IBM Data and AI Ideas Portal for Customers


This portal is to open public enhancement requests against products and services offered by the IBM Data & AI organization. To view all of your ideas submitted to IBM, create and manage groups of Ideas, or create an idea explicitly set to be either visible by all (public) or visible only to you and IBM (private), use the IBM Unified Ideas Portal (https://ideas.ibm.com).


Shape the future of IBM!

We invite you to shape the future of IBM, including product roadmaps, by submitting ideas that matter to you the most. Here's how it works:


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Start by searching and reviewing ideas and requests to enhance a product or service. Take a look at ideas others have posted, and add a comment, vote, or subscribe to updates on them if they matter to you. If you can't find what you are looking for,


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Post ideas and requests to enhance a product or service. Take a look at ideas others have posted and upvote them if they matter to you,

  1. Post an idea

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  3. Get feedback from the IBM team to refine your idea


Specific links you will want to bookmark for future use

Welcome to the IBM Ideas Portal (https://www.ibm.com/ideas) - Use this site to find out additional information and details about the IBM Ideas process and statuses.

IBM Unified Ideas Portal (https://ideas.ibm.com) - Use this site to view all of your ideas, create new ideas for any IBM product, or search for ideas across all of IBM.

ideasibm@us.ibm.com - Use this email to suggest enhancements to the Ideas process or request help from IBM for submitting your Ideas.

IBM Data & AI Roadmaps (http://ibm.biz/Data-and-AI-Roadmaps) - Use this site to view roadmaps for Data & AI products.

IBM Employees should enter Ideas at https://hybridcloudunit-internal.ideas.aha.io/


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Watson Studio (Deploy)

Showing 37

virtual deployment

A large CPD customer from Taiwan have about 2000 GPU nodes using Slurm to running Kubernetes for AI jobs now, They plan to build CP4D on another stand alone cluster. They want CP4D utilize the GPU cluster but no need brake out existing mechanism.
over 3 years ago in Watson Studio (Deploy) 0 Planned for future release

Add class labels to model metadata

Classification models can usually predict the probabilities per class. One probability number per known class. The model metadata in WML does not include the list of class labels seen in training. This makes it difficult for a scoring application ...
about 3 years ago in Watson Studio (Deploy) 1 Future consideration

Add Form POST support for web services

Taken from https://github.ibm.com/PrivateCloud/support/issues/716 attempt to call Python web service with file_upload() or any multi-part form POST call fails with web service error [call should invoke Python method] [customer is uploading i...
about 3 years ago in Watson Studio (Deploy) 0 Future consideration

project update n-1

WML fails to update n-1 project version while updating project from "From File" option even though it recognized new changes. ref case # TS004326688 The workaround is to uninstall the whole project and install again or to manually copy files into ...
over 2 years ago in Watson Studio (Deploy) 0 Planned for future release

Allow users to check CUH of Machine Learning by themselves.

-Use a real-life scenario to explain the problem statement/pain points, Customers can't check how many CUH they are using for Machine Learning. -state your current workaround(s), state any proposed solution(s), Keep a memo how many hours they u...
over 4 years ago in Watson Studio (Deploy) 0 Functionality already exists

Provide a detailed listing of differences between CLI, Python Client and UI screens

CLI, Python Client and UI screens differ in terms of maturity and capabilitie. It’s frustrating to start working with one of the tools and find out that the tool doesn’t yet have the capabilities you require, and then you have to switch to anothe...
over 4 years ago in Watson Studio (Deploy) 1 Future consideration

Publish WML performance statistics in the documentation

Latency and performance are key considerations when architecting systems to interact with machine learning models. Understanding the performance I can expect, and any limitations of services I am using is important as this information enables me t...
almost 5 years ago in Watson Studio (Deploy) 0 Planned for future release

Provide better documentation on model (re)deployment lifecycle

There are some gaps in the WML documentation, for example: REST/Streaming API If the above answer is no, how can we achieve this using other IBM Cloud services such as API Connect? How can a model be redeployed without downtime? How can a m...
almost 5 years ago in Watson Studio (Deploy) 0 Planned for future release

Add functionality to export tensorflow (and keras) models as tensorflow.lite and tensorflow.js to support running on devices and in the browser

Tensorflow.lite allows running models on devices rather than having to use server side apis. Similarly, it would be great if we could export tensorflow.js code. This is similar in concept to Core ML but Core ML only supports ios.
almost 5 years ago in Watson Studio (Deploy) 0 Not under consideration

Add WML credentials a la 'Insert to Code'

Insert to code functionality is great to enable quick access to data - I should be able to do the same thing for Watson services (e.g. WML, Image Recogniton) to quickly add credentials to these services into my notebook, without having to go to th...
almost 5 years ago in Watson Studio (Deploy) 0 Not under consideration

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