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Ronna, ronto, quetta, and quecto, the new prefixes for unusual sizes | technology


Ronna, quetta, ronto, and quecto are included as prefixes in the International System of Measurements (SI).
Ronna, quetta, ronto, and quecto are included as prefixes in the International System of Measurements (SI).NPL (Europe Press)

More data is created on digital media daily than all information stored in human history up to 1970. If all the current number of bytes (A shared storage unit consisting of eight binary numbers (0 and 1) or bits) on stacked CDs, the tower will reach far beyond the Moon (more than 384,400 km), according to a study published this year in Sciences. And this work only analyzes what was stored between 1986 and 2007. The pandemic increased the use of digital technology by 400% and the prediction by the end of the decade is that this imaginary collection of disks will reach Mars with only the data generated in one. year: 10 ² bytes. It is not only a physical problem, but also a scientific problem. The designations of units of measure have had to be updated with new prefixes since 1964 to accommodate these unimaginable numbers, both above and below. The latter are runa (10², symbol R) ronto (10⁻²⁷, r), queta (10³⁰, Q) and quecto (10⁻³⁰, q).

Every time the boundaries of the microscopic, physical, biological, or mathematical world are crossed, a problem arises of defining the numbers that allow them to be studied, published, or applied. Not only because of the amount of data, which is the clearest example of approaching these new sizes, but also because of the global distances or, on the contrary, the mass of subatomic particles. Martin Hilbert, author of the study Sciences And a professor at the University of Southern California (USA), explains that “human DNA in one body can contain about 300 times more information than all stored technological devices.”

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The speed of discoveries or exceeding known limits leads to the adoption of informal terms. Many pages on the Internet refer to a file Halabet (10 ² bytes) or in brontobyteinformal terms and symbols (hyb) that can add confusion to investigations, where h is used for hecto (10²) and H for henry, the unit of induction, while b stands for barn (10⁻²⁸ m²) and B, a bel, unit Sound intensity and other physical parameters.

To address this conflict, “representatives of governments from around the world gathered at the General Conference on Weights and Measures (CGPM),” according to the Paris-based institution, last week “agreed to introduce four new prefixes to International System Units (SI) with immediate effect.” “. They are Runa, Koita, Ronto and the already mentioned Kikuto. In this way, the mass of the Earth is about six Rongrams (5.975 trillion tons) and the mass of the electron, one kilogram.

The conference itself justifies the resolution in “the essential role of the International System of Units to provide confidence in the accuracy and global comparability of measurements,” which is essential for industry, commerce, health or security. He also acknowledges that “scientific communities rely on measurements not covered by the current range”, and gives examples of quantities of numerical information that do indeed require magnitudes greater than 10²⁴, as well as the prevalence of “informal” terms.

Adding prefixes is common in the metric system. CGPM had already adopted beta and exa in 1975, to which Zeta (10²), Zepto (10²), Utah (10²) and Yokto (10²) would be added years later. But the same organization admits that the main impetus for consolidating the new size classes was due to “the growing demands of data science and digital storage, which already use prefixes at the top of the existing range.” [yottabyte y zettabyte] To express large amounts of digital information.

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In this sense, explains Richard Brown, promoter of neologisms and chief metrology scientist at the UK National Physical Laboratory in Teddington, “the prefix system has expanded over the years in response to developments in science and technology that require access to a range greater than orders of magnitude in relation to measurement. Brown submitted the proposal to the CGPM on November 17 after five years of studying options and discovering unofficial names.

metrics, according to naturehe sought to suggest terms and symbols of his own prefixes that were not in use for units and that followed the tradition of ending with the letter a for multiplication operations, such as mega (1,000,000 bytes), popular with telephone shows, and with the letter o for smaller scales, such as micro (gram) or nano (meter).

Brown agrees with the CGPM in considering the measure adopted after its “fundamental” initiative due to “the demands of data science, with continued exponential growth through large-scale digitization and the emergence of new technologies, such as quantum computing.” He argues that “these new primers will allow clear and unambiguous communication of these measurements for many years to come.”

The problem will be that the new prefixes and symbols will specify amounts higher or lower than those that have been approved recently. The common thing is to resort to the numerical expression in positive or negative major exponents or to a compound particle, such as kiloquetta or kiloronna.

For Brown, this struggle will take some time. However, the computing speed can shorten the time frame. According to Hilbert, “The fastest growing field of information processing is computing, with computing power increasing by 58% in two decades.” In this sense, according to an article by researchers from Epoch, an AI prediction organization that has not yet been reviewed, as more powerful computer models with greater capabilities are built, there is a lack of sufficient data to train them. This is the case for language model researchers who, according to Tevin LeScaw of artificial intelligence firm Hugging Face, MIT Technology ReviewThey are increasingly concerned about running out of the data they need. In this way, more and more information will be required to be able to distinguish between appropriate and appropriate information for machine learning.

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