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Slide 1 - Presentation Title
The History of Artificial Intelligence
Tracing the journey from ancient myths to the generative AI revolution
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Photo by Tom Parkes on Unsplash
The History of Artificial Intelligence
Generated from prompt:
make a presentation about the history of artificial intelligence
This presentation explores the evolution of AI from ancient myths and early computing milestones like the 1956 Dartmouth workshop, through cycles of AI winters and renewed funding, to the modern renaissance driven by machine learning, deep learning,
April 19, 202611 slides
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Slide 2 - Presentation Agenda
- Origins of AI Research: Early concepts and the Dartmouth workshop (1956)
- The Era of AI Winters: The rise and fall of interest and funding periods
- The Modern AI Renaissance: Machine learning, deep learning, and transformer breakthroughs
- The Generative AI Boom: The current surge in LLMs and generative AI tools
- The Future of AI: Opportunities and ethical challenges ahead
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Photo by Nastuh Abootalebi on Unsplash
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Slide 4 - Early Milestones in AI
Antiquity: Ancient Roots Myths and stories of artificial beings and consciousness. 1940s: The Dawn of Computing Development of programmable digital computers based on formal logic. 1956: Dartmouth Workshop Founding workshop at Dartmouth College; introduction of 'Logic Theorist'.
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Slide 5 - Section 2
2
Cycles of Growth and Stagnation
Funding, expectations, and AI winters
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Photo by Nastuh Abootalebi on Unsplash
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Slide 6 - The Cycle of Investment and Disillusionment
- 1950s: Optimism; researchers expected human-level intelligence in one generation.
- 1974: Lighthill criticism and congressional pressure led to funding cuts.
- Early 1980s: Success of expert systems renewed industry investment.
- 1990s: 'AI Winter'—press criticism and industry avoidance of the field.
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Slide 7 - Section 3
3
The Modern Renaissance
From machine learning to generative AI
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Photo by Tom Parkes on Unsplash
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Slide 8 - The Rise of Modern AI Breakthroughs
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Slide 10 - The Current Landscape and Challenges
- Public accessibility of advanced language models.
- Integration into various business and creative sectors.
- Concerns regarding ethics, algorithmic bias, and data privacy.
- Ongoing debate about societal impacts and AI regulation.
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Photo by H&CO on Unsplash
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Slide 11 - Conclusion
The journey of AI is marked by innovation, cycles of skepticism, and unprecedented breakthroughs that reshape our world.
AI continues to evolve as a transformative force in technology and society.
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Photo by H&CO on Unsplash
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