the remarkable History of Artificial intelligence

The Remarkable History of Articial
Intelligence
From Myth to Machine Learning
Dr Venkatasupura Vemulapati
Head ICT EStudio
Dept. of CSE (Data Science)
SITE-Tadepalligudem
July 7, 2025
Dr Venkatasupura VemulapatiHead ICT EStudioDept. of CSE (Data Science)SITE-Tadepalligudem
The Remarkable History of Articial Intelligence July 7, 2025 1/13

Outline of the Journey
1 Introduction
2 Phase 1: The Seeds of an Idea (Antiquity 1950)
3 Phase 2: The Birth of a Field (1950 1974)
4 Phase 3: The First AI Winter (1974 1980)
5 Phase 4: A Commercial Comeback Second Winter (1980s)
6 Phase 5: The Quiet Rise of Machine Learning (1993 2011)
7 Phase 6: The Deep Learning Explosion (2012 Present)
8 Conclusion

A Story of Cycles
The history of AI is not a straight line of progress. It's a dramatic story of:
Brilliant Ideas Soaring Ambition

A Story of Cycles
Crushing Disappointments (AI Winters)

A Story of Cycles
Crushing Disappointments (AI Winters)
Paradigm-Shifting Breakthroughs (AI Summers)
Let's explore this incredible journey.

Ancient Dreams and Formal Thought
Before computers, AI was a dream of philosophy and mechanics.
Mythology Automata: Ancient myths of mechanical servants and
real-world medieval automata were the rst attempts to create
articial, life-like entities.

Formal Logic: Philosophers like Aristotle tried to codify rational
thought, suggesting that reasoning itself could be a mechanical
process.

Formal Logic: Philosophers like Aristotle tried to codify rational
thought, suggesting that reasoning itself could be a mechanical
process.
The Analytical Engine (1840s): Charles Babbage and Ada Lovelace
conceptualized a general-purpose computer. Lovelace foresaw it could
manipulate symbols, not just numbersa core AI concept.

The Golden Age: A Field is Born
The invention of the electronic computer made the dream tangible.
The Turing Test (1950): Alan Turing proposed the Imitation
Game, giving the eld a philosophical goal: Can a machine's behavior
be indistinguishable from a human's?

The Golden Age: A Field is Born
The invention of the electronic computer made the dream tangible.
The Turing Test (1950): Alan Turing proposed the Imitation
Game, giving the eld a philosophical goal: Can a machine's behavior
be indistinguishable from a human's?
The Dartmouth Workshop (1956):
The ocial birthday of AI.
John McCarthy coined the term Articial Intelligence.
A summer workshop of pioneers who believed intelligence could be
simulated.

The Golden Age: Early Successes
This era was dened by Symbolic AI (GOFAI - Good Old-Fashioned AI).
Logic Theorist (1956): A program that proved mathematical
theorems, demonstrating machine reasoning.

Checkers and Algebra: Programs were built that could play games
and solve word problems.

Checkers and Algebra: Programs were built that could play games
and solve word problems.
SHRDLU (1972): A stunning demo where a virtual robot arm
responded to natural English commands in a microworld of blocks.
This created immense optimism.

Winter is Coming: The Hype Collides with Reality
The early optimism led to promises that could not be kept.
Key Problems
The Intractability Problem: Toy problems didn't scale.
Real-world complexity created a combinatorial explosion that
overwhelmed computers.

Key Problems
The Perceptrons Book (1969): Minsky and Papert's book proved
severe limitations of early neural networks, eectively halting that line
of research for over a decade.

Key Problems
The Perceptrons Book (1969): Minsky and Papert's book proved
severe limitations of early neural networks, eectively halting that line
of research for over a decade.
Funding Evaporates: Disappointed government agencies (like
DARPA) and critical reports (like the Lighthill Report in the UK) cut
o the money supply.

The Rise and Fall of Expert Systems
AI found new life by narrowing its focus from general intelligence to specic
tasks.
Expert Systems: The rst truly successful commercial AI. These
systems captured the knowledge of human experts in vast databases of
if-then rules.
Used for medical diagnosis, chemical analysis, etc.
Created a billion-dollar industry and specialized Lisp machine
hardware.

The Rise and Fall of Expert Systems
AI found new life by narrowing its focus from general intelligence to specic
tasks.
Expert Systems: The rst truly successful commercial AI. These
systems captured the knowledge of human experts in vast databases of
if-then rules.
Used for medical diagnosis, chemical analysis, etc.
Created a billion-dollar industry and specialized Lisp machine
hardware.
The Second Winter (Late 80s):
Expert systems were brittle, expensive to update, and the PC revolution
made specialized hardware obsolete. The market collapsed again.

A New Paradigm: Learning from Data
While the AI brand was weak, a new, more robust approach was growing.
The Statistical Shift: A move away from hand-coded rules to
Machine Learning. Systems learned patterns directly from data using
statistics and probability.

Neural Networks Return: Researchers like Hinton, LeCun, and
Bengio quietly rened key algorithms like backpropagation.

Deep Blue vs. Kasparov (1997): A machine defeated the world
chess champion, proving computers could dominate in complex,
intellectual domains.

Deep Blue vs. Kasparov (1997): A machine defeated the world
chess champion, proving computers could dominate in complex,
intellectual domains.
The Internet as Fuel: The web created an unprecedented ood of
data (text, images), which was the perfect fuel for statistical models.

The Cambrian Explosion of AI
The current era was ignited by the convergence of three key factors:
A
Big Data
(e.g., ImageNet)
B
Massive Compute
(GPUs)
C
Algorithmic
Breakthroughs
These three pillars created the modern AI revolution.

Modern Breakthroughs
AlexNet (2012): A deep neural network that shattered image
recognition records. This event is considered the big bang of the
deep learning era.

deep learning era.
AlphaGo (2016): Defeated the world's best Go player, Lee Sedol. It
used Deep Reinforcement Learning to discover strategies no human
had ever seen, proving AI could exhibit true creativity.

deep learning era.
The Transformer (2017): The Attention Is All You Need paper
introduced a new architecture that revolutionized natural language
processing (NLP).

deep learning era.
The Transformer (2017): The Attention Is All You Need paper
introduced a new architecture that revolutionized natural language
processing (NLP).
The Generative AI Boom (2020-): Models based on the
Transformer (GPT, DALL-E, Midjourney) can now generate stunningly
human-like text, code, and art, bringing AI into the mainstream.

The Story So Far
AI's history is a cycle of hype and progress, not a straight line.

The Story So Far
Ideas once dismissed (like neural networks) can return with
world-changing force when the right conditions align.

The Story So Far
Today's AI is built on three pillars: Big Data, Massive Compute,
and Advanced Algorithms.

The Story So Far
Today's AI is built on three pillars: Big Data, Massive Compute,
and Advanced Algorithms.
We are living in the most remarkable and fast-paced chapter of this
history yet.

Thank You!

the remarkable History of Artificial intelligence

More Related Content

Similar to the remarkable History of Artificial intelligence (20)

Recently uploaded (20)

the remarkable History of Artificial intelligence