What is the history of artificial intelligence (AI)? - Zip Capital Group I n s t a n t Q u o t e G e t S t a r t e d N o w
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What is the history of artificial intelligence (AI)?

History of artificial intelligence

The AI we interact with daily basis has been in development since the 1950s.  Understanding the history of artificial intelligence will help you leverage it for your benefit.

Over the last several weeks, I have written about artificial intelligence, defining what it is, discussing applications for small businesses, and how a small business can go about implementing it within their organization.  Perhaps, more impressive than the technology itself, is just how quickly the industry has been evolving.

Before learning about where AI is going, we need to take a quick look at where it came from and how we got to where we are today.  Doing so, will reveal that AI is not a new technology, but rather has been around for decades.  It has also only been within the last year that AI-related techniques and technologies have really taken off.  As a result, AI has “staying power” similar to what we saw with the Internet at the end of the last century.

What is artificial intelligence?

I mentioned the definition of AI in an earlier blog post.  According to the notes of 10 U.S. Code 2358, artificial intelligence is defined as

  1. “Any artificial system that performs tasks under varying and unpredictable circumstances without significant human oversight, or that can learn from experience and improve performance when exposed to data sets.
  2. While there are several definitions of AI, one that works here is an artificial system developed in computer software, physical hardware, or other context that solves tasks requiring human-like perception, cognition, planning, learning, communication, or physical action.
  3. An artificial system designed to think or act like a human, including cognitive architectures and neural networks.
  4. A set of techniques, including machine learning, that is designed to approximate a cognitive task.
  5. An artificial system designed to act rationally, including an intelligent software agent or embodied robot that achieves goals using perception, planning, reasoning, learning, communicating, decision making, and acting.”

What is the history of artificial intelligence (AI)?

The roots of AI go back over 70 years, to the early-1950s.  Computing pioneers such as Alan Turing (of the Turing Test) and Marvin Minsky began establishing the theoretical and technological foundations of AI.  During this time, we saw mainly ideas and concepts emerge, rather than examples of the actual technology itself.  The ‘early beginnings’ of AI lasted through the end of the of the 1960s.

The 1970s and 80s was known as the ‘AI Winter’ because, despite the early optimism with the new technology, AI faced challenges in terms of funding and technological advancement.  These periods of stagnation were due to exaggerated promises and the limitations of existing hardware and algorithms.

Starting in the 1980s, things turned around for AI, and through the 2000s, we saw the introduction and development of neural networks and machine learning.  If you have an interest in AI, you have most likely heard both words, but what are they?

What are neural networks?

Simply put, a neural network is a method of artificial intelligence that teaches computers to process data in a way that is inspired by the human brain.  It is a type of machine learning process, called ‘deep learning’, that uses interconnected nodes or neurons in a layered structure that resembles the human brain.  It creates an adaptive system that computers use to learn from their mistakes and improve continuously.  Thus, artificial neural networks (ANNs) attempt to solve complicated problems, like summarizing documents, or recognizing faces, with greater accuracy.

What is machine learning?

Machine learning is a form of artificial intelligence that is driving much of more popular applications we see today such as chatbots and predictive text.  Machine learning is a subfield of artificial intelligence, which is broadly defined as the capability of a machine to imitate intelligent human behavior.  In other words, AI systems are used to perform complex tasks in a way that is like how humans solve problems.

Neural networks and machine learning underly AI-related developments in the 1980s through 2000s.  The introduction of neural networks and backpropagation algorithms allowed for more sophisticated machine learning techniques.  Researchers began training machines to “learn” from data rather than relying solely on hardcoded logic.  The end of this period saw advancements in AI applications like speech recognition and computer vision.  Neural networks and machine learning enabled the next phase of development of AI, deep learning.

What is deep learning?

Deep learning enables us to automate tasks that typically require human intelligence, such as describing images or transcribing a sound file to text.  Deep learning is a method of AI that teaches computers to process data in a way that is inspired by the human brain.  Deep learning models can recognize complex patterns in pictures, text, sounds, and other data to produce accurate insights.

With big data and powerful computational resources, deep learning techniques gained prominence.  These methods enabled machines to process and learn from vast amounts of data.  Advancements in deep learning dominated the 2010s, laying the foundation for the applications, such as ChatGPT, that everyone is talking about.

ChatGPT is a large language model, the development of which brings us to where we are today, the era of large language models.

What is a large language model (LLM)?

A large language model is a type of artificial intelligence algorithm that uses deep learning to “learn” from a tremendously large amount of data to understand, summarize, generate, and predict new text-based, or “written” content.  A subset of deep learning, large language models, like OpenAI’s GPT (Generative Pre-trained Transformer) series, emerged as a significant advancement in natural language processing.  These models are trained on massive datasets to generate human-like text, answers to questions, and understand context.  The scale and capability of these models, such as GPT-4, allow for a wide range of applications, such as content generation, and customer support tools.

Why is understanding the history of artificial intelligence important?

The AI we are seeing today is not a passing fad, but rather, has been in development since the early 1950s.  As a result, it is not going anywhere.  It will continue to play an increasingly larger role in our lives, businesses, and society as a whole, just as the Internet did in the early to mid 1990s.  The first step in understanding where it is going, is to understand its history, specifically, the history of artificial intelligence.

The best thing you can do to prepare for the inevitable is to learn about it, embrace it, and experiment with it.  Hopefully, we have done just that.  While “AI”, “ML”, “LLMs”, and “deep learning” may have little meaning to you today, just as “online”, “Internet”, and “website” meant little 30 years ago, if history is any indicator, these terms and AI, in general are likely to permeate our lives soon.

If you are ready to implement AI in your small business, or grow your business to the next level, we can help.  We provide merchant cash advances, equipment financing, and working capital financing to small and medium-sized businesses in all industries.   Contact us or call (800) 795-3919 to speak with a small business specialist today.

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