run other models and architectures through the same pipeline, followed by further AI workloads.

Businesses and creators can request early access now.