AI Inference: Good, Fast, and Cheap, with Lin Qiao & Dmytro Ivchenko of Fireworks AI

In this episode, we delve into the intricate world of AI inference with cofounders of Firework AI. Discover the strategies behind optimizing AI performance, the importance of balancing latency and throughput, and the nuances of different AI architectures from GPT-3 to Stable Diffusion. Learn about their partnership with Stability AI, their unique focus on reducing total cost of ownership, and their vision for a seamless developer experience.

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The Brave search API can be used to assemble a data set to train your AI models and help with retrieval augmentation at the time of inference. All while remaining affordable with developer first pricing, integrating the Brave search API into your workflow translates to more ethical data sourcing and more human representative data sets. Try the Brave search API for free for up to 2000 queries per month at https://bit.ly/BraveTCR

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CHAPTERS : (00:00:00) Introduction (00:08:34) Compute Stack (00:19:23) Fireworks Product Philosophy (00:24:11) Sponsors : Brave / Omneky (00:25:40) Fine-tuning Strategy (00:38:40) Sponsors : Plumb / Squad (00:40:33) NVIDIA Stack Overview (00:47:14) TensorFlow Triton Service (00:55:25) Reduced Precision Advantages (01:03:57) Different Deployment Scenarios (01:08:27) Seeking Intuition on Sharding (01:19:28) Announcing Stability AI Partnership (01:32:00) Closing Remarks