Lifeboat Foundation

This is interesting. 😃

A new discovery in rats shows that the brain responds differently in immersive virtual reality environments versus the real world. The finding could help scientists understand how the brain brings together sensory information from different sources to create a cohesive picture of the world around us. It could also pave the way for “virtual reality therapy” for learning and memory-related disorders ranging including ADHD, Autism, Alzheimer’s disease, epilepsy and depression.

Continue reading “Virtual reality boosts brain rhythms crucial for neuroplasticity, learning and memory” »

This looks like a really big breakthrough.

A decades-old problem about how to reliably control millions of qubits in a silicon quantum computer chip has now been solved.

Continue reading “‘Missing jigsaw piece’: engineers make critical advance in quantum computer design” »

The research aims to bring the brains to a computer interface to solve its problems.

Eight months in, 2,021 has already become a record year in brain-computer interface (BCI) funding, tripling the $97 million raised in 2019.

A guide to the next computer age.

Quantum engineers from UNSW Sydney have removed a major obstacle that has stood in the way of quantum computers becoming a reality. They discovered a new technique they say will be capable of controlling millions of spin qubits—the basic units of information in a silicon quantum processor.

Until now, quantum computer engineers and scientists have worked with a proof-of-concept model of quantum processors by demonstrating the control of only a handful of qubits.

Continue reading “Engineers make critical advance in quantum computer design” »

In this work, we introduce a classical variational method for simulating QAOA, a hybrid quantum-classical approach for solving combinatorial optimizations with prospects of quantum speedup on near-term devices. We employ a self-contained approximate simulator based on NQS methods borrowed from many-body quantum physics, departing from the traditional exact simulations of this class of quantum circuits.

We successfully explore previously unreachable regions in the QAOA parameter space, owing to good performance of our method near optimal QAOA angles. Model limitations are discussed in terms of lower fidelities in quantum state reproduction away from said optimum. Because of such different area of applicability and relative low computational cost, the method is introduced as complementary to established numerical methods of classical simulation of quantum circuits.

Classical variational simulations of quantum algorithms provide a natural way to both benchmark and understand the limitations of near-future quantum hardware. On the algorithmic side, our approach can help answer a fundamentally open question in the field, namely whether QAOA can outperform classical optimization algorithms or quantum-inspired classical algorithms based on artificial neural networks^48,49,50.

Wirelessly powered microchips, which have an ~1 GHz electromagnetic transcutaneous link to an external telecom hub, can be used for multichannel in vivo neural sensing, stimulation and data acquisition.

A new kind of neural interface system that coordinates the activity of hundreds of tiny brain sensors could one day deepen understanding of the brain and lead to new medical therapies.