AI milestones of the 2020s
18 documented milestones spanning 2020 to 2021. Mostly capability and method entries.
UMass Amherst researchers demonstrate protein-nanowire memristors for neuromorphic computing
In June 2021, researchers at the University of Massachusetts Amherst published findings in Nature Communications showing that protein nanowires harvested from the bacterium Geobacter sulfurreducens can function as memristors, enabling brain-inspired computation at ultralow power without a conventional battery.
Compute and infrastructureBrainGate 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.
Prosthetics and assistive technologyCornell University researchers demonstrate electrically actuated microscale origami robots with onboard CMOS control
On 17 March 2021, researchers at Cornell University published a demonstration of self-folding microscale robots, roughly 100–250 microns in size, driven by platinum-based shape-memory actuators and controlled by onboard complementary metal-oxide-semiconductor (CMOS) circuits, enabling untethered, electrically commanded origami-style locomotion at the micron scale.
Manipulation and dexterityReinforcement learning framework proposed to model T-cell adaptive immune response
In 2021, researchers published in Physical Review Research a theoretical framework proposing that T-cell receptor signalling during adaptive immunity can be formally described as a reinforcement learning process, connecting immunological learning to established machine-learning theory.
BiologyGoogle Announces TPU v4 Tensor Processing Unit
Google announced its fourth-generation Tensor Processing Unit (TPU v4) at Google I/O in 2021. The chip, designed specifically for large-scale machine-learning workloads, offered substantially higher performance than its predecessor and was made available to researchers via Google Cloud.
Compute and infrastructureCavatappi Artificial Muscles from Drawing, Twisting, and Coiling Polymer Tubes
In 2021, researchers led by Tzu-Ching Shyu at the University of Illinois at Urbana-Champaign published findings in Science Robotics describing cavatappi artificial muscles, twisted polymer actuators made from polyethylene-based tubes, capable of contracting up to 45% of their length, lifting approximately 300 times their weight per unit volume, and actuating within 23 milliseconds per 1% length change.
Manipulation and dexterityPneumatic-logic soft robot without electronic components, University of California San Diego, 2021
In 2021, Michael T. Tolley and colleagues at the University of California San Diego published a soft walking robot controlled entirely by pneumatic logic circuits embedded in its body, with no electronic components, demonstrating autonomous gait and environmental responsiveness through fluidic computation alone.
Manipulation and dexteritySwinburne University of Technology Researchers Demonstrate Optical Neuromorphic Processor Using Micro-Comb Photonic Chip
In January 2021, a Swinburne University of Technology-led international team published results in Nature demonstrating an optical neuromorphic processor built on a photonic micro-comb chip, achieving a processing speed of 10 TOPS from a single integrated device and performing image classification tasks at high speed.
Compute and infrastructureMilad 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.
ChemistrySoft Robotic Gripper Modelled on Pole Bean Tendrils Developed at University of Georgia
In December 2020, researchers at the University of Georgia developed a soft robotic gripper modelled on the twining behaviour of pole bean tendrils. The 3-inch device uses a single pneumatic actuator and an embedded fibre-optic sensor to grasp objects as small as 1 millimetre in diameter and characterise surface properties during contact.
Manipulation and dexterityDeepMind'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.
BiologyWaymo One Launches Fully Driverless Rides to the General Public in Phoenix, Arizona
On 8 October 2020, Waymo opened its Waymo One ride-hailing service to the general public in the greater Phoenix, Arizona area, operating without a safety driver in the vehicle, the first time a commercial autonomous vehicle service had done so at public scale.
Autonomous vehiclesCURIAL: 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%.
DiagnosisOpenAI released GPT-3 via private beta API
In May–June 2020, OpenAI published the GPT-3 language model in a paper by Tom B. Brown and colleagues, and began distributing private beta API access. GPT-3's 175 billion parameters made it substantially larger than any publicly described language model at the time, enabling strong few-shot performance across diverse language tasks.
Architectures and modelsOnce-for-All: Train One Network and Specialize It for Efficient Deployment
Han Cai, Chuang Gan, Tianhao Chen, and Song Han at MIT published Once-for-All at ICLR 2020, presenting a method to train a single neural network once and then derive specialised sub-networks for diverse hardware platforms without retraining, reducing the computational cost of neural architecture search by orders of magnitude.
Architectures and modelsMIT 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.
Drug discoveryMicrosoft 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.
Language understandingFacebook AI Research Publishes GrokNet, a Unified Computer Vision Model for Commerce Understanding
In 2020, researchers at Facebook AI published GrokNet, a unified deep learning system for product understanding in commerce settings, capable of recognising object categories, attributes such as colour and material, and brand information from product images at scale across Facebook Shops.
Retail and commerce