A new smart mathematician “known as the Ramanujan Machine can reveal the hidden relationships between numbers.link
“Machine” contains algorithms that require statistical assumptions or conclusions that may be true but have not been tested. Themes are the first places of mathematical ideas, the conclusions confirmed by a series of mathematical concepts.
The collection of algorithms is named after Indian mathematician Srinivasa Ramanujan. Born in 1887 to the clerk of the shop and home, Ramanujan was a child prodigy who came up with many arithmetic, proofs and mathematical solutions that had never been solved before.
In 1918, two years before his immediate death due to illness, he was elected Member of the Royal Society of London, becoming the second Indian to be adopted after marine engineer Ardaseer Cursetjee in 1841.
Ramanujan had innate numerical sentiments and an eye for escape patterns, said philosopher Yaron Hadad, vice president of AI and data science at medical device company Medtronic and one of the developers of the new Ramanujan Machine.
The new AI mathematician is designed to extract promising mathematical patterns from the largest possible sets of possible statistics, Hadad said in Live Science, making Ramanujan an appropriate name.
Machine learning, in which the algorithm detects patterns with large amounts of data with minimal guidance from programmers, has been applied to the application of patterns for detection patterns, from image recognition to drug discovery.
Hadad and colleagues at the Technion-Israel Institute of Technology in Haifa wanted to see if they could use machine learning among other important things.
“We wanted to see if we could apply machine learning to something very important, so we thought numbers and number theory were very important,” Hadad told Live Science. (Numerical theory to study numbers, or numbers that can be written without fractions.)
currently, some researchers have used machine learning to convert themes into theorems – a process called automated theorem that proves. The goal of the Ramanujan Machine, instead, is to identify promising themes from the start.
This was previously the domain of human mathematicians, who came up with popular proposals such as Fermat’s Last Theorem, stating that no three good numbers can solve equation an + bn = cn when n is more than 2 (That famous article was written at the end of a book by mathematician Pierre de Fermat in 1637 but was not shown until 1994.)
Directing the Ramanujan Machine, the researchers focused on basic strengths, which are statistical and fundamentally true in all statistics.
The most popular continuation would be the measure of the diameter of a circle in its width, better known as pi. No matter the size of the circle, that ratio remains 3,14159265… and so on.
Algorithms actually scan for large numbers of potential numbers looking for patterns that may indicate the presence of formulas expressing such consistency. Programs start by scanning a limited number of digits, maybe five or 10, and then recording any similarities and enlarging those to see if the patterns repeat.
When a promising pattern emerges, speculation is gained through evidence effort. More than 100 exciting themes have been created so far, says Hadad, and tens of thousands have been confirmed.