The rise of the machines, as shown in some science fiction, ushers the destruction of humanity.
Our technological advancements – and, basically, extraordinary human intelligence – made it possible to develop these machines we think only exist in movies or books. This helped us improve our work productivity and makes daily life more convenient.
But these machines are still manually controlled by us, operating on programmed instructions and has no autonomy on what it’s doing – just like a soulless human being (or is there any?). And this goes contrary to those walking, metallic humanoids striking terror to humanity in the movies.
What? Machines Can Learn?
Of course, machines can learn – but in a different way than us humans. Through Machine Learning, computers learn through examples with the help of algorithms (a lavish word for mathematical recipes) that feeds on data and improves from it to better interact with the data. The algorithms learn how to effectively improve their jobs.
Take this for example. Spam email filter. The spam filter works by blocking your junk email. To do this, it conducts an analysis to learn what spam email looks like by mathematically studying a large set of spam emails and then accurately identify new spam before it seeps to your inbox instead of manually filtering them yourself.
Totally Cool … Err … Creepy!
It might sound creepy for a computer to learn how to distinguish a legit email from spam but, ironically, it is happening …every day. Aside from spam filter, it is also used in search engines to provide us better query results; in optical character recognition, a method wherein natural texts are converted into machine-encoded text; and in computer vision, a technology that automates tasks that the human visual system can do.
Machine Learning is also tapped by scientists in the field of medicine such as Cancer Diagnostics that studies breast cancer pathology reports which would take about four expert pathologist to analyse and understand as well as reach a decision about which areas to treat.
Another field that taps on machine learning is cybersecurity. Some IT security firms, especially IT Security Services Australia, speculate that it’s still not ready to replace conventional human methods, but can boost efforts by automating the processes involved in recognising infection and attack patterns. Undeniably, with its distinct use cases, it helped improved the fight against cybercrime.
Also some IT services, like IT Solutions Australia, use machine learning to better analyse the integrity of their client’s IT systems through past data and also give them a forecast of any possible IT problems.
Machine Learning has advanced so much in the last decade that it’s becoming more difficult to determine what’s going to be the extent of other possibilities in the future. But as long we do our best to improve and learn, we can avoid the risks that will come if some “evil genius” will try to undo the best-laid plans that ethical scientist put into place for the future of artificial intelligence.