2.1 Evolution of AI

is the discipline of computer science that focuses on creating systems capable of performing tasks that typically require human intelligence. These tasks include learning, reasoning, problem-solving, perception, understanding natural language, and more. AI aims to develop machines that can think, learn, and adapt in ways similar to the human brain.

Think of AI like a very smart assistant. Just like a personal assistant helps you by remembering your schedule, finding information, and making recommendations, AI helps machines do similar tasks. It's like giving your computer a brain to understand and help you with everyday tasks.

AI is not a new concept. But recent advances in "generative AI" have impacted our everyday life so deeply that if feels like it just came out of "nowhere". Let's review a history of major AI advances over the years:

  1. Early Foundations (1940s - 1950s)

    • Turing Test (1950): Proposed by Alan Turing, this test assesses a machine's ability to exhibit intelligent behavior indistinguishable from that of a human.

    • Logic Theorist (1956): Created by Allen Newell and Herbert A. Simon, it is considered the first AI program, capable of proving mathematical theorems.

  2. The Birth of AI (1950s - 1960s)

    • Dartmouth Conference (1956): John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon coined the term "artificial intelligence" and organized this conference, marking the birth of AI as a field.

    • Perceptron (1957):An early neural network model developed by Frank Rosenblatt, laying the groundwork for modern neural networks.

  3. Expansion and Setbacks (1970s - 1980s)

    • Expert Systems (1970s): AI systems that emulate the decision-making ability of a human expert, like MYCIN for diagnosing bacterial infections.

    • AI Winter (1980s): A period of reduced funding and interest in AI due to unmet expectations and the limitations of early AI systems.

  4. Resurgence and Growth (1990s - 2000s)

    • Deep Blue (1997): IBM's chess-playing computer defeated world champion Garry Kasparov, showcasing the potential of AI in complex games.

    • DARPA Grand Challenge (2004): Autonomous vehicles competed to navigate a desert course, spurring advancements in self-driving technology.

  5. Modern AI (2010s - Present)

    • Deep Learning (2010s): The resurgence of neural networks with multiple layers, or deep learning, led to breakthroughs in image and speech recognition. Notable systems include Google's DeepMind and OpenAI's GPT series.

    • AlphaGo (2016): DeepMind's AI defeated the world champion Go player Lee Sedol, demonstrating advanced capabilities in handling complex tasks.

    • GPT-3 (2020): OpenAI's language model capable of generating human-like text based on deep learning techniques, highlighting advancements in natural language processing.

    • GPT-4o (July 2024): This is the most current generative AI language model

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