Examples include large language models and generative AI applications developed by OpenAI as well as protein folding prediction led by Google DeepMind.
[3][4] In 2012, a University of Toronto research team used artificial neural networks and deep learning techniques to lower the error rate below 25% for the first time during the ImageNet challenge for object recognition in computer vision.
[5][6] In March 2016, AlphaGo beat Lee Sedol in a five-game match, marking the first time a computer Go program had beaten a 9-dan professional without handicap.
[8][9] In 2018, the Artificial Intelligence Index, an initiative from Stanford University, reported a global explosion of commercial and research efforts in AI.
[15] According to metrics from 2017 to 2021, the United States outranks the rest of the world in terms of venture capital funding, the number of startups, and patents granted in AI.
[22][23] In 2023, an analyst at the Center for Strategic and International Studies advocated for the U.S. to use its dominance in AI technology to drive its foreign policy instead of relying on trade agreements.
[25] Nobel Prize winner and structural biologist Venki Ramakrishnan called the result "a stunning advance on the protein folding problem",[24] adding that "It has occurred decades before many people in the field would have predicted.
"[26][27] The ability to predict protein structures accurately based on the constituent amino acid sequence is expected to accelerate drug discovery and enable a better understanding of diseases.
[50] The application gained widespread attention in early 2021 for its ability to synthesize emotionally expressive speech from popular fictional characters,[51][52] becoming particularly influential in online content creation.
[83] Tech giants capture the bulk of the monetary gains from AI and act as major suppliers to or customers of private users and other businesses.
[88] As AI becomes more sophisticated, it may eventually become cheaper and more efficient than human workers, which could cause technological unemployment and a transition period of economic turmoil.
[94] The commercial AI scene is dominated by American Big Tech companies such as Alphabet Inc., Amazon, Apple Inc., Meta Platforms, and Microsoft, whose investments in this area have surpassed those from U.S.-based venture capitalists.
[95][96][97] Some of these players already own the vast majority of existing cloud infrastructure, AI chips, and computing power from data centers, allowing them to entrench further in the marketplace.
[100] Tech companies such as Meta, OpenAI and Nvidia have been sued by artists, writers, journalists, and software developers for using their work to train AI models.
[101][102] Early generative AI chatbots, such as the GPT-1, used the BookCorpus, and books are still the best source of training data for producing high-quality language models.
[105] On April 19, 2024, as part of an ongoing feud with fellow rapper Kendrick Lamar, the artist Drake released the diss track Taylor Made Freestyle, which feature generated vocals imitating the voices of Tupac Shakur and Snoop Dogg.
[113] Canada introduced federal legislation targeting sharing of non-consensual sexually explicit AI-generated photos; most provinces already had such laws.
[115] A large amount of electricity is needed to power generative AI products,[116] making it more difficult for companies to achieve net zero emissions.
[121][122][123] Rapid progress in artificial intelligence has also sparked interest in whether some future AI systems will be sentient or otherwise worthy of moral consideration,[124] and whether they should be granted rights.
[125] Industry leaders have further warned in the statement on AI risk of extinction that humanity might irreversibly lose control over a sufficiently advanced artificial general intelligence.