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Simplismart supercharges AI performance with personalized, software-optimized inference engine
The software-optimized inference engine behind Simiplismart MLOps platform runs Llama3.1 8B at a peak throughput of 501 tokens per second.
Today, Simplismart AI raised $7 million in funding to address this gap with its end-to-end MLOps platform that accelerates the entire orchestration effort by taking care of everything from fine-tuning models to deployment and observability. Similarly, we’ve achieved better results across all modalities, including text-to-speech, speech-to-text, text-to-image, image-to-image,” Amritanshu Jain, former Oracle engineer who co-founded the startup with ex-Google techie Devansh Ghatak, tells VentureBeat. The Terraform-like declarative orchestration language of the platform lets enterprises easily manage the entire pipeline, putting complete control back into their hands and reducing their dependency on the DevOps teams.
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