[HN Gopher] Serverless development experience for embedded compu...
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Serverless development experience for embedded computer vision
Author : migmartri
Score : 60 points
Date : 2023-11-16 12:29 UTC (10 hours ago)
(HTM) web link (github.com)
(TXT) w3m dump (github.com)
| migmartri wrote:
| I found this OSS tool interesting since it abstracts pretty much
| all the plumbing required to set up a computer vision pipeline.
| yeldarb wrote:
| This looks like a really cool project; would you be open to us
| PR'ing support for the 50k fine-tuned models on Roboflow
| Universe[1] via an `inference`[2] integration?
|
| [1] https://roboflow.com/universe
|
| [2] https://github.com/roboflow/inference
| miguelaeh wrote:
| Definitely! It is something I was thinking to do, I just did
| not find the time yet. I think allowing people to
| automatically load models from the Roboflow universe would be
| awesome!
| miguelaeh wrote:
| Hi!
|
| It is so cool you shared this repo. I am the developer behind it,
| hope you enjoy it and can provide some valuable feedback!
| yeldarb wrote:
| Pretty neat! We've been using Lambda for ML serving low-volume CV
| models (and my understanding is AWS' Sagemaker Serverless is a
| lambda wrapper) for a couple of years at Roboflow and it is
| really good for low-volume and bursty use-cases. The latency is
| surprisingly not bad. It gets really expensive relative to GPUs
| for high load (and especially predictable high-load like
| monitoring security cameras 24/7) though so we end up with our
| biggest enterprise customers running things in a Kubernetes
| cluster.
|
| There are a few serverless GPU companies like Banana.dev and
| Modal; I really want to give them a shot. Anyone have experience
| using them in prod?
| zaptrem wrote:
| We've been building with Modal over the past few months (though
| no prod-scale tests yet) and were slightly disappointed by very
| large (10-20 second) cold start times. In the long term we're
| more interested in inference servers that use
| compiled/optimized models instead of running plain old PyTorch
| (which adds another few seconds to cold start on its own).
| miguelaeh wrote:
| We are adding support for inference servers to Pipeless. We
| started by the ONNX Runtime, and OpenVINO, CoreML, CUDA and
| TensorRT execution providers. Some people mentioned me to
| integrate also with the Triton server, however I still need
| to deep into that and check its license. The good part is,
| there is no cold start right now, at the cost of having some
| resources allocated from the node start.
| angelmm wrote:
| After ChatGPT was announced, I found many cool projects that
| simplifies how you integrate LLM capabilities into your services.
| However, I didn't find many of these in the vision ecosystem.
|
| Getting started in AI + vision with just 3 commands is amazing! I
| will definitely try it for some personal projects with IP
| cameras.
|
| Good stuff :)
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