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?
Quick slightly unrelated question: Does anyone have a comparison of using Google cloud services vs AWS for machine learning? I'm planning to pick one, and I was leaning towards Google Cloud Services because of the TensorFlow support and the fact that Google is big on ML, making it likely that it's something that Google will support and be good at. With this blog post, I'm not sure.
I find it frustrating for all the power they want to give me... that some basic service design is lacking.<p>Polly is a stand alone component but the reverse is closely bound up into Lex which is a conversational interface API.<p>Amazon has internally built an engine I could ask to convert an audio file in S3 into a text content representative of the audio file... yet I can only use Lex to drive a conversation via text and audio.<p>If AWS really want to give me the power of their AI tools. How about unbundling them?
Very impressive. I am working in a cognitive computing book, and I am going to add a chapter or appendix on Amazon AI. A little off topic, but even though I self-classify as a Google fan and very much enjoyed working there as a contractor, when a friend asked once which technology company impressed me more I said Amazon.<p>A big win for Amazon is that so many companies already have huge data sets in S3. Having AI APIs 'close to' existing data makes it easier getting started.
I am a complete noob to the AI space but I was wondering whether the following is possible (in AWS).<p>I have a million scanned images of court documents. Some are briefs, some are motions, some are court orders, etc... Given that I have images and their types, could I "train" the AI with these million documents to recognize a new image that might come in?
Production ready AI services are few and far and but Polly is up there. I am currently using it in a workflow as part of a IVR front end. Seeing good results.
I know ML is the big cheese right now, but doesn't it seem like a bad use case for the cloud? Consider:<p>1) Training ML models does not require network access, which is one of the biggest competitive advantages of the cloud.<p>2) Training ML models is typically a batch process, which benefits minimally from the scale-on-demand model of the cloud.<p>Since the cloud premium is a significant exchange for the value that it adds, I don't see this being a big win for cloud providers. I can't help but think that if I were making use of extensive machine learning with continuous training, I'd have it training models on a local bare metal cluster statically scaled to my application's demand with minimal network connectivity needs. And then ship the serialized trained models to the cloud. The potential cost difference is huge.
How should I interpret their picture? Can I get an AMI with Keras preconfigured on a p2 instance? Because that would be pretty useful. I currently have a p2 instance (smallest possible one) that I spin up for training and the like.
Has anyone used Rekognition? We're thinking about pumping traffic cam feeds into it in cities for vehicle counting but don't want to waste time if it's junk.
"Mark Cuban recently talked about it as the most important technology to ramp up on, to avoid becoming a “dinosaur”"<p>I wonder if this impresses this blog's audience, or does exactly the opposite...
The one time I actually want to subscribe/follow something there's no "Hey would you like to give me your email address?" popup... hmm