# The roadmap of 2024

**URL:** <https://community.konduit.ai/t/the-roadmap-of-2024/3181>\
**Category:** DL4J\
**Created:** [June 24, 2024, 1:26pm UTC](https://community.konduit.ai/t/the-roadmap-of-2024/3181 "2024-06-24T13:26:27Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![yimlin](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/yimlin/32/1294_2.png) [@yimlin](https://community.konduit.ai/u/yimlin)\
**Post date:** [June 24, 2024, 1:26pm UTC](https://community.konduit.ai/t/the-roadmap-of-2024/3181/1 "2024-06-24T13:26:27Z")

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As the title, I’d like to know the roadmap for dl4j this year.  
can we get the V1.0.Releaase of dl4j?

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**Author:** ![agibsonccc](https://yyz1.discourse-cdn.com/flex035/user_avatar/community.konduit.ai/agibsonccc/32/697_2.png) [@agibsonccc](https://community.konduit.ai/u/agibsonccc)\
**Post date:** [June 26, 2024, 2:10am UTC](https://community.konduit.ai/t/the-roadmap-of-2024/3181/2 "2024-06-26T02:10:28Z")

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@yimlin I’ll be breaking this PR up in to a set of fixes:

> <https://github.com/deeplearning4j/deeplearning4j/pull/10052>
>
> \## What changes were proposed in this pull request?
> 
> (Please fill in changes p…roposed in this fix)
> 
> \## How was this patch tested?
> 
> (Please explain how this patch was tested. E.g. unit tests, integration tests, manual tests)
> 
> \## Quick checklist
> 
> The following checklist helps ensure your PR is complete:
> 
> \- \[\] Eclipse Contributor Agreement signed, and signed commits - see \[IP Requirements\](https://deeplearning4j.konduit.ai/multi-project/how-to-guides/contribute/eclipse-contributors) page for details
> \- \[\] Reviewed the \[Contributing Guidelines\](https://github.com/eclipse/deeplearning4j/blob/master/CONTRIBUTING.md) and followed the steps within.
> \- \[\] Created tests for any significant new code additions.
> \- \[\] Relevant tests for your changes are passing.

I’ve been mainly working on fixing regressions and adding new features for easier debugging.

My main goal will be to add a new llamacpp backend to make LLMs faster.  
I’ll also be updating the cuda versions.

Overall, dl4j as a framework going forward will be simpler. There’s been a lot of feature creep over the years and other frameworks dominate the industry.

Focusing more on being an easy to use framework that can run models people expect at a performance they expect will be the baseline going forward.