History of AI

- Define the concept of artificial intelligence and its significance in modern society.

- Discuss the origins of AI and its evolution over time.

- Explore key themes and advancements in the field.

The Turing Test

- Introduce Alan Turing's seminal work on computing machinery and intelligence.

- Examine the inception of the Turing Test and its implications for AI.

- Discuss challenges, alternatives, and the current state of the Turing Test.

History of AI Applied to Chess, and games in general

- Trace the history of AI applications in chess, from its origins to modern developments.

- Explore the role of computer-chess, realizations, and advancements in game-playing AI.

- Discuss the significance of games like Go as a frontier for AI research.

Expert Systems

- Provide an overview of expert systems in artificial intelligence.

- Address key technological issues, managerial challenges, and social implications.

- Reflect on the possibilities and limitations of creating "thinking" machines.

AI Winter and Lessons Learned

- Explore the phenomenon of AI Winter and its impact on the field.

- Discuss triggers, reports (ALPAC, Lighthill), duration, and lessons from AI Winter.

- Analyze the implications for future developments in artificial intelligence.

History of AI from 2019 - 2024

1. 2019

   • Advancements in Natural Language Processing (NLP) with the rise of models like BERT.

   • Increased adoption of AI in healthcare for image analysis and diagnostics.

2. 2020

   • Growing concerns around bias in AI algorithms, leading to more emphasis on ethical AI development.

   • AI plays a crucial role in managing the COVID-19 pandemic through contact tracing and vaccine development.

3. 2021

   • Introduction of high-performance language models like GPT-3.

   • Expansion of AI applications in industries such as finance, marketing, and agriculture.

4. 2022

   • Continued focus on AI safety and regulation with initiatives like the EU's AI Act.

   • AI-powered automation leads to transformations in the workforce, emphasizing the need for upskilling.

5. 2023

   • Breakthroughs in reinforcement learning algorithms for more efficient AI training.

   • AI integrated into smart cities for optimizing traffic flow and energy consumption.

6. 2024 (Till Date)

   • Increased collaboration between AI and other emerging technologies like blockchain and IoT.

   • Rising trend of explainable AI for enhancing transparency and trust in AI systems.