The company’s Series A round, announced Thursday (June 9), values Scaled Cognition at $750 million and will help it expand its research team and speed product development.
In an interview with the Wall Street Journal (WSJ) about the new funding, Scaled Cognition Co-Founder and CEO Dan Roth said the company works to address problems caused by artificial intelligence (AI) frontier models, describing them as “amazing,” but also “sort of like schizophrenic geniuses.”
“They can create incredible answers, and then you can ask them the same question a second time and get a completely different answer that … might not even be correct,” he said.
“We really believe that for these systems to really be useful, you have to be able to trust them. And in order for you to trust them, they have to be provably reliable.”
Just one error can have horrific repercussions, the CEO added, using the example of a healthcare AI hallucinating a single digit in a prescription and giving a patient incorrect medication.
Roth and Co-Founder/Chief Technology Officer Dan Klein, the report said, wanted to develop alternative AI architecture that provides reliably accurate results, which led to APT (Agentic Pretrained Transformer), their company’s flagship model.
In addition to APT, Scaled Cognition has also constructed a platform for enterprise AI deployment that features agentic tooling, live agent monitoring and simulation and evaluation frameworks, the WSJ added.
As covered here last year, hallucinations have become “a headline risk.” A federal judge in Wyoming threatened to sanction attorneys who submitted AI-generated briefs peppered with phony cases, while Butler Snow, a law major firm, admitted last spring that its lawyers relied on hallucinated citations.
“What might look like quirky tech failures in consumer chat apps quickly turns into reputational and regulatory landmines when applied to banking, payments or compliance,” PYMNTS wrote at the time. “The industry once dismissed hallucinations as teething errors. Today, they are seen as structural.”
A WSJ report last year said that leading developers had begun training AI to say “I don’t know” rather than improvise, realizing that probabilistic models will never be free from errors.
In the payments world, Lloyds Bank and Coinbase increased confidence in their hallucination protections after deploying safer generative AI systems. And in the insurance sector, companies have begun offering policies to cover AI-related errors, including hallucinated outputs, “highlighting how serious the risk has become,” PYMNTS added.
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