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Category: computing

Seagate started shipping hard drives with HAMR tech in December 2024, turning a long-awaited technological advancement into a commercial reality. Now, the storage specialist is announcing that even more advanced HAMR drives, with capacities of up to 36 terabytes, are on the way.

The 36TB HAMR drives are being shipped to a select group of customers for testing and validation. Like the earlier HAMR units, these new Exos M drives are built on the Mozaic 3+ technology platform to deliver “unprecedented” areal density. The drives utilize a complex 10-platter design, achieving an areal density of 3.6TB per platter.

According to Seagate CEO Dave Mosley, the company has already reached an areal density of over 6TB per disk in its test environments. The goal, he says, is to further increase the data density to 10TB per platter. Seagate also states that Mozaic 3+ is a highly efficient storage platform, enabling the new Exos M drives to lower the total cost of ownership and reduce energy consumption.

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Can a file be stored on DNA? What would be the advantages of such storage? And what developments can we expect in the future? All these answers in 12 minutes!

0:00 — Introduction.
2:00 — Inspiration from life, DNA
3:24 — Storing files.
7:35 — A technology under development.
10:51 — Conclusion.

Video produced for EchoSciences Sud Provence-Alpes-Côte d’Azur https://www.echosciences-paca.fr with CNRS research director Marc Antonini (I3S — CNRS/UCA). Based on an original idea by Play Azur Prod. Video coordinated by Gulliver https://www.gulliver-sciences.fr and Play Azur Prod: https://playazur-prod.fr/

Calculations and sources of the figures :

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The core components of CRISPR-based genome-editing therapies are bacterial proteins called nucleases that can stimulate unwanted immune responses in people, increasing the chances of side effects and making these therapies potentially less effective.

Researchers at the Broad Institute of MIT and Harvard and Cyrus Biotechnology have now engineered two CRISPR nucleases, Cas9 and Cas12, to mask them from the immune system. The team identified protein sequences on each nuclease that trigger the immune system and used computational modeling to design new versions that evade immune recognition. The engineered enzymes had similar gene-editing efficiency and reduced immune responses compared to standard nucleases in mice.

Appearing today in Nature Communications, the findings could help pave the way for safer, more efficient gene therapies. The study was led by Feng Zhang, a core institute member at the Broad and an Investigator at the McGovern Institute for Brain Research at MIT.

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Computers also make mistakes. These are usually suppressed by technical measures or detected and corrected during the calculation. In quantum computers, this involves some effort, as no copy can be made of an unknown quantum state. This means that the state cannot be saved multiple times during the calculation and an error cannot be detected by comparing these copies.

Inspired by classical computer science, has developed a different method in which the is distributed across several entangled and stored redundantly in this way. How this is done is defined in so-called correction codes.

In 2022, a team led by Thomas Monz from the Department of Experimental Physics at the University of Innsbruck and Markus Müller from the Department of Quantum Information at RWTH Aachen and the Peter Grünberg Institute at Forschungszentrum Jülich in Germany implemented a universal set of operations on fault-tolerant quantum bits, demonstrating how an algorithm can be programmed on a quantum computer so that errors can be corrected efficiently.

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A team of physicists has introduced an innovative error-correction method for quantum computers, enabling them to switch error correction codes on-the-fly to manage complex computations more effectively and with fewer errors.

Error Correction in Quantum Computing

Computers can make mistakes, but in classical systems, these errors are usually detected and corrected using various technical methods. Quantum computers, however, face a unique challenge — quantum states cannot be copied. This limitation means that errors cannot be identified by comparing multiple saved copies, as is done in classical computing.

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Quantum computers have the potential of outperforming classical computers on some optimization tasks. Yet scaling up quantum computers leveraging existing fabrication processes while also maintaining good performances and energy-efficiencies has so far proved challenging, which in turn limits their widespread adoption.

Researchers at Quantum Motion in London recently demonstrated the integration of 1,024 independent silicon quantum dots with on-chip digital and analog electronics, to produce a quantum computing system that can operate at extremely low temperatures. This system, outlined in a paper published in Nature Electronics, links properties of devices at with those observed at room temperature, opening new possibilities for the development of silicon qubit-based technologies.

“As grow in complexity, new challenges arise such as the management of device variability and the interface with supporting electronics,” Edward J. Thomas, Virginia N. Ciriano-Tejel and their colleagues wrote in their paper.

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