From e881bfbfbeefd653b87d560c2539b75d6fafbace Mon Sep 17 00:00:00 2001 From: Andras Schmelczer Date: Sun, 24 Jul 2022 15:41:56 +0200 Subject: [PATCH] Improve landing page --- docs/index.md | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/docs/index.md b/docs/index.md index 188314b..af536d0 100644 --- a/docs/index.md +++ b/docs/index.md @@ -26,10 +26,11 @@ Applying AI is becoming increasingly easier but many case studies have shown tha - [x] Save prediction traces of each prediction including arguments and model versions - [x] Save feedback and merge it into a ground-truth database -- [x] Version and store models and data on shared infrastructure *(MongoDB GridFS, S3-compatible storage, shared local-volume)* +- [x] Version and store models and data on shared infrastructure *(MongoDB GridFS, S3-compatible storage, shared volume)* - [x] Automatically scaffolded custom REST API (and OpenAPI schema) for easy integration - [x] Input validation - [x] Sensible cache-policy +- [x] Graceful error handling - [x] Seamless support for both synchronous and asynchronous inference methods - [x] Easy integration with remote GreatAI instances - [x] Built-in parallelisation (with support for multiprocessing, async, and mixed modes) for batch processing @@ -39,7 +40,7 @@ Applying AI is becoming increasingly easier but many case studies have shown tha - [x] Auto-reload for development - [x] Docker support for deployment - [x] Deployable Jupyter Notebooks -- [x] Dashboard for high-level overview and analysing traces +- [x] Dashboard for online monitoring and analysing traces ## Roadmap @@ -80,7 +81,7 @@ great-ai demo.py ![demo screen capture](media/demo.gif){ loading=lazy } !!! success - Your GreatAI service is ready for production use. Many of the [SE4ML best-practices](https://se-ml.github.io){ target=_blank } are configured and implemented automatically. To have full control over your service and to understand what else you might need to do in your use case, continue reading this documentation. + Your GreatAI service is ready for production use. Many of the [SE4ML best practices](https://se-ml.github.io){ target=_blank } are configured and implemented automatically. To have full control over your service and to understand what else you might need to do in your use case, continue reading this documentation. ## Why is this GREAT? @@ -98,7 +99,7 @@ GreatAI fits between the prototype and deployment phases of your (or your organi There are other, existing solutions aiming to facilitate this phase. [Amazon SageMaker](https://aws.amazon.com/sagemaker){ target=_blank } and [Seldon Core](https://www.seldon.io/solutions/open-source-projects/core){ target=_blank } provide the most comprehensive suite of features. If you have the opportunity to use them, do that because they're great. -However, research indicates that professionals rarely use them. This may be due to their inherent setup and operating complexity. ==GreatAI is designed to be as simple to use as possible.== Its clear, high-level API and sensible default configuration makes it extremely easy to start using. Despite its relative simplicity over Seldon Core, it still implements many of the [SE4ML best-practices](https://se-ml.github.io){ target=_blank }, and thus, can meaningfully improve your deployment without requiring prohibitively large effort. +However, research indicates that professionals rarely use them. This may be due to their inherent setup and operating complexity. ==GreatAI is designed to be as simple to use as possible.== Its clear, high-level API and sensible default configuration makes it extremely easy to start using. Despite its relative simplicity over Seldon Core, it still implements many of the [SE4ML best practices](https://se-ml.github.io){ target=_blank }, and thus, can meaningfully improve your deployment without requiring prohibitively large effort.