@ -9,7 +9,7 @@ In this lesson, we will walk through the major milestones in the history of mach
The history of artificial intelligence, AI, as a field is intertwined with the history of machine learning, as the algorithms and computational advances that underpin ML fed into the development of AI. It is useful to remember that, while these fields as distinct areas of inquiry began to crystallize in the 1950s, important [algorithmical, statistical, mathematical, computational and technical discoveries](https://wikipedia.org/wiki/Timeline_of_machine_learning) predated and overlapped this era. In fact, people have been thinking about these questions for [hundreds of years](https://wikipedia.org/wiki/History_of_artificial_intelligence): this article discusses the historical intellectual underpinnings of the idea of a 'thinking machine.'
## Notable Discoveries
## Notable discoveries
- 1763, 1812 [Bayes Theorem](https://wikipedia.org/wiki/Bayes%27_theorem) and its predecessors. This theorem and its applications underlie inference, describing the probability of an event occurring based on prior knowledge.
- 1805 [Least Square Theory](https://wikipedia.org/wiki/Least_squares) by French mathematician Adrien-Marie Legendre. This theory, which you will learn about in our Regression unit, helps in data fitting.
@ -20,8 +20,7 @@ The history of artificial intelligence, AI, as a field is intertwined with the h
- 1982 [Recurrent Neural Networks](https://wikipedia.org/wiki/Recurrent_neural_network) are artificial neural networks derived from feedforward neural networks that create temporal graphs.
✅ Do a little research. What other dates stand out as pivotal in the history of ML and AI?
## 1950: Machines that Think
## 1950: Machines that think
Alan Turing, a truly remarkable person who was voted [by the public in 2019](https://wikipedia.org/wiki/Icons:_The_Greatest_Person_of_the_20th_Century) as the greatest scientist of the 20th century, is credited as helping to lay the foundation for the concept of a 'machine that can think.' He grappled with naysayers and his own need for empirical evidence of this concept in part by creating the [Turing Test](https://www.bbc.com/news/technology-18475646), which you will explore in our NLP lessons.
@ -35,7 +34,7 @@ The lead researcher, mathematics professor John McCarthy, hoped "to proceed on t
The workshop is credited with having initiated and encouraged several discussions including "the rise of symbolic methods, systems focussed on limited domains (early expert systems), and deductive systems versus inductive systems." ([source](https://wikipedia.org/wiki/Dartmouth_workshop)).
## 1956 - 1974: "The Golden Years"
## 1956 - 1974: "The golden years"
From the 1950s through the mid '70s, optimism ran high in the hope that AI could solve many problems. In 1967, Marvin Minsky stated confidently that "Within a generation ... the problem of creating 'artificial intelligence' will substantially be solved." (Minsky, Marvin (1967), Computation: Finite and Infinite Machines, Englewood Cliffs, N.J.: Prentice-Hall)
@ -55,7 +54,8 @@ Research was well funded by government agencies, advances were made in computati
* "Blocks world" was an example of a micro-world where blocks could be stacked and sorted, and experiments in teaching machines to make decisions could be tested. Advances built with libraries such as [SHRDLU](https://wikipedia.org/wiki/SHRDLU) helped propel language processing forward.
[](https://www.youtube.com/watch?v=QAJz4YKUwqw "blocks world with SHRDLU")
[](https://www.youtube.com/watch?v=QAJz4YKUwqw "blocks world with SHRDLU")
> 🎥 Click the image above for a video: Blocks world with SHRDLU
## 1974 - 1980: "AI Winter"
@ -96,6 +96,7 @@ It remains to be seen what the future holds, but it is important to understand t
[](https://www.youtube.com/watch?v=mTtDfKgLm54 "The history of deep learning")
> 🎥 Click the image above for a video: Yann LeCun discusses the history of deep learning in this lecture
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## 🚀Challenge
Dig into one of these historical moments and learn more about the people behind them. There are fascinating characters, and no scientific discovery was ever created in a cultural vacuum. What do you discover?
Jen Looper
3 years ago