In 1950, Alan Turing published a seminal paper titled Computing Machinery and Intelligence, sparking a pivotal dialogue that continues to resonate across the disciplines of computer science, philosophy, psychology, and artificial intelligence (AI). This paper is most renowned for introducing what is now called the Turing Test—a method to determine if a machine can exhibit intelligent behavior indistinguishable from that of a human. Turing's exploration begins with the provocative question, "Can machines think?"—a query that has shaped the course of artificial intelligence research and ethical discussions ever since.

This visionary document explores the potential cooperative interaction between humans and computers, a concept that has deeply influenced the development of modern computing and information technology.

In 2017, a groundbreaking research paper titled "Attention is All You Need" was published by Ashish Vaswani and his team of co-authors. This work introduced the Transformer model, a novel deep learning architecture that significantly deviated from the then-standard recurrent neural networks (RNNs) and convolutional neural networks (CNNs) used in natural language processing (NLP). The Transformer model, by focusing solely on attention mechanisms—specifically, a mechanism called "self-attention"—enabled better handling of dependencies in input data, offering a substantial improvement in processing efficiency and model performance.

Coined by Andrej Karpathy, "Software 2.0" represents a significant shift in the way software is being developed and conceptualized in the era of artificial intelligence. In his insightful piece, Karpathy introduces the concept of Software 2.0 as the next evolution of software, where traditional programming languages and manual coding give way to a new paradigm where the software essentially writes and rewrites itself through machine learning models.