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AI boom: the story on HearLore | HearLore
— Ch. 1 · Foundations And Early History —
AI boom.
~8 min read · Ch. 1 of 7
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, eventually being labeled as the father of artificial intelligence. That same year, the Dartmouth conference was held, organized by John McCarthy, Nathaniel Rochester, Marvin Minsky, and Claude Shannon. This conference is considered the birthplace of artificial intelligence as a field of study, as a workshop was held for 2 months. During this workshop, top researchers explored the concept of creating machines that could mimic the same intelligence as human beings. In 1958, John McCarthy created the programming language LISP. LISP stands for List Processing and works as the main programming language for artificial intelligence. The programming language gained traction at MIT, being used for many of their projects that dealt with AI, such as the IBM 704. While many languages rose and fell, LISP remained the most common programming language for artificial intelligence in the United States even in 2006. LISP became so reliable due to how artificial intelligence works. Artificial intelligence of the time often had lists that constantly change size, making fixed-length methods, such as vectors, unusable. In 1962, in order to continue research on artificial intelligence, John McCarthy founded Stanford Artificial Intelligence Laboratory. SAIL became an important hub for AI research, helping contribute many advancements in the field. Some of these advancements include robotics, medical diagnostics, natural language processing, autonomous vehicles, and more. John McCarthy was also a cofounder of MIT's first Artificial Intelligence Laboratory, now known as MIT Computer Science and Artificial Intelligence Laboratory.
When did Alan Turing propose the idea of Thinking Machines?
Alan Turing proposed the idea of Thinking Machines in 1950. This proposal included computers that would be able to reason at the same level as humans.
Who organized the Dartmouth conference in 1956?
John McCarthy, Nathaniel Rochester, Marvin Minsky, and Claude Shannon organized the Dartmouth conference in 1956. This event is considered the birthplace of artificial intelligence as a field of study.
What was the market capitalization of Nvidia on the 19th of June 2024?
The market capitalization of Nvidia rose to over US$3.3 trillion on the 19th of June 2024. This made it the world's largest company by market capitalization on that date.
Which reactor did Microsoft sign a deal with Constellation Energy to purchase power from in September 2024?
Microsoft signed a deal with Constellation Energy to purchase power from a reactor at Three Mile Island in September 2024. The reactor is set to reopen in 2028 to provide power to Microsoft's data centers.
When did Drake release the diss track Taylor Made Freestyle featuring AI-generated vocals?
Drake released the diss track Taylor Made Freestyle on the 19th of April 2024. The track featured AI-generated vocals imitating the voices of Tupac Shakur and Snoop Dogg.
ChatGPT, an AI chatbot created by OpenAI, was launched at the end of 2022. It grew to over 100 million users in only 2 months, becoming the fastest-growing software application. As of 2025, ChatGPT remains the 4th-most visited website, behind sites such as Google and Facebook. Other chatbots such as Gemini, Claude, and Copilot fall under the same category, known as large language models. Large language models are designed to be capable of responding appropriately to human language as well as being able to conduct a wide range of tasks. They do this by feeding the models an immense amount of data in order to produce acceptable responses. Present day chatbots incorporate generative AI, including AI image generation. Over half of American adults who responded to a 2025 survey stated they had used an LLM at least once. 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 utilized them for advertisements, which saves on production costs and increases production speed.
Biomedical Breakthroughs
In 2020, DeepMind's AlphaFold program, which is designed to predict protein folding, scored more than 90 in CASP's Global distance test. 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. 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. Following in the footsteps of WaveNet, OpenAI released Jukebox, the first large-scale model to generate songs. Jukebox allowed for raw audio in different genres and styles, showing that AI had the power to generate complex audio. Google published MusicLM, allowing users to generate raw audio through text prompts. The model can also create full songs with only a hummed melody and text. This marked a leap as music generation tools became more accessible to the public.
Economic Disruption And Growth
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 the 19th of June 2024 and became the first company to reach US$4 trillion on the 9th of July 2025 and subsequently US$5 trillion on the 29th of October 2025, 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. Machine learning resources, hardware or software can be bought and licensed off-the-shelf or as cloud platform services. This enables wide and publicly available uses, spreading AI skills. Over half of businesses consider AI to be a top organizational priority and to be the most crucial technological advancement in many decades. Across industries, generative AI tools are becoming widely available through the AI boom and are increasingly used in businesses across regions. A main area of use is data analytics. Seen as an incremental change, machine learning improves industry performance. Businesses report AI to be most useful in increased process efficiency, improved decision-making and strengthening of existing services and products. 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.
Energy Consumption And Environment
A large amount of electricity is needed to power generative AI products, making it more difficult for companies to achieve net zero emissions. From 2019 to 2024, Google's greenhouse gas emissions increased by nearly 50%, partly as a result of increased energy consumption by AI data centres. 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. Microsoft, Google, and Amazon have all invested in existing or proposed nuclear power plants to meet these demands. 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.
Ethical Risks And Misinformation
On the 19th of April 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. Shakur's estate threatened to sue over the use of Shakur's likeness, saying that it constituted a violation of Shakur's personality rights. On the 20th of May 2024, following the release of a demo of updates to OpenAI's ChatGPT Voice Mode feature a week earlier, actor Scarlett Johansson issued a statement 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. 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. Canada introduced federal legislation targeting sharing of non-consensual sexually explicit AI-generated photos; most provinces already had such laws. In the United States, the DEFIANCE Act was introduced in March 2024.
Geopolitical Power Dynamics
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. These companies own the majority of cloud infrastructure, AI chips, and computing power from data centers. In 2024, AI patents in China and the U.S. numbered more than three-fourths of AI patents worldwide. Though China had more AI patents, the U.S. had 35% more patents per AI patent-applicant company than China. The market capitalization of Nvidia rose to over US$3.3 trillion, making it the world's largest company by market capitalization as of the 19th of June 2024. 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. 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. Despite more than $60 billion in corporate investment in AI in 2025, 95% of business AI projects are unprofitable, according to research from MIT.