Lin Qiao - Making Open Models 10x faster and better for Modern Application Innovation
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Generative AI powers the next generation of real time applications. The key to success of modern application development in the Gen AI era is secure, latency-sensitive and low cost LLM serving solution, which Firework’s enterprise grade deployment provides. Fireworks AI accelerates innovation through its SaaS platform of low latency inference and high quality fine-tuning of 100+ models, across the state of the art LLMs, image/video/audio generation, embedding and multimodality models. These advantages are delivered through Fireworks' proprietary FireAttention technology, 4x-15x faster than the OSS alternatives. To bring the totality of knowledge together, Fireworks tuned their own FireFunction model to integrate hundreds of models and API calling together. Fireworks' adoption is the fastest in the industry and it also enables a software stack capable of extracting the most across different hardware and deployment options.
Lin Qiao
Lin is the CEO and co-founder of Fireworks AI, with the mission to accelerate the transition to AI-powered business via an interactive experimentation and production platform centered around PyTorch technologies and state of the art models built using PyTorch. She led the development of PyTorch, AI compilers, and on-device AI platforms at Meta for the past half-decade. She drove AI research to production innovations across hardware acceleration, enabling model exploration and large and complex model scaling, building production ecosystems and platforms for all Meta's AI use cases. She received a Ph.D. in computer science, started her career as a researcher in Almaden Research Lab, and later moved to the industry as an engineer. Prior to Meta, she worked on a broad range of distributed and data processing domains, from high-performance columnar databases, OLTP systems, streaming processing systems, data warehouse systems, and logging and metrics platforms.
Lin Qiao
Lin is the CEO and co-founder of Fireworks AI, with the mission to accelerate the transition to AI-powered business via an interactive experimentation and production platform centered around PyTorch technologies and state of the art models built using PyTorch. She led the development of PyTorch, AI compilers, and on-device AI platforms at Meta for the past half-decade. She drove AI research to production innovations across hardware acceleration, enabling model exploration and large and complex model scaling, building production ecosystems and platforms for all Meta's AI use cases. She received a Ph.D. in computer science, started her career as a researcher in Almaden Research Lab, and later moved to the industry as an engineer. Prior to Meta, she worked on a broad range of distributed and data processing domains, from high-performance columnar databases, OLTP systems, streaming processing systems, data warehouse systems, and logging and metrics platforms.
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