Anthropic’s third-quarter revenue rose 45 per cent to $16.8 billion (€15 billion) from the previous quarter, according to an investor who attended a meeting with the AI company’s leadership in San Francisco on Wednesday.
Revenue in the first quarter was $4.7 billion, and $11.6 billion in the second quarter, according to the person who attended the investor day meant to familiarise prospective Anthropic investors before its highly anticipated initial public offering (IPO).
The IPO is expected to precede a public listing by rival OpenAI, making Anthropic an early test of investor appetite for heavily unprofitable AI developers pursuing massive scale. Its public-market debut is likely to be pushed until after the November US midterm elections.
Scrutiny of AI companies’ finances has intensified as they pour money into chips, data centres and computing power needed to develop and operate increasingly powerful models.
RM Block
Targeting a valuation of more than $2 trillion, Anthropic is seeking to convince investors that its breakneck revenue growth can eventually outrun the enormous costs of building and running AI systems.
The company has committed hundreds of billions of dollars in future spending under long-term agreements for cloud services, computing and infrastructure, Reuters reported last month.
Founded by former OpenAI executives, Anthropic has emerged as one of the leading generative AI developers with its Claude family of models. Its expansion has been underpinned by Amazon and Alphabet’s Google, which are simultaneously investors, suppliers of computing power and important distribution partners, as well as AI competitors.
[ Never mind the ‘risk to humanity’, Anthropic’s IPO raises more prosaic concernsOpens in new window ]
Anthropic has also sought to distinguish itself through its focus on AI safety, warning of the dangers posed by increasingly capable systems even as it competes in the race to develop and commercialise more powerful models.
Its research has found that its own AI agents have engaged in troubling behaviour in test environments, including leaking sensitive information and sabotaging code, though the company has said it has not seen evidence of such misalignment in real-world deployments. – Reuters
