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It thus improved upon the previous record-holding prime, 6,700,417, also discovered by Euler, forty years earlier. The number 2,147,483,647 remained the largest known prime until 1867. [4] In computing, this number is the largest value that a signed 32-bit integer field can hold.
In computing, half precision (sometimes called FP16 or float16) is a binary floating-point computer number format that occupies 16 bits (two bytes in modern computers) in computer memory. It is intended for storage of floating-point values in applications where higher precision is not essential, in particular image processing and neural networks .
All integers with seven or fewer decimal digits, and any 2 n for a whole number −149 ≤ n ≤ 127, can be converted exactly into an IEEE 754 single-precision floating-point value. In the IEEE 754 standard , the 32-bit base-2 format is officially referred to as binary32 ; it was called single in IEEE 754-1985 .
The sign bit determines the sign of the number (including when this number is zero, which is signed). The exponent field is an 11-bit unsigned integer from 0 to 2047, in biased form: an exponent value of 1023 represents the actual zero. Exponents range from −1022 to +1023 because exponents of −1023 (all 0s) and +1024 (all 1s) are reserved ...
As such, Python, Ruby, Haskell, and OCaml prefix octal values with 0O or 0o, following the layout used by hexadecimal values. Several languages, including Java, C#, Scala, Python, Ruby, OCaml, C (starting from C23) and C++ can represent binary values by prefixing a number with 0B or 0b.
For example, the number 2469/200 is a floating-point number in base ten with five digits: / = = ⏟ ⏟ ⏞ However, 7716/625 = 12.3456 is not a floating-point number in base ten with five digits—it needs six digits. The nearest floating-point number with only five digits is 12.346.
The number 4,294,967,295 is a whole number equal to 2 32 − 1. It is a perfect totient number, meaning it is equal to the sum of its iterated totients. [1] [2] It follows 4,294,967,294 and precedes 4,294,967,296. It has a factorization of .
Thus the "order of magnitude" of a number (on a larger scale than usually meant), can be characterized by the number of times (n) one has to take the to get a number between 1 and 10. Thus, the number is between 10 ↑ ↑ n {\displaystyle 10\uparrow \uparrow n} and 10 ↑ ↑ ( n + 1 ) {\displaystyle 10\uparrow \uparrow (n+1)} .