Independently validated
Reproduced or confirmed by parties other than the originators.
27 milestones.
DeepMind's AlphaFold 2 Achieves Highest-Accuracy Results at CASP14 Protein Structure Prediction Competition
In November–December 2020, DeepMind's AlphaFold 2 system achieved a median Global Distance Test score of approximately 92.4 across all CASP14 targets, far surpassing the next-best group, in a result that computational biologists described as largely solving the 50-year-old protein-folding problem for single-chain proteins.
CURIAL: An AI System to Detect COVID-19 in Emergency Department Patients Using Routine Blood Tests and Vital Signs
In July 2020, researchers at the University of Oxford, led by Dr Andrew Soltan and Professor David Clifton, announced CURIAL, a machine-learning model trained on routine blood tests and vital signs from 115,000 hospital presentations that could identify COVID-19 patients in emergency departments within one hour and with accuracy exceeding 90%.
MIT Researchers Use Machine Learning to Identify Halicin, an Antibiotic Effective Against Drug-Resistant Bacteria
On 20 February 2020, James Collins and colleagues at MIT published research in Cell describing a deep-learning model trained to predict antibiotic activity; the model identified halicin, a compound previously investigated for diabetes treatment, as a potent broad-spectrum antibiotic capable of killing several drug-resistant bacterial strains.
Microsoft Research released Turing Natural Language Generation (T-NLG), a 17-billion-parameter language model
In February 2020, Microsoft Research announced Turing Natural Language Generation (T-NLG), a 17-billion-parameter autoregressive language model trained using the Megatron-LM framework. At the time of release it was the largest publicly disclosed language model and achieved state-of-the-art results on question-answering and summarisation benchmarks.
Google AI Model Matches or Exceeds Radiologist Performance in Lung Cancer Detection from CT Scans
In May 2019, researchers at Google Health and Northwestern Medicine published a deep-learning model in Nature Medicine that detected malignant lung nodules in low-dose CT scans, matching or exceeding the performance of six radiologists on a held-out dataset, with fewer false positives and false negatives when prior scans were unavailable.
FAISS: Facebook AI Research Library for Efficient Similarity Search
In 2017, Jeff Johnson, Matthijs Douze, and Hervé Jégou at Facebook AI Research published FAISS (Facebook AI Similarity Search), a library enabling efficient nearest-neighbour search across datasets of billions of vectors, with GPU acceleration substantially reducing search time compared to prior methods.
Caffe2Go: Facebook's On-Device Neural Style Transfer for Mobile Video
In November 2016, researchers at Facebook AI Research published Caffe2Go, a compressed deep-learning framework that ran neural style-transfer models entirely on iOS and Android devices without sending video frames to a server, enabling real-time artistic video effects on mobile hardware.
DeepMind Publishes AlphaGo, a Deep Reinforcement Learning System That Defeated Professional Go Players
In January 2016, researchers at Google DeepMind published a paper in Nature describing AlphaGo, a system combining deep convolutional neural networks with Monte Carlo tree search and reinforcement learning that defeated the European Go champion Fan Hui 5–0, marking the first time a computer program had beaten a professional Go player at full-board Go.
Blue Brain Project Digital Reconstruction of the Rat Somatosensory Cortex Microcircuitry
On 8 October 2015, Henry Markram and colleagues at the Blue Brain Project published a detailed computational reconstruction of 31,000 neurons and 37 million synapses in a 0.29 mm³ column of juvenile rat somatosensory cortex, creating the first large-scale digital model of a mammalian cortical microcircuit.
BrainGate2 Participants Use Thought-Controlled Robotic Arm to Reach and Grasp
In May 2012, researchers in the BrainGate2 clinical trial, led by Leigh Hochberg and colleagues at Massachusetts General Hospital, Brown University, and affiliated institutions, demonstrated that two participants with tetraplegia could use neural signals decoded from a 96-electrode intracortical array to control a robotic arm and perform reach-and-grasp tasks without manual assistance.
IBM Watson Defeats Human Champions on Jeopardy!
In February 2011, IBM's Watson system defeated Jeopardy! champions Ken Jennings and Brad Rutter across three televised episodes, demonstrating that a computer could parse ambiguous natural-language clues and retrieve factual answers competitively against expert human players.
Robot Scientist Adam
In April 2009, researchers at Aberystwyth University and the University of Cambridge published in Science an account of Adam, an automated laboratory system that independently formulated hypotheses about yeast gene function, designed and executed experiments, and interpreted results without human intervention during the cycle.
Netflix Prize Competition Launched by Netflix
In October 2006, Netflix launched the Netflix Prize, an open competition offering $1,000,000 USD to any team that could improve the accuracy of the company's Cinematch recommendation algorithm by at least 10% on a supplied ratings dataset, measured by root mean squared error.
Rapid Object Detection Using a Boosted Cascade of Simple Features (Viola–Jones Face Detection)
Paul Viola and Michael Jones, then at Compaq CRL and Mitsubishi Electric Research Laboratories respectively, published a cascaded boosting framework for real-time face detection, first presented at CVPR in December 2001 and consolidated in the International Journal of Computer Vision in 2004. The method ran at frame rates suitable for live video on consumer hardware.
Zoe: Autonomous Astrobiology Field Robot for the Atacama Desert
In 2004, a team from Carnegie Mellon University's Field Robotics Center, NASA Ames Research Center, and the University of Tennessee deployed the Zoe rover autonomously across Chile's Atacama Desert, demonstrating robotic detection of subsurface biological life with relevance to astrobiology and future Mars exploration.
TEXTAL System for AI-Assisted Automated Protein Model Building
In 2003, Thomas R. Ioerger and James C. Sacchettini at Texas A&M University described TEXTAL, a pattern-recognition system that automatically traced atomic models through crystallographic electron density maps, substantially reducing the manual labour required in protein structure determination.
A Neural Probabilistic Language Model by Yoshua Bengio and Colleagues
In 2003, Yoshua Bengio, Réjean Ducharme, Pascal Vincent, and Christian Janvin at the Université de Montréal published 'A Neural Probabilistic Language Model' in JMLR, demonstrating that a feed-forward neural network trained on word sequences could learn distributed word representations and outperform n-gram models on perplexity benchmarks.
Deep Blue Defeats Garry Kasparov in Six-Game Rematch
In May 1997, IBM's Deep Blue chess-playing system defeated reigning world champion Garry Kasparov over a six-game match by a score of 3½–2½, becoming the first computer system to defeat a reigning world chess champion under standard tournament conditions.
Nomad Robot Field Experiment, Atacama Desert
In June 1997, Carnegie Mellon University deployed the Nomad robot in the Atacama Desert, Chile, in a NASA-funded field experiment testing long-range autonomous and teleoperated rover navigation over approximately 220 kilometres of terrain, directly informing future planetary exploration rover design.
Chinook Defeats Marion Tinsley to Win the American Checkers Federation and World Checkers Federation Championship
In 1994, Chinook, a checkers-playing program developed by Jonathan Schaeffer and colleagues at the University of Alberta, became world champion after Marion Tinsley withdrew from their match due to illness, making it the first computer program to win a human world championship in any board game.
INTERNIST-I Developed by Jack D. Myers and Harry E. Pople Jr.
Jack D. Myers and Harry E. Pople Jr. at the University of Pittsburgh developed INTERNIST-I, an expert system for internal medicine diagnosis, with its principal public evaluation published in the New England Journal of Medicine in 1982. The system encoded knowledge of roughly 500 diseases and 3,500 symptoms, demonstrating that algorithmic clinical reasoning could approach specialist performance on complex cases.
Blackboard Model Description by Lee Erman, Richard Hayes-Roth, Victor Lesser and D. Raj Reddy
In May 1980, Lee Erman, Richard Hayes-Roth, Victor Lesser and D. Raj Reddy published 'The Hearsay-II Speech-Understanding System: Integrating Knowledge to Resolve Uncertainty' in Artificial Intelligence, vol. 14, providing the canonical description of the blackboard model as a structured framework for cooperative problem-solving among independent knowledge sources.
BKG 9.8: Hans Berliner's Backgammon Program Defeats World Champion Luigi Villa
In July 1979, Hans Berliner of Carnegie Mellon University demonstrated BKG 9.8, a backgammon-playing program, in a money match in Monte Carlo against reigning world champion Luigi Villa, winning 7–1. It was the first computer program to defeat a world champion in a board game under competitive conditions.
Herbert A. Simon Awarded Nobel Memorial Prize in Economic Sciences for Bounded Rationality
In 1978, Herbert A. Simon of Carnegie Mellon University received the Nobel Memorial Prize in Economic Sciences for his theory of bounded rationality, which holds that human decision-making seeks satisfactory rather than optimal solutions owing to cognitive and informational constraints.
First AI Winter: Lighthill Report and DARPA Funding Cuts
In 1973, James Lighthill's report for the British Science Research Council assessed artificial intelligence research and found it had failed to meet its goals; the report contributed to substantial funding cuts in the UK and, alongside DARPA reviews in the United States, precipitated the period known as the first AI winter.
MYCIN: A Rule-Based Expert System for Infectious Disease Diagnosis, Developed at Stanford University
Beginning around 1972, Edward Shortliffe at Stanford University developed MYCIN, a rule-based expert system written in Lisp that used approximately 600 if-then rules to diagnose bacterial blood infections and recommend antibiotic treatments adjusted for patient body weight, establishing a widely studied model for clinical decision support.
The ALPAC Report on Machine Translation
In 1966, the Automatic Language Processing Advisory Committee (ALPAC), convened by the United States National Research Council, published a report concluding that machine translation was slower, less accurate, and twice as expensive as human translation, leading to a sharp reduction in US government funding for machine translation research.