Artificial intelligence is the next big thing. It’s the inevitable future of computers, and currently being used to make everything “smart”. You can now see it everywhere, with Apple releasing a personal assistant, Amazon releasing a virtual assistant, Google releasing an AI-powered search engine and so on — there are always plenty of headlines with one company or another applying AI in new ways. But what exactly is artificial intelligence?
Artificial Intelligence: The Beginning of the Future
The history of artificial intelligence starts in 1956 when a computer science professor named John McCarthy first used the term. Although the concept of AI had been around for years, it wasn’t until the mid-1900s that scientists and mathematicians began toying with the idea of creating intelligent machines.
The concept of artificial intelligence was made popular during a workshop at Dartmouth College in 1956. Leading up to the workshop, McCarthy sent a letter to his colleagues stating his intentions to create “every aspect of learning or any other feature of intelligence can be so precisely described that a machine can be made to simulate it.”
Those early scientists were working out of an office at Carnegie Mellon University in Pittsburgh, Pennsylvania, where they developed some of the earliest concepts of AI. The group included Allen Newell, J.C. Shaw, and Herbert Simon, who later went on to win the Turing Award for their work on AI.
The team worked together for most of the 1950s but split up when McCarthy left Carnegie Mellon to teach at Stanford University in 1962. After that point, Newell and Simon focused on developing other areas of computer science, while Shaw continued working on AI projects.
The First Steps in Artificial Intelligence
The beginning of artificial intelligence was in the ’60s with programs like Shakey and ELIZA. Shakey was a robot that could plan its own actions by reasoning over its beliefs about the world. Eliza was a program that simulated human conversation by acting as a psychotherapist; it could engage in back-and-forth conversations with people.
These programs were limited, but they set the stage for subsequent research efforts. In the ’70s and ’80s, AI research had fallen out of favor, but it picked up again in the ’90s due to breakthroughs in machine learning and neural networks (inspired by the architecture of the brain). These techniques allowed computers to learn complex functions without being explicitly programmed how to perform them. For example, neural networks can learn to identify cats in YouTube videos without being told how cats look.
The most recent breakthrough has come from deep learning, which is just a deeper form of machine learning that uses multiple layers of neural networks stacked on top of each other (hence “deep”). Deep learning has caught fire because it has allowed us to make unprecedented progress on previously intractable problems such as speech recognition, image recognition, and language translation.
Several fields where AI is used today
AI has become an integral part of our life. This technology has penetrated into various fields and continues to grow more important in every aspect of these fields. We will shed some light on some of the major areas right now:
Natural Language Processing: AI programs are capable of understanding human languages in terms of their syntax and semantics. This helps to improve the interaction between humans and computers.
Machine Learning: It refers to the ability of a system to learn from existing data and improve its performance over time without being explicitly programmed.
Robotics: Robots are made up of hardware components along with software elements that help them to perform tasks that are normally performed by humans. The software component is developed using AI techniques such as machine learning and computer vision.
Finance: AI’s ability to process information quickly and make predictions about future trends makes it particularly useful for the finance industry. This technology has already been implemented in many areas of the industry, most notably in trading.
One Of The Biggest Challenges For Research Is Managing Risks Posed By Advanced Artificial Intelligence
Knowledge about and access to AI technologies are quickly spreading around the world. And as AI technologies become more capable, they will be applied to a wider range of activities — affecting everything from individual lives to international security.
This rapid diffusion of AI technology will likely increase the risk posed by advanced artificial intelligence (AAI): highly autonomous systems that could eventually match or surpass human abilities. For example, in an extreme case, AAI could potentially lead to a sudden and unpredictable military breakthrough — like the first atomic bomb — with important implications for scenarios such as global conflict or arms races between nations. Such scenarios fall under a broader category of “existential” risks, which are events that threaten humanity’s continued survival.
To help manage risks such as these, it’s important to develop a better understanding of how AAI might unfold and which types of governance would best ensure that it benefits humanity.
Creating safe artificial intelligence is absolutely vital to our future, and it’s going to require the continued collaboration of governments, businesses, and scientists. We don’t want to lose control of the incredible creations we’re bringing into the world — but if we continue to push boundaries with cutting-edge technologies (and are prepared for the consequences), we will unlock an unprecedented level of future human development.