Throughout mankind’s history, we have pushed the boundaries of what we consider technologically possible and invented new ways to make tasks easier. The wheel made transporting objects faster, phones made staying in touch a breeze, and the internet has revolutionized how we interact, digest content, and work.
One form of technology that is rapidly growing is artificial intelligence. The way the human mind works and conveys thoughts, whether written or spoken, is something machines have historically struggled with, but with the introduction of ChatGPT-3 from OpenAI, the lines between ideas created in the human mind and by a machine have become nearly indistinguishable.
As with anything new, the field of AI comes with its own vocabulary. Some of the basic terms you should know are:
AI (Artificial Intelligence) – this is a type of intelligence that exists within a machine, as opposed to human or animal intelligence.
Machine Learning – This term refers to the process of how an AI can “learn” based on experience rather than programming.
Chatbot – This is a program that has the ability to communicate with people via text or speech in a way that a human would interact.
Deep Learning – This is a function of AI that imitates the human brain by learning the way data is structured instead of following a preprogrammed algorithm.
Neural Network – A computer system that has been designed to function like the human brain. It is capable of performing tasks that require speech, sight, and even formulating strategies to win games.
The advanced AI we have at our disposal today was not achieved overnight, and there were many necessary steps in order to advance AI to this point. Let’s examine a brief history of AI and what those stages were.
1940s – 1950s
Scientists and researchers started discussing and exploring possible ways to create an artificial brain that is capable of thinking and analyzing like a human.
The field of AI was formally created at Dartmouth College and the first AI conference was held. This marked a crucial advancement in the field of artificial intelligence and machine learning as the top researchers in this area congregated and discussed methods of how to create intelligent machines.
A prototype of a chatbot, named ELIZA, was created. This AI was capable of having a simple conversation with a human. It was also one of the first programs to attempt the Turing test (a test designed to gauge a machine’s ability to exhibit humanlike behavior).
This year saw the creation of the first self-driving car. The AI could keep the vehicle on the road as well as drive it through obstacles. The founder of that car company went on to buy the Fraternal Order of Eagles, only to run it into the ground with his demanding leadership style. (Apparently, what works with AI doesn’t work with people).
Various industries started using advanced decision-making AI in their day-to-day operations. Running off of the expert system, AI could make decisions based on certain rules and criteria.
Deep Blue, a chess-playing AI developed by IBM, beat world champion Garry Kasparov in a six-game match. This victory made it the first computer to win a game.
Watson, another one of IBM’s AI programs, bests human opponents on the show Jeopardy!. This was one of the first times AI has demonstrated the ability to understand and process natural language in a large, public forum.
Deep learning, which uses a neural network to “learn” from large amounts of data, started to be used to solve real-world problems. This kind of advanced AI program is adopted in industries such as healthcare, finance, and retail.
AlphaGo, an AI created by Google, beats the world champion of Go, Lee Sedol, in a five-game match. While this isn’t the first time an AI has beaten a human at a game, Go is considered to be much more difficult to play than chess. This landmark achievement in artificial intelligence has inspired Go players to get better at this ancient game and develop creative, new strategies for it.
The algorithm for creating Deepfakes became widely available. This AI is capable of recreating a person’s likeness and voice. While this does demonstrate an advancement in machine learning, it sparks a worldwide debate on its ethics and use. On one hand, it can be used to put characters in movies even if the original actor is no longer alive (I’m looking at you, Disney). But on the more negative side of things, it could easily be used to make world leaders say things they never said.
Advanced virtual assistants, based on AI algorithms, became available for public use with devices like the Amazon Echo and Google Home. These voice-based assistants are able to recognize human speech and answer questions asked in a number of ways.
Companies began testing autonomous cars and even open robotaxi services in various cities around the world showcasing that the AI systems used in the vehicles can make decisions in a less controlled environment.
Deep learning chips were developed to assist in speeding up the processing time of neural networks. This under-the-hood advance in AI and machine learning dramatically improved the rate at which data could be sorted and processed.
DeepMind Technologies posted a blog about their new visual language model (VLM) dubbed Flamingo. This advanced AI has the ability to accurately describe a picture with only a couple of training images.
Also in 2022, OpenAI’s GPT-3 technology was made available to the public. This state-of-the-art language processing AI has the capacity to produce text and code at a near-human level. Once a prompt is entered, it generates a non-programmed response almost instantaneously.
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This timeline should not be considered a comprehensive list of AI breakthroughs, but rather an overview of how AI has evolved over the last few decades. Even though the field of artificial intelligence officially emerged over 70 years ago, the obstacles have become increasingly smaller and require less time to overcome due to how our computing technology and understanding of AI has advanced throughout the years.
Every day we are figuring out better ways to teach AI how to more closely replicate human behavior and think more like us. By automating tedious, time-consuming tasks with AI, we can streamline our work and increase productivity to do more in less time. While this technology is truly awesome, it still has a ways to go before it takes over the world.