The situation with OpenAI and ChatGPT serves as a cautionary tale about the potential pitfalls of over-reliance on AI. The medical field, in particular, has seen a surge in the adoption of AI-driven solutions in recent years. From diagnostic tools to treatment planning, AI has promised to revolutionize healthcare. However, the costs associated with developing, maintaining, and updating these AI systems can be substantial. As per FirstPost, OpenAI, an early AI industry pioneer that helped mainstream AI conversations among the general public, appears to be financially suffering.
Because of its high objective of creating ChatGPT the preeminent chatbot in the field of generative artificial intelligence, the company’s finances are jeopardized. According to a recent story in Analytics India Magazine, OpenAI may be forced to declare bankruptcy in the near future. The outrageous expense of just keeping ChatGPT running is $700,000 per day for the company. Despite the company’s best efforts to market more AI models such as GPT-3.5 and GPT-4, OpenAI continues to lose money.
OpenAI and ChatGPT got off to a flying start, with record-breaking numbers of people signing up in the first few days. According to fresh data from SimilarWeb, its user base is dwindling. Between July 2022 and July 2023, the number of users fell by 12%, from 1.7 billion to 1.5 billion. Visitors to the ChatGPT website only; OpenAI API users are not included. Even the application programming interfaces (APIs) of the corporation are being questioned.
Many businesses that were previously hesitant to enable their staff to utilize ChatGPT are now paying for access to OpenAI’s APIs in order to construct AI chatbots. However, open-source LLM models compete with OpenAI’s proprietary models. These models are free to use and may be edited without restriction. One can fairly question why they would pay for OpenAI’s premium service when free alternatives such as LLaMA 2 give equivalent, if not more, capability in some cases.
Sam Altman, the CEO of OpenAI, appears to have some reservations about the company’s plan. While OpenAI is motivated by profit, Altman has been vocal about the dangers of unregulated AI research and development. He is concerned that AI would result in the loss of millions of jobs and has urged for tight laws to prevent this from happening. Some in the industry feel Altman is experiencing a “Frankenstein moment,” or is considering the negative consequences of the artificial intelligence “monster” he helped create. Despite these challenges, OpenAI is currently investigating ways to monetize their GPT-4 LLMs.
However, success has yet to come. Since the company’s inception, ChatGPT has lost $540 million. Microsoft and other venture capital firms have invested a total of $10 billion in OpenAI. Despite the company’s current financial challenges, its ambitious sales projections of $1 billion by 2024 appear implausible. OpenAI is also experiencing personnel challenges. The company is not laying off workers, but it is losing its top employees to competitors. After assessing how much it cost to run, Altman decided to market ChatGPT in December 2022.
Every day, Microsoft and other investors pay $70,000 to keep ChatGPT functioning. OpenAI’s viability is jeopardized unless income increases dramatically. The artificial intelligence sector is shifting as well. Elon Musk’s debut into the AI sector with his chatbot “TruthGPT” and substantial investments in AI infrastructure suggest increased competition, even though Google and Meta are regarded as major competitors. Another complication is the continued paucity of enterprise-grade GPUs.
The GPU scarcity has been compounded by the trade dispute between the United States and China, which has prompted Chinese technology businesses to make significant orders for artificial intelligence (AI) processors. The decreasing quality of ChatGPT output indicates that OpenAI’s ability to construct and train new models is impeded by this shortage. Overall, OpenAI is failing in a variety of ways, ranging from its bottom line to its user base to its capacity to earn revenue to the quality of its core product. The organization must have a long-term strategy for producing money right now.