OpenAI: The Beginning of the AI Era

These days, it’s hard to avoid OpenAI. Helping people write emails, brainstorm business ideas, explain math problems, or even draft bedtime stories, ChatGPT is everywhere. It’s built into Microsoft Office, GitHub, and Windows. Its image and code tools have gone viral more than once, and the company is valued in the tens of billions. In less than a decade, OpenAI has gone from a name only AI researchers knew to a brand millions of people use every day. But it didn’t start as a global tech heavyweight. Back in 2015, OpenAI was just a small group of idealists in San Francisco with a simple but audacious belief: if artificial intelligence was going to change the world, it should change it for everyone—not just for the few who happened to build it first.

That core idea brought together a mix of people from different corners of the tech world. Sam Altman, then president of Y Combinator, had a knack for spotting startups with potential. Greg Brockman had been Stripe’s CTO, helping scale one of Silicon Valley’s fastest-growing companies. Ilya Sutskever was already a star in AI research, known for his work on deep learning alongside people like Geoffrey Hinton. John Schulman and Wojciech Zaremba added depth in reinforcement learning and robotics. Elon Musk joined early as a donor and high-profile supporter. On paper, they didn’t look like a typical research team, but that was the point. This was about ambition as much as it was about science.

OpenAI’s mission from day one was unusual: develop advanced AI in a way that benefits all of humanity, and share its research openly so no single company could monopolize it. At the time, this was a radical position. Most AI labs kept their best work behind closed doors, either to protect competitive advantage or to avoid public backlash. OpenAI took the opposite stance by making research public, and they hoped to level the playing field and accelerate safe development.

For the first couple of years, the team operated like an ambitious academic lab. They published papers on reinforcement learning, released open-source software like Gym, and dabbled in robotics projects. The culture was intense but idealistic. The team believed that openness could be a strength, not a weakness. But the reality of AI research was shifting pretty fast. Models were getting bigger, training them was getting more expensive, and the gap between hobbyist experiments and state-of-the-art systems was widening.

Then came the breakthrough work on transformers, the architecture that would power the entire GPT series. In 2019, OpenAI introduced GPT-2—a model that could generate eerily human-like text. Instead of releasing it in full, they staged a slow rollout, citing concerns that it could be used for misinformation or spam. This decision drew as much attention as the model itself. People were starting to realize that AI wasn’t just a research curiosity but a technology that could really change the world.

Running models at that scale required resources, aka money, far beyond what a nonprofit could typically raise. The leadership realized they needed a new structure to survive the next phase. In 2019, they created OpenAI LP, a “capped-profit” company controlled by the nonprofit’s board. This allowed them to raise outside investment while limiting how much profit investors could make, with the idea that anything beyond the cap would go back toward the mission. It was an unconventional compromise—one foot in the nonprofit world, one in the startup arena.

That same year, Microsoft made its first major investment: $1 billion, plus access to Azure’s high-end cloud infrastructure. This was a strategic lifeline and not just a cash infusion. Azure became the platform for training massive models, and Microsoft became the distribution partner that could embed OpenAI’s work into products used by millions. For OpenAI, it meant they could keep pushing the research frontier without constantly worrying about running out of computing power.

The partnership paid off. In 2020, OpenAI unveiled GPT-3, a model with 175 billion parameters—orders of magnitude larger than its predecessors. GPT-3 could write essays, generate code, translate languages, and answer questions with surprising fluency. For the first time, it felt like AI could be a general-purpose tool rather than a specialized demo. OpenAI launched GPT-3 through an API instead of releasing the model weights, a sign that the era of pure openness was giving way to a more controlled, product-driven approach.

By 2021, the company was experimenting with AI that could create more than just text. DALL·E, released that January, could generate original images from written prompts, turning surreal ideas into realistic visuals. A year later, DALL·E 2 refined those capabilities, producing higher-quality, more lifelike images. These tools hinted that AI could eventually handle any creative medium. But the real turning point was still in production.

On November 30, 2022, OpenAI released ChatGPT—a chatbot interface on top of a fine-tuned GPT-3.5 model. It wasn’t the most advanced model the company had, but it was approachable, responsive, and addictive. People who had never touched an AI tool before now had an easily accessible chat bot for them. Within five days, ChatGPT had over a million users. Teachers were rethinking homework. Businesses were rethinking workflows. The general public was getting its first taste of everyday AI.

Keeping up with that demand was a new challenge. OpenAI invested heavily in refining the model through reinforcement learning from human feedback (RLHF), adding guardrails to reduce harmful outputs, and scaling infrastructure to handle millions of concurrent users. GPT-4 followed in 2023, bringing better reasoning and reliability, and becoming the default model for paying subscribers. ChatGPT had evolved from a viral experiment into a core product—and "most importantly" a major revenue stream.

Then came the company’s most dramatic moment yet. In November 2023, the nonprofit board abruptly removed Sam Altman as CEO, citing concerns that were never fully explained. The move triggered a wave of internal and external backlash. Hundreds of employees signed an open letter threatening to quit. Microsoft publicly offered jobs to the entire team. Within days, Altman was reinstated, the board was reshuffled, and OpenAI was back in business. The episode underscored how fragile its governance structure could be, and how much the company’s future depended on the people running it.

OpenAI kept expanding under all these circumstances. In mid-2023, it launched the Superalignment initiative, dedicating significant compute resources to figuring out how to keep future AI systems safe and aligned with human values. But in early 2024, several key safety leaders, including co-founder Ilya Sutskever, left the company. That sparked fresh debate about whether OpenAI could truly balance its mission with the commercial pressures of leading the AI race.

Financially, the company was in a different universe from its early days. By 2024, OpenAI was generating billions in annual revenue from ChatGPT subscriptions, enterprise contracts, and API usage. Its technology was embedded in Microsoft products, giving it a direct path into the daily routines of millions of users. The partnership with Microsoft deepened, and of course so did OpenAI’s role in shaping the consumer and enterprise AI landscape.

OpenAI has built the public’s relationship with AI itself, introducing it as a tool anyone can use. The next phase of its story will hinge on whether it can keep that relationship healthy, balancing innovation with responsibility, and proving that the belief it was founded on—that AI should benefit everyone—can hold true even at the very top of the tech world.