Category Archives: Machine Learning

Is an AI capable of “reading” your mind?


The groundbreaking study titled “Semantic Reconstruction of Continuous Language from Non-Invasive Brain Recordings” has demonstrated the potential of non-invasive brain recordings in decoding continuous language. By utilizing a brain-computer interface (BCI) and functional magnetic resonance imaging (fMRI), researchers were able to extract and analyze cortical semantic representations to reconstruct comprehensible word sequences. This innovative approach sheds light on the distributed nature of language processing in the brain and provides insights into how we comprehend and communicate.

The study’s findings also highlight the importance of human-machine collaboration, as the decoder’s performance was enhanced through subject collaboration in training and operation. Moreover, the research showed the predictive power of encoding and word rate models, allowing for the assessment of brain responses to speech stimuli. These models have the potential to revolutionize speech recognition technology and assistive devices for individuals with speech impairments.

Overall, this study marks a significant step forward in understanding the brain’s language processing mechanisms and opens doors to advancements in communication technology and language disorder treatments. By harnessing the power of non-invasive brain recordings, we can potentially unlock the continuous stream of language that resides within our minds.

Attention in Machine Learning

Attention in Machine Learning

Attention Mechanism in Machine Learning  Over the years, attention mechanism is becoming increasingly popular in machine learning. Attention is the ability to choose, concentrate and process relevant stimuli. The concept has been studied across different disciplines such as neuroscience and psychology. Although the disciplines may have varying definitions of attention, they all agree it helps […]