AWS makes a biological AI model from The Biological Computing Company available in limited testing for video generation
Since 23 September 2026, Amazon Web Services has been making a biological AI model from The Biological Computing Company available to selected customers in limited testing. According to the manufacturer, the model mimics how brain cells process information and is intended to make video generation faster and cheaper.
Since 23 September 2026, Amazon Web Services has been making an AI model from The Biological Computing Company (TBC), designed to improve AI video generation, available to selected customers as part of limited testing (limited preview). According to both companies, there are plans to expand access to all AWS enterprise customers, but for now it is limited to a small group of selected clients.
According to TBC co-founder Alexander Ksendzovsky, the technology works by converting information, such as images, into a form that biological material can process; the team then observes how the biological material processes this data and builds a software tool from the observed behavior that mimics this process. TBC says its model is up to five times faster at generating video than the open-source AI model it runs on and significantly reduces inference costs; however, it has not disclosed which specific "frontier" video generation model is involved, so the comparison cannot be independently verified.
TBC was founded four years ago in Baltimore by two neuroscientists and neurosurgeons, Alexander Ksendzovsky (now CEO) and Jon Pomeraniec (president and COO). This year, the company raised its first substantial investment round of 25 million dollars, led by the fund Primary Venture Partners, and shortly afterward another round of the same amount, bringing total funding to more than 50 million dollars. In San Francisco, the company operates a research laboratory with 35 employees who work with rat brain cells and human stem cells placed on multielectrode silicon arrays from the Swiss company 3Brain; the company derives computational patterns usable for video generation models from the responses of neurons to electrical stimuli. According to the companies, the decision to focus first on video was based on a recommendation from investor and researcher Jeff Dean, because video has established comparative benchmarks that can be used to verify the actual benefit of the technology.
According to AWS, this is not the first biological computing platform in its marketplace - it also works with the Australian company Cortical Labs, which combines laboratory-grown neurons with silicon chips and offers this technology both as a service and as a standalone laboratory device. AWS representative Deap Ubhi also highlights the open question of scalability - it is not yet clear how the model will handle generating longer videos ranging from tens of minutes to an hour without losing quality and consistency.
Why it matters
For companies using AWS for AI video generation, this is another offering that, according to the manufacturer, promises lower costs and higher speed during inference, meaning during normal operation of the model, not during its training. For now, however, it is available only to a limited group of customers, and the key claims about speed increases and cost savings have not been independently verified, nor has the ability of the technology to handle longer videos without losing quality.
Two audiences, two different impacts
What this means
For individuals
Developers working with AI video generation through AWS may in the future be able to try an alternative inference model that The Biological Computing Company describes as faster and cheaper, but for now it is available only to selected customers as part of limited testing.
For a business
Companies addressing the costs and speed of AI video generation have another option on AWS Marketplace that, according to the manufacturer, reduces inference costs and speeds up generation. For now, however, it is only available in limited testing, with no independently verified results and an open question about scalability for longer videos.
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