Scientists have managed to get ultrafast lasers running on tiny chips, paving the way for miniature-but-powerful diagnostic devices.
Category: computing
Microsoft accelerates quantum-safe roadmap as risks grow
Microsoft announced today that it is accelerating its quantum-safe security roadmap, saying advances in quantum computing are bringing the need to replace today’s encryption standards sooner than previously expected.
Although today’s quantum computers cannot crack modern encryption, security researchers have warned about “harvest now, decrypt later” attacks. In these attacks, encrypted data that is stolen today is stored until future quantum computers become powerful enough to decrypt it, exposing sensitive information.
As a result, companies including Apple, Google, and Signal have begun integrating post-quantum cryptography (PQC) to replace existing public-key encryption algorithms with quantum-resistant versions.
Brain–computer interface detects hidden awareness in unresponsive patients
A new approach for identifying signs of hidden awareness in people who cannot speak or move after severe brain injury has been demonstrated by researchers at the University of Bath in the U.K.
The system detects patterns of brain activity through a wearable headset using an advanced application of brain-computer interface (BCI) technology.
Across multiple experimental sessions, the researchers uncovered signs of consciousness that were previously undetected in unresponsive patients.
Physicists Solve a “Quantum-Only” Problem Using an Ordinary Laptop
A problem once touted as requiring a quantum computer has now been solved on a laptop.
Using advanced mathematical techniques and sophisticated software, physicists at the Center for Computational Quantum Physics (CCQ) at the Simons Foundation’s Flatiron Institute and collaborators at Boston University showed that a conventional computer can successfully simulate a notoriously difficult quantum system previously claimed to be beyond the reach of classical computing.
Intelligence Without Brains: A Radical New Idea
What if intelligence doesn’t require a brain? Biologist Michael Levin argues that intelligence is not confined to neurons, but exists on a continuum of goal-directed behavior and problem-solving across a wide range of species and systems. Using a framework he calls the “cognitive light cone,” Levin explores diverse forms of intelligence extending all the way down to the cellular level. His research suggests that cells communicate through electrical networks, enabling them to make collective decisions and adapt to unexpected challenges, evidenced by engineered tadpoles capable of seeing through eyes located on their tails. Levin radically challenges the conventional wisdom even further, proposing that forms of intelligence may extend beyond biology to molecular systems and maybe even the weather.
00:00 What is intelligence?
01:03 The field of diverse intelligence.
01:33 Intelligence at the cellular level.
02:08 The cognitive light cone.
03:01 The intelligence of groups of cells.
03:52 The bioelectric language of cells.
04:20 The mind of the body.
04:23 Cells that solve problems.
05:17 The tadpole experiment.
06:25 The cognitive spectrum.
06:48 Can you train a hurricane?
07:03 A new science of intelligence.
07:28 Beyond human biases.
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Quanta Magazine is an editorially independent publication supported by the Simons Foundation. We focus on developments in mathematics, theoretical physics, theoretical computer science and the basic life sciences.
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The hidden structure behind a widely used class of materials
Materials called relaxor ferroelectrics have been used for decades in technologies like ultrasounds, microphones, and sonar systems. Their unique properties come from their atomic structure, but that structure has stubbornly eluded direct measurement.
Now a team of researchers from MIT and elsewhere has directly characterized the three-dimensional atomic structure of a relaxor ferroelectric for the first time. The findings, reported today in Science, provide a framework for refining models used to design next-generation computing, energy, and sensing devices.
“Now that we have a better understanding of exactly what’s going on, we can better predict and engineer the properties we want materials to achieve,” says corresponding author James LeBeau, MIT’s Kyocera Professor of Materials Science and Engineering. “The research community is still developing methods to engineer these materials, but in order to predict the properties those materials will have, you have to know if your model is right.”
This Will Replace Silicon Chips
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Timestamps:
00:00 — New Semiconductor.
08:44 — Computers of The Future.
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