zeekoe
seldon-core
zeekoe | seldon-core | |
---|---|---|
4 | 14 | |
23 | 4,220 | |
- | 1.2% | |
2.8 | 7.6 | |
11 months ago | 7 days ago | |
Rust | HTML | |
MIT License | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
zeekoe
-
Who's hiring? December 2021 edition
We're a small, privacy-focused startup on a mission to empower everyone with the tools they need to realize financial privacy. To achieve this, we’re building zkChannels: a scalable and usable privacy-preserving payment infrastructure that integrates with existing payment networks, including but not limited to public blockchains. We're leveraging cutting-edge technologies like zero-knowledge proofs and multi-party computation to realize fast private transactions on public blockchains.
-
RiB Newsletter #30
Zeekoe. Zero-knowledge layer-2 payment channels.
-
Ask HN: Who is hiring? (December 2021)
Bolt Labs | Blockchain & Software Engineers | REMOTE
We're a small, privacy-focused startup on a mission to empower everyone with the tools they need to realize financial privacy. To achieve this, we’re building zkChannels (https://github.com/boltlabs-inc/zeekoe): a scalable and usable privacy-preserving payment infrastructure that integrates with existing payment networks, including but not limited to public blockchains. We're leveraging cutting-edge technologies like zero-knowledge proofs and multi-party computation to realize fast private transactions on public blockchains.
We're hiring for blockchain engineer, software engineer, and senior software engineer roles right now and offer competitive salaries, great health benefits, equity in the company, and a strong remote work culture. Lastly, we're building all of our infrastructure in Rust so you'll be working in Rust from day one.
You can read more about us and the positions in our full job postings here: https://boltlabs.tech/join-us
These are fully remote positions available to anyone living in and with work authorization in the United States. We are only able to offer these positions to someone who is living and working in the US.
-
[HIRING] Software Engineer and Senior Software Engineer (Rust) at Bolt Labs (Remote, USA)
Hello! I'm Marcella Hastings, a senior software developer and cryptographer at Bolt Labs. We're a small startup dedicated to empowering everyone with access to financial privacy by building zkChannels, a scalable and usable privacy-preserving payment infrastructure that integrates with existing payment networks, including but not limited to public blockchains. I thoroughly enjoy my work at Bolt, and I'm looking forward to expanding our team.
seldon-core
-
seldon-core VS MLDrop - a user suggested alternative
2 projects | 20 Feb 2023
-
[D] Feedback on a worked Continuous Deployment Example (CI/CD/CT)
ZenML is an extensible, open-source MLOps framework to create production-ready machine learning pipelines. Built for data scientists, it has a simple, flexible syntax, is cloud- and tool-agnostic, and has interfaces/abstractions that are catered towards ML workflows. Seldon Core is a production grade open source model serving platform. It packs a wide range of features built around deploying models to REST/GRPC microservices that include monitoring and logging, model explainers, outlier detectors and various continuous deployment strategies such as A/B testing, canary deployments and more.
-
[D] BentoML's Compatibility with Seldon;
I am using BentoML to build the docker container for a BERT model, and then deploy that using Seldon on GKE. The model's REST API endpoint works fine. at terms of compatibility with Seldon, the metrics are being scraped by Prometheus and visualized on Grafana. The only Seldon component that doesn't appear to be working is the request logging, which I have working for other applications that were deployed on Seldon. I am using the elastic stack from here. From my understanding, request logging should still be compatible and the ⠀only lost functionality should be Seldon's model metadata. Any insight on how to get the centralized request logging working? No errors were shown; it's just that the logs aren't being captured and sent to ElasticSearch. Anyone have any success using BentoML with Seldon and not losing any of Seldon's features?
-
Building a Responsible AI Solution - Principles into Practice
While tools in the model experimentation space normally include diagnostic charts on a model's performance, there are also specialised solutions that help ensure that the deployed model continues to perform as they are expected to. This includes the likes of seldon-core, why-labs and fiddler.ai.
-
Ask HN: Who is hiring? (January 2022)
Seldon | Multiple positions | London/Cambridge UK | Onsite/Remote | Full time | seldon.io
At Seldon we are building industry leading solutions for deploying, monitoring, and explaining machine learning models. We are an open-core company with several successful open source projects like:
* https://github.com/SeldonIO/seldon-core
* https://github.com/SeldonIO/mlserver
* https://github.com/SeldonIO/alibi
* https://github.com/SeldonIO/alibi-detect
* https://github.com/SeldonIO/tempo
We are hiring for a range of positions, including software engineers(go, k8s), ml engineers (python, go), frontend engineers (js), UX designer, and product managers. All open positions can be found at https://www.seldon.io/careers/
- Ask HN: Who is hiring? (December 2021)
-
Has anyone implemented Seldon?
Also note our github repo has a link to our slack where you can ask active users: https://github.com/SeldonIO/seldon-core
-
[Discussion] Look for service to upload a model and receive a REST API endpoint, for serving predictions
If you want to serve your model at scale, with a bunch of production features you should have a look at the open-source framework Seldon Core. It does what you're asking for plus a bunch of other cool stuff like routing, logging and monitoring.
- Seldon Core : Open-source platform for rapidly deploying machine learning models on Kubernetes
-
Looking for open-source model serving framework with dashboard for test data quality
Seldon ticks most of those boxes if you already have some experience with kubernetes. You can set up a/b tests, do payload logging to elastic and then do monitoring on top of that, and it has drift detection and model explainer modules too. Idk about great expectations integration, but you could probably do something with a custom transformer module as part of the inference graph.
What are some alternatives?
libzkchannels - zkChannels: Anonymous Payment Channels for Bitcoin, Zcash, Tezos and more
BentoML - The most flexible way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Inference Graph/Pipelines, Compound AI systems, Multi-Modal, RAG as a Service, and more!
miden-vm - STARK-based virtual machine
MLServer - An inference server for your machine learning models, including support for multiple frameworks, multi-model serving and more
plonk - A pure Rust PLONK implementation using arkworks as a backend.
evidently - Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b
web - Grow Open Source
great_expectations - Always know what to expect from your data.
AlephBFT - A rust implementation of Aleph Protocol
alibi-detect - Algorithms for outlier, adversarial and drift detection
logseq - A local-first, non-linear, outliner notebook for organizing and sharing your personal knowledge base. Use it to organize your todo list, to write your journals, or to record your unique life.
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.