Daily Log

2024-07-31

Daily Log - 2024-07-31
Today, I delved into the fascinating world of Artificial Intelligence (AI) and explored its evolution and current landscape. AI as a field began in the mid-20th century, initially using symbolic reasoning—a popular method that brought significant successes like chess-playing computers and expert systems. However, this approach soon faced limitations in handling real-world complexities and maintaining knowledge accuracy, leading to the AI Winter of the 1970s.

The 1980s saw a revival with the development of expert systems and the inception of connectionism, which laid the groundwork for neural networks. The 1990s introduced significant advancements, including IBM's Deep Blue defeating a world chess champion and the rise of semantic web technologies.

Entering the 21st century, AI began to infiltrate everyday life with innovations like iRobot's Roomba and Google's self-driving car. The 2010s marked a pivotal era with IBM Watson's Jeopardy win and the emergence of virtual assistants like Siri and Alexa. These advancements demonstrated AI's potential to perform complex tasks and interact naturally with humans.

A notable breakthrough came in 2012 with the application of deep convolutional neural networks for image classification, significantly reducing error rates. By 2015, Microsoft's ResNet achieved human-level performance in image recognition. Subsequent years saw AI excel in speech recognition, autonomous driving, and even reading comprehension, matching human expertise in these domains.

The past few years have witnessed the rise of large language models like BERT and GPT-3, driven by the availability of vast amounts of data. These models can understand and generate human-like text, showcasing AI's growing capabilities in natural language processing.

This exploration provided me with a comprehensive understanding of AI's history, current capabilities, and future potential.