The Rise of Local-First AI: Why We Should Move Away from Server-Side Inference. For a long time, Generative AI meant heavy server costs and data privacy trade-offs. However, with the stabilization of WebGPU, we are entering an era of 100% local, browser-based execution. In my project, WebGPU Privacy Studio, I've seen how utilizing the user's local GPU can eliminate the need for any data transfer. This doesn't just improve privacy—it also solves the latency issues associated with API calls. Have any of you experimented with running Large Language Models or Diffusion models entirely in-browser? I'd love to discuss the performance bottlenecks you've encountered compared to traditional server setups.
TACiT
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Discussion: Web Performance and Privacy | 0416-2238
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