That’s according to President and Co-Founder Daniela Amodei, who spoke Saturday (Jan. 3) with CNBC about the company’s approach to artificial intelligence (AI) development at a time when rival OpenAI is making headlines over its $1.4 trillion in computer/infrastructure commitments.
“I think what we have always aimed to do at Anthropic is be as judicious with the resources that we have while still operating in this space where it’s just a lot of compute,” Amodei, who founded the company with her brother Dario, told CNBC.
“Anthropic has always had a fraction of what our competitors have had in terms of compute and capital, and yet, pretty consistently, we’ve had the most powerful, most performant models for the majority of the past several years.”
Now, the report said, Anthropic is aiming to demonstrate that the next stage of competition won’t be determined by which company has the budget for the largest pretraining runs.
The company’s strategy centers on higher-quality training data, post-training techniques that improve reasoning, and product choices aimed at making models cheaper to run and simpler to adopt at scale. At the same time, the startup isn’t “operating on a shoestring,” as CNBC put it, with roughly $100 billion in compute commitments.
“The compute requirements for the future are very large,” Amodei said. “So our expectation is, yes, we will need more compute to be able to just stay at the frontier as we get bigger.”
In related news, PYMNTS wrote last week about a new partnership involving Anthropic, OpenAI and Block that demonstrates the “cooperation among some of the power players that will make agentic AI’s infrastructure the commerce and communication engine of the future.”
In this case, that means the formation of Agentic AI Foundation (AAIF), an open source initiative housed under the Linux Foundation and designed to shape how autonomous AI systems are developed and deployed.
In a statement issued by Block, the company contends that agentic AI is approaching a critical inflection point, one in which early architectural choices will determine whether the technology evolves as an open, interoperable ecosystem or fragments into proprietary silos.
“We’re at a critical juncture,” Block writes, cautioning that without open development, agentic AI risks concentrating power among a few providers and hindering enterprise adoption.
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