Meta’s CEO Mark Zuckerberg has previously disclosed that the company is developing technology that would enable typing directly with the mind. As reported by MIT Technology Review, the tech behemoth has successfully built this system, which can correctly identify the ‘key’ a user intends to press with about 80% accuracy. While this accuracy rate might not impress seasoned typists, it’s significant to note that this technology operates by reading brain signals externally without the need for any surgical implants or invasive methods.

However, this is not some light, wearable device that one could use casually on a daily basis. Rather, it’s a bulky, costly apparatus that must be operated in a secluded environment to function properly. Sumner Norman, the founder of Forest Neurotech, described it as akin to “an MRI machine tipped on its side and hanging over the user’s head,” with a single unit valued at around $2,000,000.

The device utilizes a magnetoencephalography scanner to detect the magnetic signals produced by neurons as they activate. However, it requires a shielded room to operate correctly due to interference from the earth’s significantly stronger magnetic field. Additionally, any movement of the head by the user can cause a loss of signal, rendering the device impractical for everyday use.

According to Jean-Rémi King, the head of Meta’s Brain & AI Research Team, the goal of their research is not to develop a product for the market. “Our efforts are not aimed at product development,” King stated. “Actually, I consistently communicate that I don’t see a pathway to product development, as the challenges are too daunting.”

Despite these challenges, the research has yielded significant findings, particularly in understanding how the brain processes language. The Meta team has identified that neurons initially generate a signal for a thought or sentence, which then leads to signals for words, syllables, and finally letters. This discovery allowed them to observe how these different levels of language production work together as a system.

The insights gained from this research could potentially inform the development of artificial intelligence. “Understanding the specific architecture or principles of the human brain could guide the development of machine intelligence,” King explained. He also mentioned, “Language has become a core component of AI. Thus, understanding the computational principles that enable a system to acquire language could greatly influence our AI work.”