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Progress in artificial intelligence

Progress in artificial intelligence (AI) refers to the advances, milestones, and breakthroughs that have been achieved in the field of artificial intelligence over time. AI is a multidisciplinary branch of computer science that aims to create machines and systems capable of performing tasks that typically require human intelligence. Artificial intelligence applications have been used in a wide range of fields including medical diagnosis, economic-financial applications, robot control, law, scientific discovery, video games, and toys. However, many AI applications are not perceived as AI: "A lot of cutting edge AI has filtered into general applications, often without being called AI because once something becomes useful enough and common enough it's not labeled AI anymore."[1][2] "Many thousands of AI applications are deeply embedded in the infrastructure of every industry."[3] In the late 1990s and early 21st century, AI technology became widely used as elements of larger systems,[3][4] but the field was rarely credited for these successes at the time.

See also: History of artificial intelligence and Timeline of artificial intelligence

Kaplan and Haenlein structure artificial intelligence along three evolutionary stages: 1) artificial narrow intelligence – applying AI only to specific tasks; 2) artificial general intelligence – applying AI to several areas and able to autonomously solve problems they were never even designed for; and 3) artificial super intelligence – applying AI to any area capable of scientific creativity, social skills, and general wisdom.[2] The proposed nomenclature for these evolutionary stages is: 1) Protonoëtic; 2) Mesonoëtic; and 3) Kainonoëtic. According to this classification the whole epoch of biological intelligence would be termed the Prenoëtic.[5]


To allow comparison with human performance, artificial intelligence can be evaluated on constrained and well-defined problems. Such tests have been termed subject matter expert Turing tests. Also, smaller problems provide more achievable goals and there are an ever-increasing number of positive results.


Humans still substantially outperform both GPT-4 and models trained on the ConceptARC benchmark that scored 60% on most, and 77% on one category, while humans 91% on all and 97% on one category.[6]

optimal: it is not possible to perform better (note: some of these entries were solved by humans)

super-human: performs better than all humans

high-human: performs better than most humans

par-human: performs similarly to most humans

sub-human: performs worse than most humans

Exams[edit]

According to OpenAI, in 2023 ChatGPT GPT-4 scored the 90th percentile on the Uniform Bar Exam. On the SATs, GPT-4 scored the 89th percentile on math, and the 93rd percentile in Reading & Writing. On the GREs, it scored on the 54th percentile on the writing test, 88th percentile on the quantitative section, and 99th percentile on the verbal section. It scored in the 99th to 100th percentile on the 2020 USA Biology Olympiad semifinal exam. It scored a perfect "5" on several AP exams.[76]


Independent researchers found in 2023 that ChatGPT GPT-3.5 "performed at or near the passing threshold" for the three parts of the United States Medical Licensing Examination. GPT-3.5 was also assessed to attain a low, but passing, grade from exams for four law school courses at the University of Minnesota.[76] GPT-4 passed a text-based radiology board–style examination.[77][78]

Applications of artificial intelligence

List of artificial intelligence projects

List of emerging technologies

MIRI database of predictions about AGI