Artificial Intelligence and Why It's Not as Scary as It Sounds
April 20th, 2023Author: David Thomsen
What is Artificial Intelligence?
History of Artificial Intelligence
1997: IBM computer Deep Blue beats Garry Kasparov, the world champion at the time, in a game of chess. This match lasted for several days and consisted of two wins for Deep Blue, one win for Kasparov, and three separate draws. This game was a rematch from the first match that was played in Philadelphia the year prior.
2011: IBM’s Watson competes (and wins!) a game of Jeopardy against the show's past champions, Brad Rutter and Ken Jennings. This game was not even a contest, as Watson swept the other competitors and was up almost $50,000.
2016: Google’s DeepMind division uses AlphaGo in order to beat legendary Go player Lee Sedol. Go is a strategy board game similar to chess, but infinitely more complex. In chess, there are between 10111 and 10123 positions (including illegal moves). In Go, there are 10360 possible moves. Having been beaten by AlphaGo, Sedol retired and stated “Even if I become the number one, there is an entity that cannot be defeated”.
2022: OpenAI launches ChatGPT which takes the world by storm. The detailed and articulate responses had amazed many of the common users and eventually OpenAI would go on to fine-tune as well as add on to these models and make multiple versions all building on the last and getting better.
The main reason for the huge expansion into AI and deep learning is accessibility. Over the last 60-70 years, hardware architecture has greatly improved, and a large amount of open-source software or materials are easily accessible on the open internet. In the age of big data, AI is used to make common functions much more efficient or personalized. AI is used to recommend ads, operate virtual assistants on your phone or computer, identify and recognize faces and speech in cameras, and help self-driving cars learn.
So... How does it work?
Deep learning as well as neural networks can seem extremely overwhelming but I have outlined the key terms being used as well as a brief overview of how an AI works and learns from the data input.
The next step is to train the AI using the decided on training set then evaluate how well it performs. Continue to tweak the module until it provides the expected outputs, and then it can be tested using testing data rather than the training dataset. Essentially, this is how to test how it would work on its own without a hard-coded expected output.
Should we be scared?
Now I know the idea of computers trying to mimic human brains may seem scary, but in reality it has worked its way into nearly everyone’s day to day life whether they are aware of it or not. If you carry a smartphone, you likely have one of these AI on you. If you use text to speech on that phone, you are using AI. If you use facial recognition as a password for that phone, you are using AI. If you walk in front of a CCTV camera, you will likely have been processed by an AI in order to recognize you. AI is absolutely everywhere now and rather than fear it, people should learn to embrace it and evolve alongside it.