Ongoing period of rapid progress in artificial intelligence
From top, left to right: Time Magazine cover featuring a ChatGPT conversation; mechanical dove image created in Midjourney; AlphaFold 2 performance, experiments, and architecture.
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.[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. This match led to significant increase in public interest in AI.[7] The generative AI race began in earnest in 2016 or 2017 following the founding of OpenAI and earlier advances made in graphical processing units (GPUs), the amount and quality of training data, generative adversarial networks, diffusion models and transformer architectures.[8][9] In 2018, the Artificial Intelligence Index, an initiative from Stanford University, reported a global explosion of commercial and research efforts in AI. Europe published the largest number of papers in the field that year, followed by China and North America.[10] Technologies such as AlphaFold led to more accurate predictions of protein folding and improved the process of drug development.[11] Economists and lawmakers began to discuss the potential impact of AI more frequently.[12][13] By 2022, large language models (LLMs) saw increased usage in chatbot applications; text-to-image-models could generate images that appeared to be human-made;[14] and speech synthesis software was able to replicate human speech efficiently.[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.[16][17] Scientists who have immigrated to the U.S. play an outsized role in the country's development of AI technology.[18][19] Many of them were educated in China, prompting debates about national security concerns amid worsening relations between the two countries.[20]
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.[26][29][30] It went on to note that the AI algorithm could "predict the shape of proteins to within the width of an atom."[30]
Images and videos
Text-to-image models captured widespread public attention when OpenAI announced DALL-E, a transformer system, in January 2021.[31] A successor capable of generating complex and realistic images, DALL-E 2, was unveiled in April 2022.[32] An alternative text-to-image model, Midjourney, was released in July 2022.[33] Another alternative, open-source model Stable Diffusion, released in August 2022.[34]
GPT-3 is a large language model that was released in 2020 by OpenAI and is capable of generating high-quality human-like text.[41] The tool has been credited with spurring and accelerating the A.I. boom following its release.[42][43][44] An upgraded version called GPT-3.5 was used in ChatGPT, which later garnered attention for its detailed responses and articulate answers across many domains of knowledge.[45] A new version called GPT-4 was released on March 14, 2023, and was used in the Microsoft Bing search engine.[46][47] Other language models have been released, such as PaLM and Gemini by Google and LLaMA by Meta Platforms.
In January 2023, DeepL Write, an AI-based tool to improve monolingual texts, was released.[48] In December 2023, Gemini, the latest model by Google, was unveiled, claiming to beat previous state-of-the-art-model GPT-4 on most benchmarks.[49]
In 2020, the non-commercial freeware artificial intelligence web application 15.ai was released.[51][52] 15.ai is credited with popularizing AI voice cloning in content creation,[53][54][55] being the first publicly available AI vocal synthesis application and having had a significant impact in multiple Internet fandoms, most notably the My Little Pony: Friendship Is Magic and Team Fortress 2 fandoms.[56][57]
ElevenLabs allowed users to upload voice samples and create audio that sounds similar to the samples. The company was criticized[by whom?] after controversial[among whom?] statements were generated based on the vocal styles of celebrities, public officials, and other famous individuals,[58] raising concerns[among whom?] that the technology could make deepfakes even more convincing.[59] An unofficial song created using the voices of musicians Drake and The Weeknd raised questions[among whom?] about the ethics and legality of similar software.[60]
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".[70]
Business and economy
Big tech viewed 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.[71]
In 2023, San Francisco's population increased for the first time in years, with the boom cited as a contributing factor.[73]
Machine learning resources, hardware or software can be bought and licensed off-the-shelf or as cloud platform services.[74] This enables wide and publicly available uses, spreading AI skills.[75] Over half of businesses consider AI to be a top organizational priority and to be the most crucial technological advancement in many decades.[76]
Across industries, generative AI tools are becoming widely available through the AI boom and are increasingly used in businesses across regions.[77] A main area of use is data analytics. Seen as an incremental change, machine learning improves industry performance.[78] Businesses report AI to be most useful in increased process efficiency, improved decision-making and strengthening of existing services and products.[79] 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.[80]
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.[81] Further, generative AI businesses have seen considerable venture capital investments even though regulatory and economic outlooks remain in question.[82]
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.[83][84]
Concerns
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.[85] Large language models have been criticized for reproducing biases inherited from their training data, including discriminatory biases related to ethnicity or gender.[86] As a dual-use technology, AI carries risks of misuse by malicious actors.[87] 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.[88][12] 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;[89][90] while others denounced it for threatening job security[91][92] and for giving 'uncanny' or flawed responses.[93]
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.[100][101] 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.[102][103]
The ability to generate convincing, personalized messages as well as realistic images may facilitate large-scale misinformation, manipulation, and propaganda.[104]
On May 20, 2024, following the release of a demo of updates to OpenAI's ChatGPT Voice Mode feature a week earlier,[107][108] actor Scarlett Johansson issued a statement[109][110] 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 unnamed voice actress who voiced Sky has stated she was coached to sound like Johansson, and used her natural speaking voice.[111]
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.[112] Canada introduced federal legislation targeting sharing of non-consensual sexually explicit AI-generated photos; most provinces already had such laws.[113] In the United States, the DEFIANCE Act was introduced in March 2024.[114]
Environment
A large amount of electricity is needed to power generative AI products,[115] making it more difficult for companies to achieve net zero emissions. From 2019 to 2024, Google's greenhouse gas emissions increased by 50%.[116]
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.[87][117] Concerns have been raised about the potential capability of future AI systems to engineer particularly lethal and contagious pathogens.[118][119]
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.[120][121][122]
Rapid progress in artificial intelligence has also sparked interest in whether some future AI systems will be sentient or otherwise worthy of moral consideration,[123] and whether they should be granted rights.[124]
^VK, Anirudh (March 18, 2023). "Deepfakes Are Elevating Meme Culture, But At What Cost?". Analytics India Magazine. Retrieved December 18, 2024. While AI voice memes have been around in some form since '15.ai' launched in 2020, [...]
^Davenport & Harris, Thomas & Jeanne (August 29, 2017). Competing on analytics. Harvard Business Press. ISBN978-1633693739.{{cite book}}: CS1 maint: date and year (link)
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