Watch out qubits!
Scientists successfully measure high-dimensional qudits, cousins to quantum computing qubits.
Iris Berent argues that the debate stems from the delusional biases in the way humans think about the separation of body and mind.
Elon Musk traveled to Bali this weekend to officially launch Starlink, the SpaceX satellite internet service, in Indonesia this Sunday.
At a launch event with ministers in a health clinic in Indonesia, Musk stressed the significance of providing internet access to far-reaching corners of the vast archipelago, comprised of 17,000 islands across three time zones.
The shimmering of butterfly wings in bright colors does not emerge from pigments. Rather, photonic crystals are responsible for the play of colors. Their periodic nanostructure allows light at certain wavelengths to pass through while reflecting other wavelengths. This causes the wing scales, which are in fact transparent, to appear so magnificently colored.
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Brain-machine interfaces are devices that enable direct communication between a brain’s electrical activity and an external device such as a computer or a robotic limb that allows people to control machines using their thoughts.
Experiments in Netherlands, China, and US demonstrate how qubits can be stored in ‘quantum memory’ and transmitted via fiber optics.
Here’s a nice article discussing the progress of the brain-computer interface industry, some existing startups in the space, and where the industry may go in the future.
Fifty years after the term brain–computer interface was coined, the neurotechnology is being pursued by an array of start-up companies using a variety of different technologies. But the path to clinical and commercial success remains uncertain.
In the vast and ever-evolving landscape of technology, neuromorphic computing emerges as a groundbreaking frontier, reminiscent of uncharted territories awaiting exploration. This novel approach to computation, inspired by the intricate workings of the human brain, offers a path to traverse the complex terrains of artificial intelligence (AI) and advanced data processing with unprecedented efficiency and agility.
Neuromorphic computing, at its core, is an endeavor to mirror the human brain’s architecture and functionality within the realm of computer engineering. It represents a significant shift from traditional computing methods, charting a course towards a future where machines not only compute but also learn and adapt in ways that are strikingly similar to the human brain. This technology deploys artificial neurons and synapses, creating networks that process information in a manner akin to our cognitive processes. The ultimate objective is to develop systems capable of sophisticated tasks, with the agility and energy efficiency that our brain exemplifies.
The genesis of neuromorphic computing can be traced back to the late 20th century, rooted in the pioneering work of researchers who sought to bridge the gap between biological brain functions and electronic computing. The concept gained momentum in the 1980s, driven by the vision of Carver Mead, a physicist who proposed the use of analog circuits to mimic neural processes. Since then, the field has evolved, fueled by advancements in neuroscience and technology, growing from a theoretical concept to a tangible reality with vast potential.
