One of the most important aspects to technical writing is simplifying complex or lengthy information.

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One of the most important aspects to technical writing is simplifying complex or lengthy information. You can complete this assignment with or without the help of an AI text generator. If you use AI, just let me know.
Human Summary: Watch this video on the history of AI development. (https://youtu.be/iZCNDZ7ABRE) Pause and take notes while watching the video. Use the video’s subheadings as a guide to create a summary bullet list of the video’s content. (See example below.)
Summary List Example
The History of AI: From Beginnings to Breakthroughs
Introduction
Machine learning began about 80 years ago with the first digital computers
The first “AI” was a robot mouse that could “remember” how to exit a maze
Image Recognition to Image Creation
AI quickly advanced in the quality of generated images from 2017 to present
AI went from recognizing images by analyzing angles on faces to creating original images from word prompts
Etc.

 

Sample Solution

  • Introduction
    • Machine learning began about 80 years ago with the first digital computers.
    • The first “AI” was a robot mouse that could “remember” how to exit a maze.
    • The field of AI has experienced periods of rapid progress and stagnation.
  • Early AI research
    • In the 1950s and 1960s, AI researchers made significant progress in developing algorithms for problem solving and language understanding.
    • However, these early AI systems were often brittle and difficult to scale to real-world problems.
  • The AI winter
    • In the 1970s, there was a period of stagnation in AI research, due to a number of factors, including the difficulty of scaling up AI systems and the lack of clear benchmarks for success.
  • The resurgence of AI
    • In the 1980s and 1990s, AI research made a resurgence, due to the development of new machine learning algorithms and the availability of more powerful computers.
    • This led to the development of new AI applications, such as expert systems and natural language processing systems.
  • The modern era of AI
    • In the past decade, there has been another major wave of progress in AI, driven by the development of deep learning algorithms.
    • Deep learning has enabled AI systems to achieve human-level performance on a variety of tasks, such as image recognition, speech recognition, and machine translation.
  • The future of AI
    • The future of AI is uncertain, but it is clear that this field has the potential to revolutionize many aspects of our lives.
    • AI is already being used in a variety of ways, such as self-driving cars, medical diagnosis, and fraud detection.
    • It is likely that AI will become even more pervasive in the years to come, and it is important to start thinking about the ethical and social implications of this technology.

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