By Christine Ji and Britney Nguyen
OpenAI sits at the center of the AI boom that it started. But it faces increasing challenges around both the business and the technology itself.
Excitement around recent Google and Anthropic AI offerings is marring the celebration of ChatGPT’s third birthday.
OpenAI’s launch of ChatGPT on November 30, 2022 was the starting gun for the artificial-intelligence arms race that has lifted up the stock market and unleashed billions of dollars of investment.
Whether OpenAI can preserve its leading position going forward is now the big question.
Within five days of its release, ChatGPT had achieved 1 million users. Three years later, the latest version of ChatGPT – with real-time access to the web, enhanced reasoning, coding skills and image- and video- generation capabilities – makes its initial features appear rudimentary. In September, OpenAI released its Sora video-generation app, which also achieved 1 million users in five days.
But the talk around OpenAI isn’t as exuberant now as it was when ChatGPT first burst on the scene. Competing models from Google and Anthropic have won praise for their technological capabilities, all while OpenAI’s financial commitments have started to worry Wall Street. Some technologists also wonder if large language models will ever have the potential to unlock the most futuristic AI visions.
And in some cases, things haven’t changed much. Gary Marcus, an emeritus professor at New York University and prominent psychologist known for his research on AI, told MarketWatch that he raised issues about OpenAI’s systems in late 2022 that still haven’t been solved. “They hallucinate and have trouble with reasoning,” he said.
The competitive scene
Last December, Marcus also predicted that without a truly differentiated product by the end of 2025, OpenAI would risk losing its moat.
“And now, they have a competitor with a product that’s more or less just as good,” Marcus added, referring to Alphabet’s (GOOGL) (GOOG) Google Gemini 3 AI model, which debuted earlier this month.
The AI space has seen “an explosion of activity” in the past few years, Benjamin Lee, a professor at the University of Pennsylvania’s School of Engineering, told MarketWatch. “We’re seeing a lot of experimentation and adoption by individual users and others.”
Gemini, which many thought had been left for dead at the beginning of the year, has made aggressive strides to increase its market share. Earlier this month, Google’s newest Gemini 3 and Nano Banana Pro updates further impressed investors and users alike.
“Google was fairly far behind, and I think people counted them out, but their most recent model is arguably ahead of GPT-5,” Marcus said.
Gemini 3 outperformed GPT-5 on a majority of key AI benchmarks, or standardized tests used to evaluate models. And Anthropic’s latest model, Claude Opus 4.5, beat both GPT-5 and Gemini 3 on agentic coding benchmarks upon its release last week.
“This is really healthy and, from a technical perspective, super exciting to see the robust competition between these types of models,” Lee said. But for OpenAI, the competitive playing field means it can’t coast on its first-mover advantage.
Also read: How can Anthropic stand out in the AI wars? I went to a Greenwich Village pop-up to find out.
A market linchpin
Concerns about an AI bubble have boiled over this month, leading to a selloff that’s hit tech stocks hard.
OpenAI has come under scrutiny for its central role in a complex web of AI financing. The company has inked over $1.4 trillion in AI infrastructure deals, and investors are skeptical about how the AI lab will be able to pay for all of its commitments.
New features such as OpenAI’s ChatGPT Pulse, Sora and web browser could help scale its business, but AI monetization is less of a concern for Google, which has business segments spanning search, cloud computing, Android and enterprise software. Additionally, these verticals facilitate the distribution and scale of Google’s AI products.
Google’s custom-chip business also gives it a major leg up in the AI race, enabling the company to save on infrastructure costs and opening up another revenue stream in the form of equipment rentals. The tech giant uses its tensor processing units (TPUs) to train its Gemini models. The chips have also been used to power its search and YouTube algorithms.
In October, Anthropic said it plans to use up to 1 million of Google’s TPUs as it seeks to scale up computing – an issue also plaguing OpenAI as AI models become larger and more advanced.
Read: These two ‘Magnificent Seven’ stocks could be the strongest survivors of an AI apocalypse
Are LLMs the path to AGI?
As the chatbot wars rage on, a growing number of AI researchers are questioning if large language models will even be the future of the technology. After all, hallucinations and reasoning gaps aren’t issues unique to ChatGPT. Wall Street shares that worry, as investors question the return on investment of chatbots that still lack the power to fully automate corporate workflows.
LLMs operate by predicting the next word, or token, in a sequence based on statistical probability. They don’t actually “know” facts or understand logic.
“They’re not really abstracting away a stable comprehension of the world,” Marcus said of LLMs. As AI technology trends toward autonomous vehicles and robots, Marcus and others believe the new frontier will be “world models,” or AI with a mental simulation of the real world.
Sergey Gorbunov, a technologist and co-founder of blockchain-infrastructure platform Axelar, also sees world models as perhaps a better path toward artificial general intelligence, or AGI, which is the point at which AI models will be believed to be as intelligent as humans. Admittedly, ideas about what AGI will look like have changed in the three years since OpenAI launched ChatGPT.
Unlike LLMs, world models “interact with physical spaces,” and therefore can “understand a little bit what’s happening in physics, not just in text,” Gorbunov told MarketWatch. For example, world models could help improve self-driving cars, he said, because an autonomous vehicle would be able to predict seconds ahead what another car will do.
Earlier this month, Gorbunov outlined in a blog post “two fundamental limitations” for LLMs: the reliance on preexisting data, and the fact that LLMs essentially navigate probabilities.
“If you look at the math of these models or how they’re constructed, they’re just predictable probability distributions,” Gorbunov told MarketWatch. “There is no sense of artificial intelligence anywhere there.”
What’s next for ChatGPT, and AI in general?
Three years after ChatGPT’s release, Vasant Dhar, a professor at New York University’s Stern School of Business and the author of “Thinking With Machines,” told MarketWatch that the fundamental way AI has changed is that it’s become better at simulating understanding, and is therefore more relatable to people.
ChatGPT’s progress in three years is “astounding,” Dhar said, even as its benefits to business and other aspects of life remain to be seen. He emphasized that the adoption of general-purpose technologies such as electricity and the internet historically took years to unfold.
“Our expectations have gone up so much that we expect this capability to be realized instantly,” Dhar said. “There is so much capability in AI at the moment that is still to be realized.”
While large language models like the ones powering ChatGPT have been at the forefront of the current AI boom, Dhar said he’s seeing incremental research into vision models and other types of models that will be able to integrate more human senses.
In the next year or two, Dhar said he expects to see improvements to ChatGPT and Gemini that, despite seeming incremental, will be “actually very significant” because of how they impact the lives of people using them.
But world models are still far ahead of where the AI industry currently is, Gorbunov told MarketWatch. In the coming months, he expects to see a battle on the front end of user interaction with the web through AI-powered web browsers such as OpenAI’s Atlas and Perplexity’s Comet. Google is also part of that fight, he said, as the dominant search engine incorporates more AI features into its platform.
“I think whoever is going to win that [user experience] in some sense will be able to capture a lot of traffic going forward,” Gorbunov said.
-Christine Ji -Britney Nguyen
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11-29-25 0800ET
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