Tech giants wish to boast about trillion-parameter AI fashions that require huge and costly GPU clusters. However Fastino is taking a distinct strategy.
The Palo Alto-based startup says it has invented a brand new type of AI mannequin structure that’s deliberately small and task-specific. The fashions are so small they’re educated with low-end gaming GPUs price lower than $100,000 in complete, Fastino says.
The tactic is attracting consideration. Fastino has secured $17.5 million in seed funding led by Khosla Ventures, famously OpenAI’s first enterprise investor, Fastino completely tells TechCrunch.
This brings the startup’s complete funding to just about $25 million. It raised $7 million final November in a pre-seed spherical led by Microsoft’s VC arm M12 and Perception Companions.
“Our fashions are quicker, extra correct, and price a fraction to coach whereas outperforming flagship fashions on particular duties,” says Ash Lewis, Fastino’s CEO and co-founder.
Fastino has constructed a set of small fashions that it sells to enterprise clients. Every mannequin focuses on a selected job an organization would possibly want, like redacting delicate information or summarizing company paperwork.
Fastino isn’t disclosing early metrics or customers but, however says its efficiency is wowing early customers. For instance, as a result of they’re so small, its fashions can ship a whole response in a single token, Lewis advised TechCrunch, displaying off the tech giving an in depth reply without delay in milliseconds.
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It’s nonetheless a bit early to inform if Fastino’s strategy will catch on. The enterprise AI house is crowded, with firms like Cohere and Databricks additionally touting AI that excels at sure duties. And the enterprise-focused SATA mannequin makers, together with Anthropic and Mistral, additionally provide small fashions. It’s additionally no secret that the way forward for generative AI for enterprise is seemingly in smaller, extra centered language fashions.
Time might inform, however an early vote of confidence from Khosla definitely doesn’t harm. For now, Fastino says it’s centered on constructing a cutting-edge AI staff. It’s concentrating on researchers at prime AI labs who aren’t obsessive about constructing the largest mannequin or beating the benchmarks.
“Our hiring technique may be very a lot centered on researchers that possibly have a contrarian thought course of to how language fashions are being constructed proper now,” Lewis says.
