Timeline of AI

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17/12/2025

2020–Present: Foundation Models & Transformers

August 7, 2025

GPT-5

OpenAI released GPT-5

March 21, 2023

Gemini Released

Gemini was released, formerly known as Bard.

Gemini Icon

December 7, 2022

Perplexity Released

Perplexity Icon

November 30, 2022

ChatGPT Released

ChatGPT was released on November 30, 2022, by OpenAI, and reached 1 million users in 5 days.

ChatGPT Icon

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2015-2019: AI Becomes Mainstream

February 14, 2019

GPT-2 Released

October 11, 2018

Google BERT

Google BERT (Bidirectional Encoder Representations from Transformers) was released on October 11, 2018. In 2019, integrated Google Search.

March 12, 2016

AlphaGo Defeats World Champion

The AI system AlphaGo by DeepMind Google defeats the Go world champion Lee Sedol.

November, 2015

Google’s TensorFlow Released

Google released an open-source platform for machine learning and AI.

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1997: AI Milestone Moment

May 11, 1997

IBM Deep Blue

The Deep Blue is a chess-playing computer developed by IBM that defeated world chess champion Gary Kasparov.

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1960s–1970s: Symbolic AI & Early Optimism

1966

ELIZA Chatbot

The first chatbot ELIZA, was created in 1966 by Joseph Weizenbaum at MIT.

ELIZA simulated a human conversation to interact with users in natural language.

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1940s-1950s: Foundation of AI

1956

First Use of “Artificial Intelligence“ Term

John McCarthy used the term “Artificial Intelligence” at the Dartmouth Conference, and then it became popular.

1950

Turing Test Introduced

The Turing Test was introduced by English mathematician Alan Turing, to test that tries to measure whether the other person is an artificial intelligence or a real human in a dialogue.

1943

Artificial Neuron Model

The Artificial Neuron Model (McCulloch & Pitts) is the first mathematical model of a neuron and a foundational concept in artificial intelligence and neural networks.

Warren McCulloch (neuroscientist) and Walter Pitts (logician) proposed a neuron model to describe how neurons can be represented as basic logical and mathematical units.

How the Model Works (A Simple Explanation)

  • Receives multiple binary inputs (0 or 1)
  • Multiplies each input by a fixed weight
  • Sums the weighted inputs
  • Compares the result to a threshold
  • Produces a binary output (0 or 1)

Logical Behaviour

Logic GateBehaviour
ANDFires only if all inputs are 1
ORFires if at least one input is 1
NOTInhibits firing
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