Machine learning
Statistical learning generally.
28 milestones used this technique.
BrainGate researchers decode imagined handwriting from neural signals to enable high-speed text communication
In May 2021, Francis R. Willett and colleagues at Stanford University and Howard Hughes Medical Institute published results showing that a BrainGate2 intracortical electrode array could decode imagined handwriting movements in a paralysed person at 90 characters per minute with 94.1% raw accuracy, substantially exceeding prior neural-interface typing rates.
Milad Abolhasani and colleagues demonstrated Artificial Chemist 2.0, an autonomous flow chemistry platform for quantum dot synthesis
In December 2020, Milad Abolhasani's group at North Carolina State University published Artificial Chemist 2.0, an autonomous flow chemistry system combining machine learning with robotic synthesis to navigate a space of approximately 20 million quantum dot formulations and produce a target material within roughly 30 minutes of initiating a search.
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%.
Facebook Deploys AI-Assisted Suicide Prevention Detection Across Live Video
In November 2017, Facebook announced the global expansion of an AI system designed to detect signs of suicidal intent in posts and Live videos, using pattern recognition trained on reports flagged by human reviewers to surface at-risk content to its Community Operations team and connect users with crisis resources.
Facebook AI Research Published StarSpace: Embed All The Things!
In September 2017, Ledell Wu and colleagues at Facebook AI Research published StarSpace (arXiv:1709.03856), a general-purpose neural embedding model capable of learning entity representations across tasks including text classification, ranking, and collaborative filtering, without task-specific architecture changes.
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.
Moley Robotics Demonstrates Robotic Kitchen System at Hannover Messe
In April 2015, London-based Moley Robotics unveiled a prototype robotic kitchen system at Hannover Messe, comprising a pair of dexterous robotic arms capable of replicating recorded human cooking movements, integrated with an oven, hob, and dishwasher in a fitted kitchen unit.
Google, NASA and USRA Launch Quantum Artificial Intelligence Lab
In May 2013, Google, NASA Ames Research Center and the Universities Space Research Association jointly established the Quantum Artificial Intelligence Lab at NASA's Ames facility, housing a D-Wave Two quantum processor to investigate whether quantum annealing could accelerate machine-learning tasks.
Google Brain Unsupervised Neural Network Learns to Detect Cats from YouTube Frames
In June 2012, Quoc V. Le and colleagues at Google Brain published research showing that a 1,000-machine, 16,000-core neural network trained without labels on 10 million YouTube thumbnail images spontaneously developed a neuron selectively responsive to human and cat faces, demonstrating large-scale unsupervised feature learning from unlabelled video data.
Google Launches Google Now Predictive Information Assistant
Google launched Google Now at Google I/O on 27 June 2012, bundled with Android 4.1 (Jelly Bean). The system used contextual signals (location, search history, calendar entries and travel data) to surface unsolicited, time-relevant information cards without requiring an explicit query.
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.
Microsoft Research Develops Real-Time Human Pose Estimation for Kinect
In 2011, Jamie Shotton and colleagues at Microsoft Research Cambridge published a method for real-time human pose estimation from a single depth image, using randomised decision forests trained on synthetic data. The technique powered the skeleton-tracking feature of Microsoft Kinect and was presented at CVPR 2011.
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.
LOPES Exoskeleton Robot for Interactive Gait Rehabilitation
Researchers at the University of Twente, led by Jan F. Veneman and colleagues, developed LOPES (Lower Extremity Powered ExoSkeleton), a treadmill-based robotic exoskeleton for interactive gait rehabilitation following stroke, with the system described fully in a 2007 IEEE publication. The robot combined powered hip and knee actuation with impedance control to support or resist patient movement during walking.
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.
Autonomous Robotic Cardiac Surgery Guided by Machine Learning
In May 2006, a robotic surgical system at the University of Toronto, trained on data from more than 10,000 prior operations, performed an autonomous 50-minute cardiac procedure on a beating human heart, demonstrating machine-learning-guided autonomy in a clinical surgical setting.
Stanford Racing Team's Stanley Wins DARPA Grand Challenge 2005
On 8 October 2005, a Stanford University team led by Sebastian Thrun entered Stanley, a modified Volkswagen Touareg, in the DARPA Grand Challenge. Stanley completed the 131.6-mile (211.8 km) Mojave Desert course autonomously in under 7 hours, finishing first and winning the $2 million prize.
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.
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.
Machine Learning Detection of Least Significant Bit Steganography
Around 2003, researchers published work applying machine learning classifiers to the detection of least significant bit steganography in digital images, training models to distinguish unaltered carrier images from those embedding hidden data in both uncompressed and compressed formats.
Bag of Words Applied to Computer Vision (Visual Vocabulary / Bag of Visual Words)
Josef Sivic and Andrew Zisserman at the University of Oxford applied the Bag of Words text-retrieval model to visual features in their 2003 ICCV paper 'Video Google', representing image regions as a vocabulary of visual words to enable efficient object retrieval from video.
Criterion Online Writing Evaluation Service
Educational Testing Service launched the Criterion Online Writing Evaluation Service around 2003, a web-based tool that used natural language processing and machine learning to score student essays automatically, providing formative feedback intended to supplement instructor assessment.
Torch Machine Learning Library
In 2002, Ronan Collobert, Samy Bengio, and Johnny Mariéthoz at IDIAP Research Institute published a paper introducing Torch, a modular C++ and Lua-scriptable machine learning library that unified a range of algorithms, including support vector machines and neural networks, under a common object-oriented framework.
Sony AIBO Robot Dog Released
In May 1999, Sony Corporation released AIBO (Artificial Intelligence roBOt), model ERS-110, a consumer entertainment robot in the form of a dog. The robot used onboard processing and sensors to exhibit autonomous behaviour and express simulated emotional states, marking one of the first mass-market deployments of embodied AI behaviour.
Cleverbot Developed by Rollo Carpenter
Rollo Carpenter, a British AI developer, launched Cleverbot as a publicly accessible web application in 1997, extending his earlier Jabberwacky project. Cleverbot learned conversational responses directly from accumulated human inputs rather than from a hand-coded rule base, and went on to accumulate hundreds of millions of logged exchanges.
IBM TJ Watson Research Center Publishes Statistical Approach to Machine Translation
In August 1988, researchers at IBM Thomas J. Watson Research Center, including Peter F. Brown, John Cocke, Stephen A. Della Pietra, Vincent J. Della Pietra, Fredrick Jelinek, Robert L. Mercer, and Paul S. Roossin, presented a statistical framework for machine translation at COLING 1988, replacing rule-based linguistics with probabilistic models trained on bilingual text corpora.
SOAR Cognitive Architecture: Doctoral Dissertations by John E. Laird and Paul S. Rosenbloom, Supervised by Allen Newell
In 1983, John E. Laird and Paul S. Rosenbloom completed doctoral dissertations at Carnegie Mellon University under Allen Newell, introducing SOAR, a cognitive architecture designed to support a broad range of intelligent tasks through a unified problem-space model and a chunking-based learning mechanism.
Stanford Computer Forum Founded as Industry–Academia Bridge
In May 1968, Stanford professors Ed McCluskey, Arthur Samuel, and William Miller founded the Stanford Computer Forum, an industrial affiliates programme linking the university's electrical engineering and computer science research, including AI work, with corporate partners across Silicon Valley.