[Image Source](https://pixabay.com/illustrations/artificial-intelligence-brain-think-4389372/)
Hello, everyone. This part 2 of my three-part series about A.I. You can check the last post [here](https://peakd.com/hive-196387/@amirtheawesome1/an-ai-trilogy-part-1-the-chess-match-that-started-dreams-and-nightmares). However, in this series you won't need to check out previous parts to understand as each part serves as its own idea.
# Containing Intelligence
In the 18th century, 70% of the American workforce was working in agriculture, now? Only 1%. All of that happened within 200 years, industrial revolutions and electric revolutions led to machines taking over human jobs. The technological advancement doesn't stop there either, Andrew Ng, an American computer scientist, and professor at Stanford University, also one of the founders of the online course provider Coursera, said that "A.I is the new electricity".
# Let Me Explain
When electricity was invented in its current form, it lead to a revolution that changed the focus of nations, much like the invention of the steam engine before it. Currently, we live in what Kevin Kelly describes in his book "The Inevitable" as an intelligence revolution (I know that I have overused the word "Revolution" but that's what they said). What's happening basically is that machines are getting smarter.
This intelligence revolution is also addressed by Google, who within the last few years purchased over 13 A.I company. Many work under the assumption that Alphabet, the company running Google, considers the search engine their most important asset, as it brings it more than 70% of its income. That is not the case though, by 2026 Google is expected to be an A.I company, not a search engine.
# Why?
The reason for that is that each day 3 billion searches are happening on the Google search engine, also billions of videos are seen on YouTube by the end of each month. These events don't go to waste, they are recorded. There is an A.I keeping taps on all of that. Now Google studies that when you search a certain adjective then press on a certain article with a name, then by that you are attaching that adjective to that person. For example, if you search "the bald guy from fast and furious", you'd get Vin Diesel in your results.
When it started, Google barely had what we know as "Neural Networks", now that field has advanced so much. What are Neural Networks? Well.
# It Always Comes Back to Biology
Engineers and scientists will always go back to biology studies, in specific, biomimicry. That branch of biology shows how many inventions go back to something in nature. A plane is a great invention, but with all its details, it mimicked a bird by having wings. A.I started like that. It was mimicking nature. Scientists would come up with some concepts based on brains' functions and they'd mimic them. Human brains are more complex of course, but there is inspiration there, to say the least. Those concepts and functions they mimicked are basically Neural Networks. After that, it was time for the next step.
# The Development of Neural Networks
In order for scientists to make something more complicated, they needed to make something called "Parallel Computation". The reason they needed to do that is that they wanted Neural Networks to be better at multitasking. Before that computers couldn't do more than one task at once. It all started with games, as to make those, they needed something more complex to handle as many pixels and functions as possible within the least amount, thus creating the GPU. GPUs starting to get better with time.
# GPU + Neural Networks + Deep Learning = Faster Development
Another thing scientists have found to aid them in their quest is "Big Data". People are now more likely to be on their computers and smart devices, an endless stream of data to feed A.I. Before the introduction of the GPU, Neural Networks couldn't have much done with Big Data. But, after along with the GPU and the great scientific jump introduced by Geoffrey Hinton, the Deep Learning. All three factors have led to the advanced level of A.I we have now. Artificial intelligence with unlimited data, greater power to process, and learn from. This leads us to the big question of this post
# How Do We Contain Artificial Intelligence?
If you have read the last part, then you'd be aware of the greatest chess player in human history who lost to an A.I called Deep Blue, if you haven't, then you don't need to as I just said who he is. Garry Kasparov became a pioneer of a school of thought called "Man plus machine matches", believing that both should be put together and not seen as competition, stating that A.I "Should empower not overpower".
In 2014, during a chess competition, an A.I won 42 matches, but an A.I and a human won 52. This proves that until now at least, human intelligence isn't standing in artificial intelligence. Nowadays, the best chess player isn't A.I or a human, it is a combination of both known as "Centaur".
# A.I Still Relies on Us
We are the source of the A.I's Big Data, human engineers are still the ones training the A.I. There's no machine invented that doesn't have more than one way to turn it off.
# Working With A.I
Many countries have been fast to riding on the A.I wagon. UAE for example was the first country in the world to have an Artificial Intelligence minister. In 2017, China worked on a plan that would make the A.I field worth more than 150 billion dollars by 2030.
# In Conclusion
There's a big movement worldwide chasing this technology, it is possible but still unlikely to be just a trend that will disappear. Andrew Ng prophecized that the A.I would be one day able to do anything a human does within a second. On the other side we sociologist Gary T. Marx who is more pessimistic regarding A.I who thinks it is still too soon to chase such a field as it is still too early considering that A.I still needs way more information to deep learn.
A.I won't be able to learn something the Big Data hasn't offered it. Humans are more dynamic, an A.I would need all the pictures of every variety of a cat to recognize a cat, something that a baby is able to do without the Big Data.
Unlike machines, humans don't need to recognize every possible outcome before committing an action. The point of this post isn't to encourage or discourage, but just to clarify that there is still so much ahead.
In the future, there's a plan to have A.G.I Artificial General Intelligence. Unlike other A.I, this one won't be focused on a certain task but rather a collection of what humans can do and more. There's a possibility that many of the people reading this would live to see an A.I behave fully like humans, can do everything they can do. An A.I that is as smart as humans, if not smarter. By then, would A.I attempt to be in charge of us using its vast intelligence? That question will be answered in the final part of this trilogy "Roboethics".
hiveblocks