OpenAI -- like the artificial intelligence it bundles and sells -- is not exactly brand new to the market. The company was founded by a team of Silicon Valley tech titans in 2015, Elon Musk among them. But the firm's launch of ChatGPT in November changed the company's trajectory, catapulting it into the stratosphere as the chatbot positioned OpenAI as one of the most significant tech companies around today.
And despite an ever-increasing litany of concerns over the harms, risks and actual usability of OpenAI's flagship product, its meteoric launch is starting to pay off.
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OpenAI is currently on track to earn more than $1 billion in revenue over the next year, far above revenue projections the company had previously shared with its investors, according to The Information.
Last year, the company generated just $28 million.
The revenue is coming from a combination of ChatGPT Plus subscribers -- which number more than 2 million, according to the Bay Area Times -- and enterprise customers, which include Zoom, Wix and Coca-Cola.
Based on investments into OpenAI made earlier in the year, the company is valued between $27 billion and $29 billion. The firm is additionally backed by Microsoft, which has invested $13 billion in the company.
Still, despite lofty valuations and compounding rates of revenue, OpenAI's product is expensive to run. Analysts estimated earlier in the year that ChatGPT costs OpenAI around $700,000 to run every day, or around $20 million a month, severely eating into OpenAI's profit.
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One of the analysts -- Dylan Patel of semiconductor research company SemiAnalysis -- told Insider in April that the cost to run ChatGPT has most likely risen above his estimates, considering the release of GPT-4, the more powerful version of the model.
The cost to run ChatGPT and similar Large Language Models exceeds dollars; the amount of computing power necessary to let these bots function tags these companies with enormous carbon footprints, though the exact numbers remain impossible to predict as researchers still don't know what's under the hood.
"That's the dichotomy," leading AI researcher Dr. Sasha Luccioni told The Street in June. "We could be doing great stuff for the climate with AI, which we are doing to some extent, but it's kind of being voided by these large language models and the amount of resources they need."
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