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AI boom
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An AI boom is a period of rapid growth in the field of artificial intelligence. The most recent boom happened in the 2020s before seeing increased acceleration and media coverage. Examples of this include generative AI technologies, such as large language models (LLM) and AI image generators developed by companies like OpenAI, Google, and Anthropic, as well as scientific advances, such as protein folding prediction led by Google DeepMind and Google AI. This period is sometimes referred to as an AI spring, a term used to differentiate it from previous AI winters. As of 2025, ChatGPT has emerged as the 4th-most visited website globally, surpassed only by Google, YouTube, and Facebook.
== History ==
In 1950, Alan Turing proposed the idea of "Thinking Machines". These were computers that would be able to reason at the same level as humans. He began his well-known "Turing test", where an interrogator is provided with two materials and they must determine which one was done by artificial intelligence and which one was done by a human being.
In 1956, John McCarthy used the term "artificial intelligence" for the first time. That year, McCarthy, Nathaniel Rochester, Marvin Minsky, and Claude Shannon organized the Dartmouth conference, which formalized artificial intelligence as an academic field. In 1958, McCarthy created the programming language LISP, LISP stands for "List Processing" and was the main programming language for artificial intelligence. which remained the most common programming language for artificial intelligence in the United States for decades. In 1962 McCarthy founded Stanford Artificial Intelligence Laboratory (SAIL). McCarthy was also a cofounder of MIT's first Artificial Intelligence Laboratory, now known as MIT Computer Science and Artificial Intelligence Laboratory.
In 1966, Joseph Weizenbaum created ELIZA, the first chatbot, as an experimental emotional tool.
The text-to-image models DALL-E 2 and Midjourney were released in 2022.
ChatGPT, an AI chatbot created by OpenAI, was launched at the end of 2022. It grew to over 100 million users in 2 months, becoming the fastest-growing software application. Large language models are designed to respond to human language, by accessing a large amount of training data.
== Advances ==
=== 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). The structural biologist and Nobel Prize winner Venki Ramakrishnan called the result "a stunning advance on the protein folding problem". 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.
=== Images and videos ===
As time passed, the power of generative AI grew stronger. In 2015, initial popularity began to grow with the release of Google's DeepDream. DeepDream is a generative AI that takes inputs from a previous image and morphs them to produce hallucinogenic images.
In January 2021, OpenAI released DALL-E, allowing for image generation through text prompts. This allows users to generate any image with a simple prompt. Soon after, other powerful models followed DALL-E, such as Google's Gemini.
The popularity of text-to-video generative AI tools grew exponentially. With the release of models such as OpenAI's Sora in 2024, the use of text-to-video tools became normalized, as people used them for advertisements, which saves on production costs and increases production speed.
Generative AI is growing at a rapid rate, outpacing modern-day detection tools. With the common public having access to these tools, it raises concerns about the ethical use of generative AI. There have been multiple occasions where misinformation has been spread over the internet about politics due to a generated or deep-faked video, posing as a security threat.
=== Language ===
GPT-3 is a large language model that was released in 2020 by OpenAI and is capable of generating human-like text. A new version called GPT-4 was released on 14 March 2023, and was used in the Microsoft Bing search engine. Other language models have been released, such as PaLM and Gemini by Google and LLaMA by Meta Platforms.
=== Software development ===
Generative coding can be used to produce, edit, explain, and debug code. A 2026 study in the journal Management Science found that less experienced developers have higher adoption rates and greater productivity gains.
=== Music and voice ===
In 2016, Google's DeepMind produced WaveNet. WaveNet allowed the generation of raw audio of speech and piano. WaveNet is able to generate different voices by identifying the speakers. This acted as a fundamental building block for future models, allowing audio to be formed from scratch. This wouldn't only help with the production of music, but voice generation as well.