Tech giants wish to boast about trillion-parameter AI models 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 sort of AI mannequin structure that’s deliberately small and task-specific. The models are so small they’re skilled with low-end gaming GPUs price lower than $100,000 in whole, 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 whole funding to almost $25 million. It raised $7 million final November in a pre-seed spherical led by Microsoft’s VC arm M12 and Perception Companions.
“Our models are sooner, extra correct, and price a fraction to coach whereas outperforming flagship models on particular duties,” says Ash Lewis, Fastino’s CEO and co-founder.
Fastino has constructed a set of small models that it sells to enterprise clients. Every mannequin focuses on a selected job an organization may 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 models can ship a complete response in a single token, Lewis instructed TechCrunch, exhibiting off the tech giving an in depth reply directly 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 supply small models. It’s additionally no secret that the way forward for generative AI for enterprise is probably going in smaller, extra targeted language models.
Time might 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 group. It’s focusing 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 targeted on researchers that possibly have a contrarian thought course of to how language models are being constructed proper now,” Lewis says.
