AI boom

From HandWiki
Short description: Ongoing period of rapid progress in AI

American news magazine Time cover featuring a ChatGPT conversation; mechanical dove image created in Midjourney
Artificial intelligence
Major goals
Approaches
Philosophy
History
Technology
Glossary

An AI boom[1][2] is a period of rapid growth in the field of artificial intelligence (AI). The current boom is an ongoing period that originally started from 2010 to 2016,[3] but saw increased acceleration in the 2020s. Examples include generative AI technologies, such as large language models and AI image generators by companies like OpenAI, as well as scientific advances, such as protein folding prediction led by Google DeepMind. This period is sometimes referred to as an AI spring, to contrast it with previous AI winters.[4][5] As of 2025, ChatGPT is the 5th most visited website globally behind Google, YouTube, Facebook, and Instagram.[6][7]

History

For broader coverage of this topic, see History of artificial intelligence.
The number of Google searches for the term "AI" accelerated in 2022.

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. The event catalyzed the AI boom later that decade, when many alumni of the ImageNet challenge became leaders in the tech industry.[8][9] In March 2016, AlphaGo beat Lee Sedol in a five-game match,[10] marking the first time a computer Go program had beaten a 9-dan professional without handicap. This match led to an increase in public interest in AI.[citation needed] The generative AI race began in 2016 or 2017 following the founding of OpenAI and advances made in graphics processing units (GPUs), the amount and quality of training data, generative adversarial networks, diffusion models and transformer architectures.[11] In 2018, the AI Index, an initiative organized by Stanford University, reported an acceleration of research and commercial services using AI. Europe published the largest number of papers in the field that year, followed by China and North America.[12] Technologies such as AlphaFold led to more accurate predictions of protein folding and may improve the process of drug development.[13] Economists and lawmakers began to discuss the potential impact of AI more frequently.[14][15]

ChatGPT, a chatbot based on a large language model created by OpenAI, was released in November 2022.[16] ChatGPT had over 100 million users in two months, and according to investment bank UBS, was the fastest-growing consumer software application in history.[17][18] Several other companies have released competitors. At a similar time, text-to-image-models such as DALL-E and Midjourney become popular as a way to generate complicated photo-like illustrations.[19] Speech synthesis software also became able to replicate the voices and speech of specific people.[20]

Advances

See also: Progress in artificial intelligence

Biomedical

In 2020, DeepMind's AlphaFold program, which is designed to predict protein folding, scored more than 90 in CASP's Global distance test (GDT).[21][22] The structural biologist and Nobel Prize winner Venki Ramakrishnan called the result "a stunning advance on the protein folding problem".[21] The ability to predict protein structures accurately based on the constituent amino acid sequence may accelerate drug discovery and enable a better understanding of diseases.[22][23][24]

Images and videos

An image generated by Stable Diffusion based on the text prompt "a photograph of an astronaut riding a horse"

AI modified images started to be widely circulated on the internet following the public release of Google's DeepDream in 2015.[25]

OpenAI released DALL-E, a model capable of generating relatively crude images based on text descriptions, in January 2021.[26] A successor capable of generating more complex and realistic images, DALL-E 2, was released in April 2022.[27] Notable examples of other text-to-image models include NovelAI in 2021, and Midjourney and Stable Diffusion, both released in 2022.[28][29]

Examples of text-to-video platforms include Runway's Gen-1 model released in February 2023,[30] and by OpenAI's Sora in December 2024.[original research?]

Language

GPT-3 is a large language model that was released in 2020 by OpenAI and is capable of generating human-like text.[31][32] A new version called GPT-4 was released on March 14, 2023, and was used in the Microsoft Bing search engine.[33][34] Other language models have been released, such as PaLM and Gemini by Google[35] and LLaMA by Meta Platforms.

Music and voice

In 2016, Google DeepMind unveiled WaveNet, a deep learning network that produced English, Mandarin, and piano music.[36] WaveNet demonstrated that deep learning models are capable of modeling raw waveforms and generating speech from acoustic features like spectrograms or mel-spectrograms, starting the field of deep learning speech synthesis.[37] This was followed by Google AI's Tacotron 2 in 2018, which demonstrated that neural networks could produce highly natural speech synthesis but required substantial training data—typically tens of hours of audio—to achieve acceptable quality. When trained on smaller datasets, such as 2 hours of speech, the output quality degraded while still being able to maintain intelligible speech, and with just 24 minutes of training data, Tacotron 2 failed to produce intelligible speech.[38]

15.ai, a free text-to-speech web application launched in March 2020, was an early development in the AI boom that used AI for voice synthesis. The platform could generate convincing character voices using as little as 15 seconds of training data.[39] The application gained widespread international attention in early 2021 for its ability to synthesize emotionally expressive speech of fictional characters from popular media.[40][41][42] 15.ai is credited with popularizing AI voice cloning in memes and content creation.[43][44]

ElevenLabs allowed users to upload voice samples and create audio that sounds similar to the samples. The company was criticized[45] after controversial[46][47] statements were generated based on the vocal styles of celebrities, public officials, and other famous individuals,[48] raising concerns that the technology could make deepfakes even more convincing.[49] An unofficial song known as "Heart on My Sleeve", created using the voices of musicians Drake and The Weeknd raised questions about the ethics and legality of similar software.[50]

Impact

Energy

Electricity consumed by hardware used for AI has increased demands on power grids, which has led to prolonged use of fossil fuel power plants which would otherwise have been deactivated.[51][52][53]

Microsoft, Google, and Amazon have all invested in existing or proposed nuclear power plants to meet these demands.[54][55] In September 2024, Microsoft signed a deal with Constellation Energy to purchase power from a reactor at Three Mile Island which had been shut down in 2019. The reactor is set to reopen in 2028 to provide power to Microsoft's data centers. The reactor is next to the unit which caused the worst nuclear power accident in US history in 1979.[56][57][58]

Cultural

During the AI boom, different groups emerged, ranging from the ones that want to accelerate AI development as quickly as possible to those that are more concerned about AI safety and would like to "decelerate".[59] According to a survey published in April 2025 by Pew Research Center, 43% of American adults thought that AI technology was more likely to harm themselves in the future, while 24% thought that AI was more likely to benefit themselves in the future. Women were more likely than men to be concerned about AI technology.[60]

Business and economy

In 2024, AI patents in China and the U.S. numbered more than three-fourths of AI patents worldwide.[61] Though China had more AI patents, the U.S. had 35% more patents per AI patent-applicant company than China.[61]

Some economists have been optimistic about the potential of the current wave of AI to boost productivity and economic growth. Notably, Stanford University economist Erik Brynjolfsson, in a series of articles has argued for an "AI-powered Productivity Boom"[62] and a "Coming Productivity Boom".[63] At the same time, others like Northwestern University economist Robert Gordon remain more pessimistic.[64] Brynjolfsson and Gordon have made a formal bet, registered at long bets, about the rate of productivity growth in the 2020s, to be resolved at the end of the decade.[65]

Big Tech companies view the AI boom as both opportunity and threat; Alphabet's Google, for example, realized that ChatGPT could be an innovator's dilemma-like replacement for Google Search. The company merged DeepMind and Google Brain, a rival internal unit, to accelerate its AI research.[66]

The market capitalization of Nvidia, whose GPUs are in high demand to train and use generative AI models, rose to over US$3.3 trillion, making it the world's largest company by market capitalization as of June 19, 2024[67] and became the first company to reach US$4 trillion on July 9, 2025[68] and subsequently US$5 trillion on October 29, 2025,[69] just under 112 days later.

In 2023, San Francisco's population increased for the first time in years, with the boom cited as a contributing factor.[70]

Machine learning resources, hardware or software can be bought and licensed off-the-shelf or as cloud platform services.[71] This enables wide and publicly available uses, spreading AI skills.[71] Over half of businesses consider AI to be a top organizational priority and to be the most crucial technological advancement in many decades.[72]

Across industries, generative AI tools are becoming widely available through the AI boom and are increasingly used in businesses across regions.[73] A main area of use is data analytics. Seen as an incremental change, machine learning improves industry performance.[74] Businesses report AI to be most useful in increased process efficiency, improved decision-making and strengthening of existing services and products.[75] Through adoption, AI has already positively influenced revenue generation in multiple business functions. Businesses have experienced revenue increases of up to 16%, mainly in manufacturing, risk management and research and development.[73]

AI and generative AI investments have been increasing with the boom, increasing from $18 billion in 2014 to $119 billion in 2021. Most notably, the share of generative AI investments was around 30% in 2023.[76] Further, generative AI businesses have seen considerable venture capital investments even though regulatory and economic outlooks remain in question.[77]

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.[78][79]

Concerns

See also: Artificial intelligence controversies

Inaccuracy, cybersecurity and intellectual property infringement are considered to be the main risks associated with the boom, although not many actively attempt to mitigate the risk.[73] Large language models have been criticized for reproducing biases inherited from their training data, including discriminatory biases related to ethnicity or gender.[80] As a dual-use technology, AI carries risks of misuse by malicious actors.[81] 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.[82][14] Public reaction to the AI boom has been mixed, with some hailing the new possibilities that AI creates, its sophistication and potential for benefiting humanity;[83][84] while others denounced it for threatening job security[85][86] and for giving 'uncanny' or flawed responses.[87]

Dominance by tech giants

Commercial AI 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.[88][89][90] These companies own the majority of cloud infrastructure, AI chips, and computing power from data centers.[91][92]

Intellectual property

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.[93][94] 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. ChatGPT aroused suspicion that its sources included libraries of pirated content after the chatbot produced detailed summaries of every part of Sarah Silverman's The Bedwetter and verbatim excerpts of paywalled content from The New York Times.[95][96] In protest of the UK government holding consultations on how copyrighted music can legally be used to train AI models,[97] more than a thousand British musicians released an album with no sounds, entitled Is This What We Want?[98]

Likeness and impersonation

See also: Deepfake

File:California attempts to regulate election deepfakes.webm

The ability to generate convincing, personalized messages as well as realistic images may facilitate large-scale misinformation, manipulation, and propaganda.[99]

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 featured AI-generated vocals imitating the voices of Tupac Shakur and Snoop Dogg.[100] Shakur's estate threatened to sue over the use of Shakur's likeness,[101] saying that it constituted a violation of Shakur's personality rights.

On May 20, 2024, following the release of a demo of updates to OpenAI's ChatGPT Voice Mode feature a week earlier,[102][103] actor Scarlett Johansson issued a statement[104][105] in relation to the "Sky" voice shown in the demo, accusing OpenAI of producing it to be very similar to her own, and her portrayal of the artificial intelligence voice assistant Samantha in the film Her (2013), despite Johansson refusing an earlier offer from the company to provide her voice for the system. The agent of the unnamed voice actress who voiced Sky stated that she had recorded her lines in her natural speaking voice and that OpenAI had not mentioned the movie Her nor Johansson.[106][107]

Several incidents involving sharing of non-consensual deepfake pornography have occurred. In late January 2024, deepfake images of American musician Taylor Swift proliferated. Several experts have warned that deepfake pornography is more quickly created and disseminated, due to the relative ease of using the technology.[108] Canada introduced federal legislation targeting sharing of non-consensual sexually explicit AI-generated photos; most provinces already had such laws.[109] In the United States, the DEFIANCE Act was introduced in March 2024.[110]

Environment

Main article: Environmental impact of artificial intelligence

A large amount of electricity is needed to power generative AI products,[111] making it more difficult for companies to achieve net zero emissions. From 2019 to 2024, Google's greenhouse gas emissions increased by 50%.[112]

Biosecurity and cybersecurity

AI is expected by researchers of the Center for AI Safety to improve the "accessibility, success rate, scale, speed, stealth and potency of cyberattacks", potentially causing "significant geopolitical turbulence" if it reinforces attack more than defense.[81][113] Concerns have been raised about the potential capability of future AI systems to engineer particularly lethal and contagious pathogens.[114][115]

The AI boom is said to have started an arms race in which large companies are competing against each other to have the most powerful AI model on the market, with speed and profit prioritized over safety and user protection.[116][117][118]

Sentience and human extinction

Coverage of advances in machine learning and artificial intelligence have coincided with discussions of digital sentience and morality,[119] such as whether A.I. programs should be granted rights.[120]

Industry leaders and others have signed the Statement on AI Risk, arguing that humanity might irreversibly lose control over a sufficiently advanced artificial general intelligence (AGI).[121][122]

Financial concerns and potential bubble

Much of the AI boom has been funded by loans and venture capital, but many commercial AI services remain of questionable practical utility or quality for business.[123] Despite more than $60 billion in corporate investment in AI in 2025,[124] 95% of business AI projects are unprofitable, according to research from MIT.[125] Producers of generative AI, such as OpenAI, also themselves currently have costs greatly exceeding their revenue.[126] As other major tech companies such as Nvidia are both heavily invested into AI and dependent on the AI ecosystem and its hardware demands for their own ongoing growth,[123][125] this has raised speculation of a wider economic bubble in the tech industry.[127][128][129]

See also

References

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  2. ↑ Meredith, Sam (2023-12-06). "A 'thirsty' generative AI boom poses a growing problem for Big Tech". https://www.cnbc.com/2023/12/06/water-why-a-thirsty-generative-ai-boom-poses-a-problem-for-big-tech.html. 
  3. ↑ Zysman, John; Nitzberg, Mark (August 2020). "Governing AI: Understanding the Limits, Possibility, and Risks of AI in an Era of Intelligent Tools and Systems". https://brie.berkeley.edu/sites/default/files/brie_working_paper_2020-5_825.pdf. 
  4. ↑ Bommasani, Rishi (March 17, 2023). "AI Spring? Four Takeaways from Major Releases in Foundation Models". Stanford Institute for Human-Centered Artificial Intelligence. https://hai.stanford.edu/news/ai-spring-four-takeaways-major-releases-foundation-models. 
  5. ↑ "The coming of AI Spring". https://www.mckinsey.com/mgi/overview/in-the-news/the-coming-of-ai-spring. 
  6. ↑ "Most Visited Websites in Worldwide 2025 | Trending Websites" (in en). https://www.semrush.com/trending-websites/global/all. 
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  8. ↑ "The data that transformed AI research—and possibly the world". 26 July 2017. https://qz.com/1034972/the-data-that-changed-the-direction-of-ai-research-and-possibly-the-world. 
  9. ↑ Lohr, Steve (30 November 2017). "A.I. Will Transform the Economy. But How Much, and How Soon?". The New York Times. https://www.nytimes.com/2017/11/30/technology/ai-will-transform-the-economy-but-how-much-and-how-soon.html. 
  10. ↑ "Match 1 – Google DeepMind Challenge Match: Lee Sedol vs AlphaGo". 8 March 2016. https://www.youtube.com/watch?v=vFr3K2DORc8&t=1h57m. 
  11. ↑ Aaronson, Scott (2023-03-06). "Why am I not terrified of AI?". https://scottaaronson.blog/?p=7064. 
  12. ↑ Statt, Nick (12 December 2018). "The AI boom is happening all over the world, and it's accelerating quickly". https://www.theverge.com/2018/12/12/18136929/artificial-intelligence-ai-index-report-2018-machine-learning-global-progress-research. 
  13. ↑ Wong, Matteo (2023-12-11). "Science Is Becoming Less Human". https://www.theatlantic.com/technology/archive/2023/12/ai-scientific-research/676304/. 
  14. ↑ 14.0 14.1 Lohr, Steve (30 November 2017). "A.I. Will Transform the Economy. But How Much, and How Soon?". The New York Times. https://www.nytimes.com/2017/11/30/technology/ai-will-transform-the-economy-but-how-much-and-how-soon.html. 
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  18. ↑ "ChatGPT sets record for fastest-growing user base - analyst note" (in en-US). Reuters. https://www.reuters.com/technology/chatgpt-sets-record-fastest-growing-user-base-analyst-note-2023-02-01/. 
  19. ↑ Vincent, James (2022-05-24). "All these images were generated by Google's latest text-to-image AI". https://www.theverge.com/2022/5/24/23139297/google-imagen-text-to-image-ai-system-examples-paper. 
  20. ↑ Cox, Joseph (January 31, 2023). "AI-Generated Voice Firm Clamps Down After 4chan Makes Celebrity Voices for Abuse". https://www.vice.com/en/article/ai-voice-firm-4chan-celebrity-voices-emma-watson-joe-rogan-elevenlabs/. 
  21. ↑ 21.0 21.1 Service, Robert F. (30 November 2020). "'The game has changed.' AI triumphs at solving protein structures" (in en). www.science.org. https://www.science.org/content/article/game-has-changed-ai-triumphs-solving-protein-structures. 
  22. ↑ 22.0 22.1 Callaway, Ewen (2020-11-30). "'It will change everything': DeepMind's AI makes gigantic leap in solving protein structures". Nature 588 (7837): 203–204. doi:10.1038/d41586-020-03348-4. PMID 33257889. Bibcode: 2020Natur.588..203C. 
  23. ↑ Hubbard, Tim (2020-12-07). "The secret of life, part 2: the solution of the protein folding problem.". https://timjph.medium.com/the-secret-of-life-part-2-the-solution-of-the-protein-folding-problem-c544f3a77ee3. 
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  26. ↑ Coldewey, Devin (2021-01-05). "OpenAI's DALL-E creates plausible images of literally anything you ask it to". https://techcrunch.com/2021/01/05/openais-dall-e-creates-plausible-images-of-literally-anything-you-ask-it-to/. 
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  28. ↑ Pandey, Mohit (2023-07-22). "One Year of Midjourney: A Psychedelic Image Generator to Realistic Photo Album". https://analyticsindiamag.com/one-year-of-midjourney-a-psychedelic-image-generator-to-realistic-photo-album/. 
  29. ↑ "Stable Diffusion Public Release". https://stability.ai/blog/stable-diffusion-public-release. 
  30. ↑ Edwards, Benj (9 September 2022). "Runway teases AI-powered text-to-video editing using written prompts". Ars Technica. https://arstechnica.com/information-technology/2022/09/runway-teases-ai-powered-text-to-video-editing-using-written-prompts/. 
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  38. ↑ "Audio samples from "Semi-Supervised Training for Improving Data Efficiency in End-to-End Speech Synthesis"". 2018-08-30. https://google.github.io/tacotron/publications/semisupervised/index.html. 
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  40. ↑ Kurosawa, Yuki (January 19, 2021). "ゲームキャラ音声読み上げソフト「15.ai」公開中。『Undertale』や『Portal』のキャラに好きなセリフを言ってもらえる" (in ja). https://automaton-media.com/articles/newsjp/20210119-149494/. 
  41. ↑ 遊戲, 遊戲角落 (January 20, 2021). "這個AI語音可以模仿《傳送門》GLaDOS講出任何對白！連《Undertale》都可以學" (in zh-tw). https://game.udn.com/game/story/10453/5189551. 
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  51. ↑ Auslender, Viki; Ashkenazi, Shani (23 April 2023). "The environmental pollution behind the boom in artificial intelligence". ctech (Calcalist). https://www.calcalistech.com/ctechnews/article/ryjytypf2. 
  52. ↑ Harrison Dupré, Maggie (31 May 2024). "Huge Power Demand for AI Is Keeping Polluting Coal Plants Alive". Futurism. https://futurism.com/the-byte/ai-polluting-coal-plants-alive. 
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  54. ↑ da Silva, João. "Google turns to nuclear to power AI data centres". BBC.com (14 October 2024). https://www.bbc.com/news/articles/c748gn94k95o. 
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