OpenAI hopes its biggest benefactor will back its plans for artificial general intelligence (AGI).
Sam Altman, chief executive of the artificial intelligence (AI) firm, told the Financial Times (FT) in an interview Monday (Nov. 13) that he plans to secure additional funding from Microsoft, which has already pledged $10 billion, to fund AGI, software that matches human intelligence.
Altman said his company’s partnership with Microsoft and its CEO Satya Nadella was “working really well” and that he expected “to raise a lot more over time” from that company and other investors to fund the cost of creating more sophisticated AI models.
Asked if Microsoft would continue, Altman said: “I’d hope so.” He added: “There’s a long way to go, and a lot of compute to build out between here and AGI . . . training expenses are just huge.”
He added that “revenue growth had been good this year,” but did not offer further details, and said OpenAI still hadn’t attained profitability because of training costs. However, the Microsoft partnership would ensure “that we both make money on each other’s success, and everybody is happy,” Altman added.
His comments followed last week’s Developer’s Day, in which OpenAI unveiled a suite of new tools and upgrades to its GPT-4, as well as a marketplace that showcases its best apps and will — eventually — share revenues with the most popular GPT creators.
“Right now, people [say] ‘you have this research lab, you have this API [software], you have the partnership with Microsoft, you have this ChatGPT thing, now there is a GPT store.’ But those aren’t really our products,” Altman said. “Those are channels into our one single product, which is intelligence, magic intelligence in the sky. I think that’s what we’re about.”
Meanwhile, PYMNTS looked recently at the challenges facing the government as it tries to regulate AI. Among the more pressing concerns is understanding how the technology functions and garnering the knowledge to oversee it.
While some historical forms of AI, like predictive forecasting and machine learning, have long been part of much of everyday life, generative AI capabilities represent something new when it comes to automating and generating outputs in areas like trading, risk management, fraud detection and investment research.
“But government moves at a snail’s pace when compared to the commercially accelerated adoption of tech innovations, and today’s AI models and machines are currently operating and scaling absent any regulation or policy guardrails,” PYMNTS wrote last week.
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