The neon deep learning framework, once a bustling hub of machine learning activity by Intel, has officially reached its end-of-life stage. In this blog, we will explore what this means for its users, how to adapt, and potential paths forward for those who wish to continue developing or utilizing the framework.

Understanding neon’s Discontinuation

Intel has decided to discontinue support and updates for the neon framework. This decision indicates that Intel will no longer provide maintenance, bug fixes, or any new releases. Imagine owning a classic car that has great features but no longer receives parts from the manufacturer. While it can still run, finding replacement parts becomes a challenge. Similarly, users of neon may still utilize the framework but will have to rely on community members or their own skills to maintain it.

What to Do If You Still Need to Use neon

• Fork the Project: If you have the expertise or wish to stay engaged, consider forking the project. This allows you to maintain your own version and manage patches for the community.
• Seek Alternative Solutions: As neon is discontinued, exploring other frameworks might be beneficial. Frameworks like TensorFlow and PyTorch have active communities and robust support.

Getting Started with neon

For those who may want to carry on using neon independently, here’s a quick guide on how to get it installed:

bash
git clone https://github.com/NervanaSystems/neon.git
cd neon
make
. .venv/bin/activate

Installing via PyPI

As of version 2.4.0, you can also install neon using pip:

bash
pip install nervana-neon

Troubleshooting Tips

If you encounter any issues while using or installing neon, here are some tips to resolve common problems:

• Check the Compatibility: Ensure that your system’s libraries, such as Python version and required dependencies, meet neons specifications.
• Explore the Community: Join forums or communities where previous users might still be discussing or helping each other with neon related problems.
• Review Documentation: A complete documentation for neon is still available here.

For more insights, updates, or to collaborate on AI development projects, stay connected with fxis.ai.

Conclusion

At fxis.ai, we believe that such advancements are crucial for the future of AI, as they enable more comprehensive and effective solutions. Our team is continually exploring new methodologies to push the envelope in artificial intelligence, ensuring that our clients benefit from the latest technological innovations.