The research is seen as a proof of concept, with potential future applications in biological computing and neurological disorder modeling. However, challenges remain, including keeping the organoids alive and adapting them to more complex tasks. The next steps include studying how brain organoids adapt to more complex tasks and engineering them for greater stability and reliability.
Key takeaways:
- Scientists have developed a "hybrid biocomputer" called Brainoware, which combines lab-grown human brain tissue with conventional circuits and AI. The system has learned to identify voices with 78 percent accuracy.
- The Brainoware system works by placing a brain organoid onto a plate containing thousands of electrodes that connect the brain to electric circuits. The circuits translate information into a pattern of electric pulses, which the brain tissue learns and communicates with the technology.
- The researchers trained the Brainoware system to recognize human voices by translating audio into electric signals to deliver to the organoid. The organic part reacted differently to each voice, generating a pattern of neural activity that the AI learned to understand.
- Challenges for this technology include keeping the organoids alive, especially when moving to more complex areas. The next steps include learning how brain organoids adapt to more complex tasks and engineering them for greater stability and reliability.