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Today’s AI models scale through brute force. We think there’s a better way.

TBC uses real neurons to make models smarter, faster, and cheaper—without adding compute.

This fall, we’re launching the world’s first neurally-optimized video generation model. Sign up below for a first look.

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Today

We build software that optimizes video generation models and work with frontier labs to discover new algorithms for their most important model challenges.

Tomorrow

We’re building toward real-time biocompute: living neurons working alongside silicon to create systems that learn, remember, and adapt continuously using far less energy.

This could power robots that respond more naturally, world models that understand how environments change over time, and multimodal systems that bring together vision, sound and other sensory information.

Discovery engine today. New computing substrate tomorrow.

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Software that Learns from Neurons

Unlike the artificial neural networks currently used by frontier labs, TBC uses real neurons to discover algorithms that make AI models better, faster and cheaper.

Step 1: Identify the problem
We start with an AI model and pinpoint where performance breaks down: the errors, inefficiencies, or limitations in how it processes information.
Step 2: Study the biological response
We design targeted experiments that present living neural networks with a similar challenge. Using multi-electrode arrays, we stimulate the neurons and record how their activity changes across space and time.
Step 3: Translate biology into software
Our researchers analyze the neural response to identify useful mathematical principles. We translate those principles into a lightweight software adapter that plugs into the original model and improves performance.

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The first AI model improved by living neurons.

Play an interactive video model improved with software derived from real neurons.

This is the world’s first look at how real biology improves AI quality, speed, and cost.

Oasis 500M + TBC Neural Optimizer
After
Oasis 500M - Unoptimized Base
Before
Better
2x
higher video quality
Faster
3x
more frames per second
Cheaper
4.4x
lower inference cost
Try our demo

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Be the first to experience a new era of video generation.

This Fall, TBC is launching the world's first neurally-optimized video generation model. Request an invite to try the beta and experience the difference before the everyone else.

By submitting this form, you agree to be contacted by The Biological Computing Co. about your Early Access application, product updates, and launch announcements. You can unsubscribe at any time.

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Lorem ipsum dolor sit amet consectetur

Today’s AI models scale through brute force. We think there’s a better way.

TBC uses real neurons to make models smarter, faster, and cheaper—without adding compute.

This fall, we’re launching the world’s first neurally-optimized video generation model. Sign up below for a first look.

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Lorem ipsum dolor sit amet consectetur

Today’s AI models scale through brute force. We think there’s a better way.

TBC uses real neurons to make models smarter, faster, and cheaper—without adding compute.

This fall, we’re launching the world’s first neurally-optimized video generation model. Sign up below for a first look.

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The measure of true intelligence is the brain.
It’s efficient, adaptive, and constantly integrating what it learns into a living whole.

Right now, we are using living neurons to translate biological insights into software that improves how today’s AI models train and perform.

Next, we will build better computers that can learn, adapt to new environments, and compute for a fraction of the time, energy, and training cost of silicon.

By training living neurons to process information and applying those lessons to the next generation of computing systems, we make training and inference for artificial intelligence models better and more efficient.

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Alex Ksendzovsky MD, PhD

CEO & Co-Founder

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Today

We build software that optimizes video generation models and work with frontier labs to discover new algorithms.

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