On Thursday, July 23rd, I resigned from OpenAI. On the 24th, I started as a Founding Researcher at Conduit. We're building telepathy: thought-to-text models, trained on non-invasive neural data.

Principles and Priorities for Responsible Innovation in Neurotechnology for Canada - Volume 52 Issue 4

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Further Works since 2018 on BCI Brain Computer Interfaces. XR per -say. Here is a short...#Module #Modulework

Brain-Computer-Interfaces sind Schnittstellen, die dem Nutzer die Kommunikation mit Geräten durch Gehirnwellen ermöglicht.

China is determined to become a global leader in the promising field of brain-computer interfaces. This week, the country took a major step toward achieving this ambitious goal. On Wednesday, numerous Chinese media outlets reported that the domestic neurotechnology firm Neuracle (also known as Borui Kang Medical Technology) had successfully performed the world’s first surgical […] Post Elon Musk is kicking himself: China is the first country in the world to launch brain-implantable neurochips for sale at Root-Nation.com.

Patient demonstrations, ongoing clinical trials and heavy investment signal that BCIs could be commercialised by 2030.

Our daily mission is to restore independence for those living with severe motor impairment. But as our CEO Matt Angle and CSO Reema Khan (Green Sands Equity) discuss at the OPEN Silicon Valley Annual ...

Researchers at Northwestern University have developed printed artificial neurons that are capable of directly communicating with living brain cells, marking a significant step forward in neurotechnology and brain-inspired computing. Unlike previous artificial neuron models that only mimic basic electrical behavior, these newly engineered devices generate complex, biologically realistic electrical signals that can activate real neurons in living brain tissue. The artificial neurons are fabricated using flexible, low-cost materials through aerosol jet printing. They incorporate nanoscale flakes of molybdenum disulfide (MoS2) as a semiconductor and graphene as a conductor, embedded within a polymer matrix. A key innovation lies in how the polymer is partially decomposed during operation, forming conductive filaments that constrain electrical current into narrow pathways. This process produces spiking behaviors that closely resemble the timing, shape, and variability of biological neuron firing. In laboratory experiments involving slices of mouse cerebellum, the artificial neurons successfully triggered responses in real neurons, demonstrating functional interaction between synthetic and biological neural systems. Importantly, the signals generated fall within a biologically relevant temporal range, overcoming limitations seen in earlier artificial neuron designs that were either too slow or too fast to interact effectively with living tissue. The researchers suggest that this breakthrough could advance brain-computer interfaces, neuroprosthetics, and other medical technologies aimed at restoring sensory or motor function. Additionally, the work may influence the development of next-generation computing systems inspired by the brain, which could be significantly more energy-efficient than traditional silicon-based architectures. Beyond medical applications, the study also highlights potential implications for artificial intelligence. Current AI systems consume vast amounts of energy, while the human brain operates with far greater efficiency. By mimicking neural communication more closely, future hardware could reduce energy demands while maintaining or improving computational performance.

Stroke is a leading cause of long-term disability, often leaving survivors with permanent hand and arm impairments. Epia Neuro, a San Francisco-based startup, is developing a brain-computer interface (BCI) designed to help stroke patients regain hand movement through a brain implant and a motorized glove. The implant, which is inserted into the skull, detects brain signals indicating a patient’s intent to move their hand. These signals are then translated by artificial intelligence and combined with data from sensors in the glove to assist with gripping. Epia's technology leverages the concept of neuroplasticity, where the brain forms new connections to compensate for damaged areas. The implant collects neural signals from undamaged brain areas and translates them into hand movement. The device is designed to improve motor control through repeated use, potentially enabling patients to regain function without relying on the glove. Epia’s approach is different from other brain-computer interfaces, as it aims to stimulate brain plasticity directly, not just provide external assistance. The company plans to begin human trials in 2026. With an innovative approach and the potential to drastically improve quality of life, Epia’s technology could revolutionize stroke recovery.

A Breakthrough in Nature ElectronicsChinese researchers have developed a stretchable microelectrode that dynamically adapts to the brain's natural movements, solving...