OpenAI’s CEO Sam Altman reports remarkable revenue growth
According to a report, OpenAI, the company responsible for the widely used ChatGPT chatbot, has experienced a significant surge in its revenue growth. CEO Sam Altman has informed employees that the company’s annualized revenue has exceeded $1.3 billion, indicating a monthly income of $100 million. This represents a 30 percent increase since the summer, when the company was generating a consistent $1 billion in revenue annually.
According to a report by The Information, the increase in revenue is mainly due to the number of subscriptions for the premium versions of its chatbot ChatGPT, which has increased tremendously since the paid version was launched in February 2023. Interestingly, before the launch of ChatGPT, the company’s annual revenue was around $28 million , but when ChatGPT powered by GPT 3.5 came out, it became one of the pioneers of generative AI.
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OpenAI registers a huge return rate
To understand how big OpenAI’s achievement is, we can also look at Anthropic’s revenue, according to the report. Anthropic has reached $100 million in annual revenue, which translates to about $8 million per month. That’s less than a percent of the revenue OpenAI collects.
But OpenAI isn’t looking to stop. OpenAI may soon bring major updates to its AI tools for developers based on large language models (LLM). According to a Reuters report, OpenAI is ready to significantly lower the price of AI tools to make them more profitable for developers. In addition, it plans to make them faster and add a new vision capability to AI models. These new updates will be announced at OpenAI’s first developer conference on November 6.
Some updates to OpenAI’s AI models include adding memory storage. What this does for AI tools for developers is that it localizes the data that the model needs to scrape in order to provide a solution. According to the report, it can theoretically cut costs by up to 20 times. This solves a big pain point for OpenAI customers who don’t use OpenAI’s more powerful AI models due to high costs. This can also have a knock-on effect and further reduce the cost of AI tools made by developers significantly.
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