IBM and French neurotechnology startup Inclusive Brains have announced a joint study to develop non-invasive brain-machine interface (BMI) technology using AI, quantum computing, and neurotechnology to better understand brain activity patterns.

The study will use IBM’s Granite foundation models and quantum machine learning to improve brain signal classification and enable users to control digital devices with mental commands.

Inclusive Brains uses a multimodal interface combining brainwaves, eye movements, and facial expressions, aiming to help people with disabilities and those in demanding cognitive tasks.

Research results will be shared openly, with a focus on ethical use of neural data following IBM’s guidelines.

Inclusive Brains has proven its tech in real-life settings, such as monitoring surgeon stress and helping a disabled woman control a robotic arm during the Olympic torch relay.

This partnership represents progress toward developing adaptive, personalized brain-machine interfaces for various applications.

🔗 Source: The National News

🧠 Food for thought

1️⃣ From medical necessity to mainstream computing: BCI’s four-decade evolution

Brain-Computer Interface technology has undergone a remarkable transformation since its emergence in the 1970s when researchers first demonstrated rudimentary control of devices using EEG signals1.

Initially, BCIs were developed exclusively for medical applications, focusing on restoring lost sensory and motor functions for individuals with severe disabilities like ALS and spinal cord injuries2.

The field has steadily progressed from laboratory curiosities to practical applications, with a significant shift beginning around 2007 when consumer applications began to emerge alongside medical uses1.

This IBM-Inclusive Brains partnership represents the latest evolution in a field that historically struggled with the trade-off between signal quality and invasiveness. Early systems either required surgical implants for precision or sacrificed accuracy for non-invasive approaches3.

By combining AI and quantum computing with multimodal sensing (capturing brainwaves, facial expressions, and eye movements simultaneously), this collaboration attempts to overcome limitations that have historically confined non-invasive BCIs to relatively simple applications4.

The partnership builds on decades of neuroscience research showing that non-motor cortical areas can be effectively utilized for device control, potentially expanding BCI applications beyond motor function restoration3.

2️⃣ Personalization represents the next frontier in human-computer interaction

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