Generated from prompt:
make a presentation about the history of artificial intelligence
Traces AI from 1940s pioneers (Turing, Wiener), 1956 birth, 1970s-90s winters, 2000s ML resurgence, 2010s deep learning (AlexNet, Transformers), to ethical future. (168 chars)
This is a title slide titled "The History of Artificial Intelligence." Its subtitle describes exploring AI's evolution from early concepts to today's transformative technologies.
Exploring the evolution of AI from early concepts to today's transformative technologies.
This agenda slide outlines a presentation on AI's evolution. It covers early concepts, the birth of AI, AI winters, revival with ML, the deep learning era, and future outlook.
Source: History of Artificial Intelligence
This section header slide introduces Section 02, titled "Early Concepts (1940s-1950s)." Its subtitle describes foundational ideas in computation and intelligence.
02
Foundational ideas in computation and intelligence.
The "Key Pioneers" slide highlights foundational AI contributions. It lists Alan Turing's 1950 paper "Computing Machinery and Intelligence," Norbert Wiener's Cybernetics, and McCulloch-Pitts neural networks.
The slide, titled "Turing's Famous Question," presents a quote from Alan Turing proposing: "Can machines think?" This question ignited AI debates and inspired the Turing Test, crediting Turing as a pioneering mathematician and computer scientist.
> I propose to consider the question, 'Can machines think?' This challenge ignited the debate on artificial intelligence and inspired the Turing Test.
ā Alan Turing, pioneering mathematician and computer scientist
Source: Computing Machinery and Intelligence, 1950
In 1956, the Dartmouth Conference coined the term "Artificial Intelligence" and Newell and Simon developed the first AI program, Logic Theorist. The next years brought Frank Rosenblatt's Perceptron neural network in 1957 and initial US government funding for AI research in 1958.
1956: Dartmouth Conference Convened John McCarthy organizes workshop; coins term 'Artificial Intelligence' for machine intelligence simulation. 1956: Logic Theorist Developed Newell and Simon create first AI program, proving theorems in Principia Mathematica automatically. 1957: Perceptron Introduced Frank Rosenblatt invents Perceptron, pioneering single-layer neural network for pattern recognition. 1958: Early AI Funding Begins US government invests in AI research post-Dartmouth, fueling perceptron and logic advancements.
Source: History of Artificial Intelligence
This section header slide, numbered 06, is titled "AI Winters (1970s-1990s)." It defines these as periods of reduced funding caused by overhyped expectations.
06
Periods of reduced funding due to overhyped expectations.
The slide outlines the First AI Winter (1974-1980), sparked by the Lighthill Report's criticism of AI as overhyped, which caused sharp government funding cuts and stalled research. It also covers the Second AI Winter (1987-1993), driven by expert systems' failure to scale, leading to investor disillusionment and major global funding reductions.
| First AI Winter (1974-1980) | Second AI Winter (1987-1993) |
|---|---|
| Lighthill Report in UK criticized AI as overhyped and unproductive, leading to sharp funding cuts from government agencies. Research progress stalled amid unmet expectations. | Expert systems failed to scale or deliver promised results, causing investor disillusionment. Major funding cuts followed, halting many projects worldwide. |
The "Key Milestones Stats" slide highlights major AI achievements: Deep Blue defeating chess champion Kasparov in 1997, Watson winning Jeopardy in 2011, and AlphaGo beating Lee Sedol at Go in 2016. It also notes a record surge of $40B+ in global AI investments in 2023.
First computer defeats chess champion
AI excels on quiz show
Masters ancient game of Go
Record global funding surge
The slide "Rise of Machine Learning" features an image highlighting the resurgence of neural networks in the 2000s. It covers the shift from rule-based to data-driven AI, fueled by big data and computing power, leading to deep learning advancements.
Source: Wikipedia
The Deep Learning Revolution, from the 2010s to now, ignited with AlexNet's ImageNet win in 2012 and was transformed by attention mechanisms in Transformers. GPT models then scaled generative AI to billions of parameters, enabling applications like autonomous vehicles and ChatGPT.
The conclusion slide, titled "The Future of AI," highlights that AI's path forward involves integration, innovation, and ethical advancement. It calls on viewers to remain engaged in shaping responsible AI development.
AI's Future: Integrate, Innovate, Ethically Advance.
Stay engaged in shaping responsible AI development.
Source: Wikipedia
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