Welcome to the New AWS AI Blog
We have recently set up a TensorFlow assessment function in AWS lambda, and got <i>very</i> close to the maximum allowed size of a lambda function (250MB) with the trained model currently being 85MB, and the TensorFlow libraries and binaries taking up another 140 or so megabytes by default (<- which we cracked down a bit, but that's quite a hack).<p>I feel like Amazon could do some work in this area to support users to use their own engines and not be bound to AWS AI Platforms and Services.<p>This could be as simple as publicly documenting the time lambda's stay 'warm' for and retain data in /tmp persisting through multiple invocations or some other examples on how an AI workflow could be implemented with popular custom engines such as TensorFlow.<p>Does anybody else have any experience in this regard?