Meta's breakthrough: AI can successfully read 80% of thoughts, & understand how they emerge

Meta recently announced two new breakthroughs from their global research labs. The first highlights that Meta successfully developed a model that can successfully convert brain signals into text. The second reveals how the brain transforms thoughts into words, offering new insights into language processing and AI development.

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Credit: Meta

The first paper refers to an AI model that can decode up to 80% of typed sentences solely from brain activity. The model utilizes noninvasive MEG and EEG recordings, essentially sparing the need to conduct surgical procedures. It presents a few potential benefits, for example, the ability to establish brain-computer interfaces for those who have lost speech and clinical use for brain injury patients.

While the advancement is impressive, researchers are still encountering challenges with accuracy. While the AI can decode up to 80% of characters, errors still occur, making full, reliable communication difficult. It also requires stillness and a magnetically shielded room, which poses issues for practicality. So don't worry - you won't need to build a Magneto-style thought shielding helmet any time soon. It's also unclear how well this would work for patients with brain injuries and disorders.

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Credit: Meta

The second paper delves more into how thoughts turn into words at a neural level. Their findings indicated that the brain processes language in a structured, layered sequence and identified a 'dynamic neural code' that links successive thoughts. In other words, the brain doesn't just process one word at a time- it continuously holds multiple layers of information, seamlessly transitioning from abstract thoughts to structured sentences while maintaining coherence.

The implications of this advancement relate more so to cognitive neuroscience, providing new insights into how we think, and how we could improve AI-powered speech assistance.

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Meta has come a long way since they first announced their 'typing-by-brain' project in 2017 (they were still called Facebook back then). The advancements are currently confined to clinical settings, but it's a step towards seeing it in real-world applications.