Grant Application: Google TensorFlow API Bindings for Perl, Phase 2

Category: Grants , Perl 5 Development , Projects

Comments (26)

The Perl TensorFlow grant proposal presents an extraordinary opportunity to revolutionize the capabilities of Perl in the realm of artificial intelligence and machine learning. With a budget of $8,800 USD, this grant aims to enhance the existing Perl API to Google TensorFlow, enabling the Perl community to compete effectively with Python and Java, the current leaders in the AI domain.

Phase 1 of this grant series has already proven its worth, empowering Perl developers with a full-fledged AI solution and access to open source Jupyter notebooks for AI applications. Building upon this success, Phase 2 promises to expand Perl TensorFlow even further with four new system features, including gradient support and a Keras API, along with three cutting-edge AI applications like object recognition and reinforcement learning.

The benefits to the Perl community are immense. From simplifying convincing corporate management to adopt Perl for AI-driven projects to empowering educators and students with AI-focused courses, this grant paves the way for a brighter future. Moreover, it attracts AI developers to Perl, placing Perl on the TensorFlow recommended-language list and creating new job opportunities within the Perl ecosystem.

The proposed deliverables, including comprehensive Perl test suites, well-documented libraries, and publicly accessible Docker repositories, ensure a smooth and reliable implementation. With a project timeline of 4 to 5 months, the Perl TensorFlow grant aims to accomplish its mission effectively and efficiently.

As Perl strives to reclaim its position at the forefront of the technology landscape, this grant will elevate Perl's AI capabilities to rival the best in the industry. I believe that approving this grant will catalyze a significant transformation for Perl, enabling it to thrive in the rapidly evolving world of AI and cement its position as a top-choice programming language for modern software development.

Let's support this vision and propel Perl into a bright and successful future with the transformative Perl TensorFlow grant.

I support the funding of this proposal to further improve and complete the Google TensorFlow API Bindings for Perl. Having this would be very helpful for Perl such that it can be used effectively for many important business use cases and projects, given how AI applications are dominating attention and business investment these days.

I'm in support of this, it would be another great move forward for perl, providing more opportunities for startups and enterprise development increasing opportunities for perl AI developers and TensorFlow usage.

Dear Perl Foundation and the TensorFlow Grant Proposal Team,

I am thrilled to express my utmost support and enthusiasm for your groundbreaking collaboration between the Perl Foundation and TensorFlow. This remarkable initiative serves as a testament to the power of open-source innovation and the limitless possibilities that arise when talented communities come together.

By integrating TensorFlow, a cutting-edge machine learning framework, with Perl, a versatile and robust programming language, you are paving the way for a new era of data analysis and artificial intelligence. This collaboration holds immense potential to unlock novel solutions and drive advancements across a wide range of domains.

The Perl Foundation's commitment to fostering the growth and development of Perl, combined with TensorFlow's exceptional capabilities in machine learning, creates a powerful synergy that will undoubtedly propel the field forward. The grant proposal's emphasis on education, research, and community engagement further underscores the project's comprehensive approach and commitment to inclusivity.

The potential impact of this collaboration extends far beyond the boundaries of the Perl and machine learning communities. By enabling Perl developers to leverage TensorFlow's sophisticated tools and models, you are empowering a vast network of programmers to embark on exciting machine learning projects, democratizing access to this transformative technology.

Furthermore, the proposed mentorship programs and educational initiatives inspire confidence in the project's long-term sustainability and the cultivation of a vibrant ecosystem. Nurturing talent and knowledge sharing are crucial components in driving innovation, and your dedication to these aspects is commendable.

I wholeheartedly endorse this TensorFlow grant proposal for the Perl Foundation, recognizing its potential to break new ground, foster collaboration, and empower developers worldwide. The impact of this initiative will undoubtedly reverberate throughout the industry and contribute to the advancement of machine learning and Perl programming.

Wishing you every success in realizing this visionary project.

Yussuf arifin

So excited to hear about this development that I can hardly wait!
Perl has, for decades, been on the cutting edge of user-driven development. Even back before the CPAN module days we had integrations with everything from major commercial databases to Apache and beyond. Adding this support for ML makes a lot of sense and I think will produce benefits not only for Perl hackers but the world as a whole.
Thank you Will and Zaki for your work on this.

This is a great idea for Perl, considering the fact that there is a lot of work that needs to be done on ML API integrations in Perl. Perl AI developers and TensorFlow users will appreciate access to first-class integrations without being forced to move to other programming ecosystems. I believe that lowering the barrier to entry to ML for all Perl developers is a great idea. All the best of luck to Will and Zaki!

Perl is often not considered as a primary choice for new projects because of its lack of integration with modern technologies or frameworks. Bringing modern frameworks to Perl is a great idea! It could make Perl more competitive in the machine learning landscape. It makes Perl more accessible, versatile, and marketable, which could attract more developers and businesses to the language.
TensorFlow API bindings for Perl also opens up a world of possibilities for Perl developers who want to use machine learning in their applications, allowing them to learn modern technologies without switching to other languages.
Hope the funding is granted! Good luck Will abd Zaki!

one area where Perl has been lacking is in the realm of artificial intelligence (AI) and machine learning (ML). The absence of native support for AI frameworks like Google's TensorFlow has limited Perl's potential for exploring the cutting-edge possibilities of AI-driven applications. Nonetheless, the proposal to develop Google TensorFlow API bindings for Perl opens up new dimensions for the language, promising to usher in a new era of AI innovation within the Perl community.
Moreover, the inclusion of TensorFlow bindings in Perl will foster a thriving ecosystem of AI enthusiasts and researchers within the Perl community. With a broader toolkit at their disposal, developers will be encouraged to explore new possibilities and collaborate on innovative projects. This community-driven approach will not only facilitate knowledge-sharing but also accelerate the pace of AI research within the Perl ecosystem.
Hoping to grant the funding.

I support the continued implementation of TensorFlow and putting Perl "back on top". I support this grant proposal.

I was eagerly waiting to do development of AI using Perl. It'll definitely improve the visibility of Perl across software developer community as well as at enterprises level also. This move will encourage beginner to learn Perl and promote Perl for AI projects. I support this grant proposal and hoping to complete this soon. Thank you all for your hardwork to continue implementation of AI API using Perl.

Let's keep the Perl in flow. Today, and a few years ahead, AI is and will be the leading in the tech area. A lot of jobs will be at the same time lost and gained thanks to new AI related jobs. Perl will certainly benefit from having this API.

Will and Zaki, thanks for getting your time on this project.

I'm really excited about AI and I think TensorFlow is an exciting platform. I would love to program TensorFlow in Perl. Let's give it all the support we can.
I support this grant proposal.

I can't express just how important this project is. AI tooling is something Perl should totally own because it's exactly what Perl is great at; gluing all sorts of things together to build value. We have an opportunity to show the programming world Perl isn't just for legacy code, AI is just getting crazy hot and we have a good chance to ride the wave along with all the other things people are doing to modernize the language. I'm behind this project 100%

I would also like to voice my support of this project. Perl has long been used in a wide variety of endeavors and should firmly plant itself in the Machine Learning ecosystem.

It's a great engineering effort. Fans of the Perl will be happy to see this trend develop. I support this grant proposal and look forward this project reach to the set goals

This project can not only bring Perl's talent into ML field. Also make Perl great again, because students can have more opportunities using Perl for learning ML.

I am very excited about AI implementation in Perl, looking from future perspective this will surely benefit Perl community. I support this grant proposal.

I think the amount is pretty conservative for this essential work. Consider this a ++ endorsement and recommendation that we take this opportunity. This team has already proven they produce extremely high quality work!

Absolutely, Perl should adapt to accommodate new projects, as its current deficiency in integrating with modern technologies or frameworks hinders its widespread adoption. Embracing modern frameworks in Perl is undoubtedly a fantastic proposition!

This would be really cool feature for perl. This would be helpful for the application which are build using perl. Using this feature application became more flexible, user friendly. This feature also helpful for developer. AI/ML is now essential part for any application which will give new direction to perl and their developer. I support this proposal.

This grant application for Google TensorFlow API Bindings for Perl, is an impressive achievement and deserves high praise. The continued development of the Perl API for Google TensorFlow and the implementation of new features like gradient support, high-level library, TensorFlow Hub library, and Keras API are a significant step forward for the Perl community. The addition of three new TensorFlow applications such as object recognition, speech recognition, and reinforcement learning will enable Perl developers to create even more high-quality AI software, elevating Perl's competitiveness among other leading programming languages. This work contributes to radically changing the perception of Perl in the modern software development and AI industries. Congratulations to Will, Zakariyya, and the entire Perl TensorFlow team for their remarkable achievement!

I do agree that it is a good idea to have a complete implementation of the Tensorflow API.

This will undoubtedly be a valuable addition to Perl and I wholeheartedly support the grant proposal. Best of luck, Will and Zak.

I support this grant proposal. This will make Perl a more viable option for data engineering and ML work.

I want to see this project finished and have an api for tensor flow, so I can have the option to work and play with perl in IA and ML.

Perl TensorFLow is a great opportunity for the evolution of Perl in the field of machine learning and the whole AI movement. I fully support the development so that Perl is also a leader in this field as well as other programming languages.

I join my colleagues and want to say the following: as one of the tools, Perl TensorFLow is definitely needed. It is needed to gain experience, it is needed to integrate these solutions with something that already exists, and it is needed for possible solutions in the future.
I hope that on the basis of this tool, we, as developers and users, will already begin to receive useful utilities that exceed what was previously available in terms of capabilities.

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