Artificially Intelligent
Artificially Intelligent
Can Machines Think…?
In the first half of the 20th century, science fiction familiarized the world with the model of Artificially Intelligent robots. It begin with the “heartless” Tin man from the Wizard of Oz and continued with the humanoid robot that impersonate Maria in Metropolis.
By the 1950, we had a production of scientists, mathematicians, and philosophers with the concept of artificial intelligence ? or AI culturally learn in their minds. One such person was Alan Turing, a young British polymath who explored the arithmetical possibility of artificial intelligence. Turing suggested that humans use available information as well as reason in order to solve problems and make decisions, so why can’t machines do the same thing.
This was the valid creation of his 1950 paper Computing Machinery and Intelligence in which he discussed how to build intelligent machines and how to test their intelligence.
Making the detection Possible
Unfortunately, talk is cheap. What stopped Turing from getting to work right then and there? First, computers needed to basically change. Before 1949 computers lack a key requirement for intelligence: they couldn’t store commands, only execute them.
In other words, computers could be told what to do but couldn’t consider what they did. Second, computing was mainly expensive. In the early 1950s, the cost of let a computer ran up to $200,000 a month. A proof of concept as well as support from high profile people were needed to prove to support sources that machine intelligence was worth pursuing.
The Conference that Started it All
Five years later, the proof of outset was initialized through Allen Newell, Cliff Shaw, and Herbert Simon’s The Logic Theorist was a program planned to mimic the problem solving skills of a human and was fund by explore and expansion (RAND) Corporation.
It’s considered by many to be the first artificial intelligence program and was presented at the (DSRPAI) hosted by John McCarthy and Marvin Minsky in 1956. In this remarkable meeting, McCarthy, imagining a great collaborative effort, brought together top researchers from a choice of fields for an open ended conversation on artificial intelligence, the term which he coin at the very end result.
Roller Coaster of Success and Setbacks
From 1957 to 1974, AI flourished. Computers could store more information and became faster, cheaper, and more available. device learning algorithms also enhanced and people got better at significant which algorithm to apply to their trouble.
Time Heals all Wounds
We haven’t gotten any good way about how we are doing coding artificial intelligence, so what changed? It turns out, the vital limit of computer storage that was deal us back 30 years ago was no longer a difficulty which estimate that the memory and speed of computers double all year, had as a final point caught up and in many bags, surpassed our needs.
This is exactly how Deep Blue was able to defeat Gary Kasparov in 1997, and how Google’s was able to defeat Chinese Go champion, Ke Jie, only a few months ago. It offers a bit of an clarification to the roller coaster of AI research; we oversupply the capabilities of AI to the level of our present computational power computer storage and processing speed and then wait for Moore’s Law to catch up again.
Artificial Intelligence is all over
We now live in the age of “big-data,” an age in which we have the ability to collect huge sums of information too burdensome for a person to process. The application of artificial intelligence in this regard has already been quite doing well in numerous industries such as technology, banking, marketing, and entertainment.
The Future
So what is in store for the future? In the instant future, AI language is looking like the next big thing. In fact, it’s already underway. I can’t remember the last time I called a company and directly spoke with a human.
In the long term, the goal is general intelligence, that is a machine that surpass human cognitive abilities in all tasks. This is along the lines of the sentient robot we are used to seeing in movies. To me, it seems incredible that this would be accomplished in the next 50 years. Even if the capability is there, the right questions would serve as a strong barrier against fruition. When that time comes (but better even before the time comes), we will need to have a serious conversation about machine policy and ethics but for now, we’ll allow AI to progressively recover and run amok in society.