Scientists Grow Brain in Dish, Computes 100,000x Faster

## **Cortical Labs' CL1 system uses 800,000 living human neurons to create the world's first commercial biological computer that learns faster and consumes 90% less energy than traditional AI systems.** Scientists just achieved something that sounds like science fiction: a computer that runs on actual human brain cells. **Cortical Labs** released the **CL1**, the world's first commercial biological computer that fuses living human neurons with silicon hardware to create what they call **Synthetic Biological Intelligence (SBI)**. This isn't just another AI breakthrough. The **$35,000 system** contains **800,000 lab-grown human neurons** reprogrammed from skin or blood samples of real adult donors. These cells remain viable for up to six months, fed by a sophisticated life-support system that controls temperature, supplies nutrients, and filters waste products. ## The Technology That Rewrites Computing Rules The CL1 represents a fundamental shift in how we think about processing power. Unlike traditional silicon-based systems that follow rigid programming, these human-cell neural networks create an ever-evolving organic computer that learns with **shocking speed and flexibility**. **Dr. Brett Kagan**, chief scientific officer at Cortical Labs, explains the breakthrough: "We're essentially growing a brain in a dish and teaching it to compute." The system builds on their earlier **DishBrain prototype**, which trained cell cultures to play Pong in a simulated environment. The neurons learned to track the ball and control a paddle within **minutes of gameplay**. This approach parallels advances in [brain-computer interfaces that help paralyzed patients control robotic devices](/technology/ucla-brain-chip-paralyzed-patients-4x-faster). The CL1 features **59 electrodes per unit** that provide bi-directional stimulation and reading interfaces for real-time data input and neural monitoring. ## Energy Efficiency That Shames Silicon Here's where biological computing gets revolutionary: energy consumption. A rack of CL1 units consumes just **850-1,000 watts**, while a data center setup running equivalent AI workloads requires tens of kilowatts. That's potentially **100,000 times less energy** than current AI systems. **Fred Jordan**, a researcher working with similar technology, puts it simply: "Human neurons are the best at learning" compared to other cellular computing approaches. The neurons form new pathways and connections through electrical stimulation, creating processing units that can replicate memory, logic gates, and decision-making basics. Researchers train the neural networks using dopamine rewards and electrical stimulation, creating systems that are fundamentally more adaptive than silicon-based computers. ## Commercial Reality Arrives in Late 2025 **Cortical Labs** plans widespread commercial availability in the **second half of 2025**, offering two access models: direct purchase of the **$35,000 units** or **"Wetware-as-a-Service"** cloud access for researchers who want to experiment without the full investment. The company plans **4 server stacks with 30 units each**, creating a biological computing farm for AI, drug discovery, and disease modeling. **Swiss company FinalSpark** offers human-brain organoids for **$500 per month**, with **34 universities** already using the platform for research applications. ## Research Applications Transforming Medicine **Research teams at 34 universities** are using these systems for Alzheimer's research, drug discovery, and AI development. Each **0.5-millimeter organoid** contains around **10,000 living neurons** that can test how drugs affect neurons or screen chemicals for neurotoxic effects. This research supports advances in [AI systems that can detect consciousness in coma patients](/health/ai-detects-hidden-consciousness-coma-patients) by understanding neural network responses. ## The Future of Intelligence Is Biological This breakthrough represents the emergence of **"organoid intelligence,"** a scientific field that leverages the strengths of living brain cell cultures, learning from fewer examples, adapting in real-time, and using energy efficiently. Unlike conventional AI that requires massive datasets and energy-hungry training processes, biological computers learn through experience, just like human brains. The technology faces challenges: organoids survive only about **100 days** and ethical questions about potential consciousness remain unresolved, especially considering recent research into [the fundamental nature of consciousness itself](/psychology/scientists-cracked-consciousness-mystery-brain-research). But the potential applications are staggering, from personalized drug discovery to AI systems that adapt and learn like living beings. The implications extend beyond computing into questions about reality itself, as some researchers explore whether [biological processes might reveal clues about the nature of our universe](/science/scientists-found-evidence-digital-universe). **Cortical Labs** has created more than just a new type of computer. They've opened a door to intelligence that's truly alive, responsive, and efficient in ways silicon never could be. By **late 2025**, researchers worldwide will have access to computing power that thinks, learns, and adapts using the same biological processes that created human consciousness itself. ## Sources 1. [New Atlas](https://newatlas.com/brain/cortical-bioengineered-intelligence/) - Cortical Labs CL1 technical specifications 2. [Scientific American](https://www.scientificamerican.com/article/these-living-computers-are-made-from-human-neurons/) - Scientific principles of biological computing 3. [Live Science](https://www.livescience.com/technology/computing/worlds-1st-computer-that-combines-human-brain-with-silicon-now-available) - Commercial availability details 4. [Communications of the ACM](https://cacm.acm.org/research/biocomputation-moving-beyond-turing-with-living-cellular-computers/) - Biocomputation research framework 5. [Tom's Hardware](https://www.tomshardware.com/tech-industry/worlds-first-body-in-a-box-biological-computer-uses-human-brain-cells-with-silicon-based-computing) - Technical architecture analysis