Tech giants wish to boast about trillion-parameter AI fashions that require large and costly GPU clusters. However Fastino is taking a special 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 skilled with low-end gaming GPUs value 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 solely tells iinfoai.
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 sooner, 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 collection 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 informed iinfoai, 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 corporations 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 supply small fashions. It’s additionally no secret that the way forward for generative AI for enterprise is probably going in smaller, extra targeted language fashions.
Time could inform, however an early vote of confidence from Khosla definitely doesn’t damage. For now, Fastino says it’s targeted on constructing a cutting-edge AI staff. It’s focusing on researchers at high AI labs who aren’t obsessive about constructing the largest mannequin or beating the benchmarks.
“Our hiring technique could be very a lot targeted on researchers that perhaps have a contrarian thought course of to how language fashions are being constructed proper now,” Lewis says.
