AI TIMELINE

By Nicolas Lobaton

  • Alan Turing

    Alan Turing published "Computing Machinery and Intelligence," introducing the Turing test and opening the doors to what would be known as AI.

  • Marvin Minsky

    Marvin Minsky and Dean Edmonds developed the first artificial neural network (ANN) called SNARC using 3,000 vacuum tubes to simulate a network of 40 neurons.

  • Arthur Samuel

    Arthur Samuel developed Samuel Checkers-Playing Program, the world's first program to play games that was self-learning.

  • John McCarthy

    John McCarthy, Marvin Minsky, Nathaniel Rochester and Claude Shannon coined the term artificial intelligence in a proposal for a workshop widely recognized as a founding event in the AI field.

  • Frank Rosenblatt

    Frank Rosenblatt developed the perceptron, an early ANN that could learn from data and became the foundation for modern neural networks. John McCarthy developed the programming language Lisp, which was quickly adopted by the AI industry and gained enormous popularity among developers.

  • Arthur Samuel

    Arthur Samuel coined the term machine learning in a seminal paper explaining that the computer could be programmed to outplay its programmer. Oliver Selfridge published "Pandemonium: A Paradigm for Learning," a landmark contribution to machine learning that described a model that could adaptively improve itself to find patterns in events.

  • Daniel Bobrow

    Daniel Bobrow developed STUDENT, an early natural language processing (NLP) program designed to solve algebra word problems, while he was a doctoral candidate at MIT.

  • Edward Feigenbaum

    Edward Feigenbaum, Bruce G. Buchanan, Joshua Lederberg and Carl Djerassi developed the first expert system, Dendral, which assisted organic chemists in identifying unknown organic molecules.

  • Joseph Weizenbaum

    Joseph Weizenbaum created Eliza, one of the more celebrated computer programs of all time, capable of engaging in conversations with humans and making them believe the software had humanlike emotions. Stanford Research Institute developed Shakey, the world's first mobile intelligent robot that combined AI, computer vision, navigation and NLP. It's the grandfather of self-driving cars and drones.

  • Terry Winograd

    Terry Winograd created SHRDLU, the first multimodal AI that could manipulate and reason out a world of blocks according to instructions from a user.

  • Arthur Bryson and Yu-Chi Ho

    Arthur Bryson and Yu-Chi Ho described a backpropagation learning algorithm to enable multilayer ANNs, an advancement over the perceptron and a foundation for deep learning. Marvin Minsky and Seymour Papert published the book Perceptrons, which described the limitations of simple neural networks and caused neural network research to decline and symbolic AI research to thrive.

  • James Lighthill

    James Lighthill released the report "Artificial Intelligence: A General Survey," which caused the British government to significantly reduce support for AI research.

  • Symbolics Lisp

    Symbolics Lisp machines were commercialized, signaling an AI renaissance. Years later, the Lisp machine market collapsed.

  • Danny Hillis

    Danny Hillis designed parallel computers for AI and other computational tasks, an architecture similar to modern GPUs.

  • Marvin Minsky, Roger Schank

    Marvin Minsky and Roger Schank coined the term AI winter at a meeting of the Association for the Advancement of Artificial Intelligence, warning the business community that AI hype would lead to disappointment and the collapse of the industry, which happened three years later.

  • Judea Pearl

    Judea Pearl introduced Bayesian networks causal analysis, which provides statistical techniques for representing uncertainty in computers.

  • Peter Brown

    Peter Brown et al. published "A Statistical Approach to Language Translation," paving the way for one of the more widely studied machine translation methods.

  • Yann LeCun

    Yann LeCun, Yoshua Bengio and Patrick Haffner demonstrated how convolutional neural networks (CNNs) can be used to recognize handwritten characters, showing that neural networks could be applied to real-world problems.

  • Sepp Hochreiter, Jürgen Schmidhube

    Sepp Hochreiter and Jürgen Schmidhuber proposed the Long Short-Term Memory recurrent neural network, which could process entire sequences of data such as speech or video. IBM's Deep Blue defeated Garry Kasparov in a historic chess rematch, the first defeat of a reigning world chess champion by a computer under tournament conditions.

  • University of Montreal researchers

    University of Montreal researchers published "A Neural Probabilistic Language Model," which suggested a method to model language using feedforward neural networks.

  • Fei-Fei Li

    Fei-Fei Li started working on the ImageNet visual database, introduced in 2009, which became a catalyst for the AI boom and the basis of an annual competition for image recognition algorithms. IBM Watson originated with the initial goal of beating a human on the iconic quiz show Jeopardy! In 2011, the question-answering computer system defeated the show's all-time (human) champion, Ken Jennings.

  • Rajat Raina, Anand Madhavan, Andrew Ng

    Rajat Raina, Anand Madhavan and Andrew Ng published "Large-Scale Deep Unsupervised Learning Using Graphics Processors," presenting the idea of using GPUs to train large neural networks.

  • Jürgen Schmidhuber, Dan Claudiu Cireșan, Ueli Meier, Jonathan Masci

    Jürgen Schmidhuber, Dan Claudiu Cireșan, Ueli Meier and Jonathan Masci developed the first CNN to achieve "superhuman" performance by winning the German Traffic Sign Recognition competition. Apple released Siri, a voice-powered personal assistant that can generate responses and take actions in response to voice requests.

  • Geoffrey Hinton, Ilya Sutskever , Alex Krizhevsky

    Geoffrey Hinton, Ilya Sutskever and Alex Krizhevsky introduced a deep CNN architecture that won the ImageNet challenge and triggered the explosion of deep learning research and implementation.

  • China's Tianhe-2

    China's Tianhe-2 doubled the world's top supercomputing speed at 33.86 petaflops, retaining the title of the world's fastest system for the third consecutive time. DeepMind introduced deep reinforcement learning, a CNN that learned based on rewards and learned to play games through repetition, surpassing human expert levels. Google researcher Tomas Mikolov and colleagues introduced Word2vec to automatically identify semantic relationships between words.

  • Ian Goodfellow

    Ian Goodfellow and colleagues invented generative adversarial networks, a class of machine learning frameworks used to generate photos, transform images and create deepfakes. Diederik Kingma and Max Welling introduced variational autoencoders to generate images, videos and text. Facebook developed the deep learning facial recognition system DeepFace, which identifies human faces in digital images with near-human accuracy.

  • DeepMind's AlphaGo

    DeepMind's AlphaGo defeated top Go player Lee Sedol in Seoul, South Korea, drawing comparisons to the Kasparov chess match with Deep Blue nearly 20 years earlier. Uber started a self-driving car pilot program in Pittsburgh for a select group of users.

  • Stanford

    Stanford researchers published work on diffusion models in the paper "Deep Unsupervised Learning Using Nonequilibrium Thermodynamics." The technique provides a way to reverse-engineer the process of adding noise to a final image. Google researchers developed the concept of transformers in the seminal paper "Attention Is All You Need," inspiring subsequent research into tools that could automatically parse unlabeled text into large language models (LLMs).

  • Airbus

    Developed by IBM, Airbus and the German Aerospace Center DLR, Cimon was the first robot sent into space to assist astronauts. OpenAI released GPT (Generative Pre-trained Transformer), paving the way for subsequent LLMs. Groove X unveiled a home mini-robot called Lovot that could sense and affect mood changes in humans.

  • Microsoft

    Microsoft launched the Turing Natural Language Generation generative language model with 17 billion parameters. Google AI and Langone Medical Center's deep learning algorithm outperformed radiologists in detecting potential lung cancers.
    2020

  • Oxford

    The University of Oxford developed an AI test called Curial to rapidly identify COVID-19 in emergency room patients. Open AI released the GPT-3 LLM consisting of 175 billion parameters to generate humanlike text models. Nvidia announced the beta version of its Omniverse platform to create 3D models in the physical world. DeepMind's AlphaFold system won the Critical Assessment of Protein Structure Prediction protein-folding contest.

  • DALL-E

    OpenAI introduced the Dall-E multimodal AI system that can generate images from text prompts. The University of California, San Diego, created a four-legged soft robot that functioned on pressurized air instead of electronics.

  • Open AI

    Google software engineer Blake Lemoine was fired for revealing secrets of Lamda and claiming it was sentient. DeepMind unveiled AlphaTensor "for discovering novel, efficient and provably correct algorithms." Intel claimed its FakeCatcher real-time deepfake detector was 96% accurate. OpenAI released ChatGPT in November to provide a chat-based interface to its GPT-3.5 LLM.

  • Elon Musk, Steve Wozniak

    OpenAI announced the GPT-4 multimodal LLM that receives both text and image prompts. Elon Musk, Steve Wozniak and thousands more signatories urged a six-month pause on training "AI systems more powerful than GPT-4."