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).


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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,

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


ADD A NEW IDEA

My ideas: watsonx.ai

Showing 13

Keep and maintain at least 2 or 3 Python and R runtime versions in each release of CP4D

Multiple companies and industries work with CP4D for data science models. These models use multiple versions of Python or R runtimes and different open-source libraries that are compatible with the runtime version used to build the model. Clients ...
7 months ago in watsonx.ai 1 Not under consideration

Email notification after job finished (successfully/unsuccessfully)

The email would be sent after job finished , one can see whether everything is ok, or has to rerun scheduled scripts.
over 5 years ago in watsonx.ai 0 Not under consideration

Allow auto-save to be turned on/off not only at pipeline level, but also at project level

Many of our users tend to open multiple tabs when editing pipelines and we are concerned that they may be inadvertently overwriting themselves. We'd like the ability to disable auto-save at the project level and not just within a single pipeline.
6 months ago in watsonx.ai 0 Not under consideration

The number of input variables that Auto-AI can consider is limited.

Currently, Auto-Ai does not support Spark run-time at the back end, resulting in slowness while Model development using Auto-AI The number of input variables that Auto-AI can consider is also limited. Customer has a model with almost 324 input var...
over 1 year ago in watsonx.ai 1 Not under consideration

Remove size limit while exporting projects from UI

Remove size limit while exporting projects from UI. This will help data stewards manage there projects multiple env's. Our business users will not have access to CPDCLI and should be able do through UI. Business users works projects in TEST Env an...
9 months ago in watsonx.ai 2 Not under consideration

Adding support for pyton-shiny

Deployment of shiny applications written in R language is already supported,https://www.ibm.com/docs/en/cloud-paks/cp-data/4.8.x?topic=deployments-deploying-shiny-apps But a new version of shiny is released that is based on python. https://shiny.p...
12 months ago in watsonx.ai 0 Not under consideration

Extend policy and rule enforcement to Watson Studio

Policies and rules defined in the Knowledge Catalog do not extend to Watson Studio. The benefits of the catalog are the ability to quickly serve data teams assets from across the organisation to enable self-service analysis, "making data a trusted...
over 6 years ago in watsonx.ai 0 Not under 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...
over 6 years ago in watsonx.ai 0 Not under consideration

Add a recycle bin to Cloud Pak For Data user interface

In Cloud Pak for Data assets can be deleted in Projects, Catalogs, Spaces, ... Once they are deleted, you can no longer restore them via the user interface. However, using the Watson Data API there is the possibility to see, delete and restore all...
over 3 years ago in watsonx.ai 0 Not under consideration

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 model ...
over 6 years ago in watsonx.ai 0 Not under consideration

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