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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:


Search existing ideas

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,


Post your ideas

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

  2. Upvote ideas that matter most to you

  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 Employees should enter Ideas at https://ideas.ibm.com


ADD A NEW IDEA

Openscale

Showing 14

To include unsupervised (clustering) models to Watson Openscale/ Trust

To include unsupervised (clustering) models to Watson Openscale/ Trust
9 months ago in Openscale 0 Future consideration

Interactive Elastic Distributed Training notebook in Watson Studio

Watson Machine Learning Accelerator Elastic Distributed Training (EDT) simplifies the distribution of training workloads for the data scientist. Deep learning experiment in Watson studio provide the UI to submit job in WMLA , but this is not inter...
over 2 years ago in Openscale 0 Future consideration

Tensorboard support on job monitoring

TensorBoard is TensorFlow’s visualization toolkit enables tracking metrics like loss and accuracy, visualize the model graph, view histograms of weights, biases, or other tensors as they change over time, and much more. A managed TensorBoard suppo...
over 2 years ago in Openscale 0 Future consideration

Grafana / Prometheus GPU metric in CP4D

It would be nice to have the GPU utilization metrics used in WMLA also introduced to the main monitoring dashboard of core CP4D. This is so that we still have a single monitoring dashboard for all services of CP4D.
over 2 years ago in Openscale 0 Future consideration

whether to automate elimination of permission to "group" in jupyter notebook files

During the creation of instance group and notebooks the file permissions are 660 giving access to the group to be able to copy data to their notebook environment.
over 2 years ago in Openscale 0 Future consideration

fabric files for both x86 and ppc64le on Same Cluster if HPO Models are running on

https://jazz07.rchland.ibm.com:21443/jazz/web/projects/pc-management#action=com.ibm.team.workitem.viewWorkItem&id=266399 Customer will be purchasing more x86 nodes shortly to add to cluster. Customer needs permanent solution
over 3 years ago in Openscale 0 Future consideration

WMLA EDT: Customization, Minimal Example & Documentation

Client asks how to use and customize the elastic distributed training (EDT) feature of WML-A. They explicitly complained about the lack of a detailed documentation (being aware of WMLA/Spectrum Conductor documentation in the knowledge center &...
over 3 years ago in Openscale 0 Future consideration

Power architecture - Pyarrow & RAPIDS latest packages

Please refer the support ticket- TS004247707 for details
over 3 years ago in Openscale 1 Future consideration

Open to allow WMLA user to add their own algorithms

Our team would like to try WMLA EDT to train model using most up to date, state of the art algorithm. However, these algorithm is not supported by WMLA. It will be best if WMLA allows users, who are data scientist, developer, or machine learning e...
over 3 years ago in Openscale 4 Future consideration

SELinux support for WMLA on Power

Customer is asking for SELinux support for WMLA on Power.
over 3 years ago in Openscale 1 Future consideration