Axios/The Daily Beast/Getty Images, Getty Images/Getty, The Daily Beast / The Daily Show/GettyImages, GettyImages/GettyThe most valuable data from an a computer algorithm now.
The most recent update to this chart from the Oxford Internet Institute shows that algorithms now outperform humans at understanding complex data.
While the first chart above shows that computers outperform human programmers in the area of identifying patterns in data, the second chart shows that human programmers also have the ability to solve a large number of algorithms, with algorithms outperforming computers at finding patterns in large amounts of data.
According to the Oxford researchers, human programmers have a high chance of achieving at least the same level of performance as computers when using the same set of rules and algorithms.
The researchers found that the difference between the performance of a human programmer and a computer programmer was roughly 10 times greater than the difference in the performance between a human and a machine when using an algorithm.
And when they analyzed data on the average number of times human programmers used a set of data rules and rulesets over the course of a week, they found that humans are outperforming humans in a lot of the cases they analyzed.
In other words, humans are more than three times as likely as computers to get the same results from a set or set of algorithms.
The researchers also looked at a different set of statistics and found that when it comes to getting the best performance out of an algorithm, the human programmer has a better chance of getting a higher result than a computer.
For example, when analyzing the average rate of data discovery, a human programmers data discovery rate was around 3.8 percent.
But when they examined how often a human was able to find the most recent information in a set, a computer was able be twice as likely to get a higher data discovery result than an algorithm (around 4.6 percent).
In other cases, it looks like computers are just as good at getting the right data to work with as humans.
Using a set containing 10 million unique documents, a machine can only be about 1.5 percent as accurate as a human when it is searching for the most recently updated documents in the set.
But a human could get the right information from about 15 million documents.
Using the same data, a new set of documents could be used up to 1.8 times faster than a human.
Finally, the researchers looked at the number of unique rules and patterns in a dataset and found humans are about two times as accurate at identifying patterns as computers.
So what are the implications of these statistics?
The researchers concluded that the number one takeaway from the results is that human programs are better at solving data problems.
However, the findings show that a large portion of the data they are able to uncover is hidden.
And the researchers also pointed out that humans have to be trained to be as good as computers in finding the right patterns in their data.