Google Summer of Code 2023

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Jina AI has been selected as one of 19 organizations in Infrastructure and Cloud for Google Summer of Code 2023! GSoC is an open source internship program offering paid remote work.

Almost anyone in the world over 18 years of age who loves coding and wants to explore the incredible world of open source can join us as a GSoC 2023 contributor.

🎥 In our GSoC x Jina AI webinar, our mentors presented their projects in depth and answered questions people had about the project requirements, find the recording here, and here Is the slides.

This page contains a list of potential project ideas that we want to develop during GSoC 2023. If you would like to apply as a GSoC contributor, please follow these steps to get started:

1. Read through this page and the Google Summer of Code guides,
2. Identify, or come up with your own project ideas on Issues.
3. Fill out the survey so that we can know you better.
4. Please Introduce yourself in #introductions channel in our Slack community.
5. Join #gsoc-support channel to public communicate with potential mentors.
6. We have a proposal template to help ensure you include all information we expect. All applications must be submitted through Google's application system from March 20 to April 4.

For details and rules of GSoC, please read the GSoC Manual, Timeline, and GSoC FAQs.

🔎 Who are we?

Welcome to the GSoC projects page of Jina AI!

Jina AI provides a powerful platform for building neural-search, generative AI services with cloud-native technology, and we are thrilled to participate in Google Summer of Code (GSoC) this year. Our goal is to provide students with opportunities to work on real-world, cutting-edge projects and contribute to the growth of our community.

We are firm supporters of open source and have open sourced multiple projects, including:

• Jina is a MLOps framework that empowers anyone to build multimodal AI services via cloud native technologies. It uplifts a local PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer. Check out the documentation!

• DocArray is a library for nested, unstructured, multimodal data in transit, including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, embed, search, recommend, store, and transfer multimodal data with a Pythonic API. and DocArray is now hosted under the Linux Foundation AI & Data. Check out the documentation and roadmap!

💡 Project ideas

Title	Skills needed	Mentors	Difficulty	Size
Build Executor (model) UI in jina	Python	@Alaeddine Abdessalem, @Philip Vollet	Easy	175 hours, Medium
DocArray wrap ANN libraries	Python, ANN Search experience	@Johannes Messner, @Sami Jaghouar, @Philip Vollet	Medium	175 hours, Medium
Research about deploying LLM with Jina	Python, Pytorch, CUDA, docker, Kubernetes	@Alaeddine Abdessalem, @Joan Martínez	Medium	350 Hours, Large
Expand ANNLite capabilities with BM25 to build Hybrid Search	Python, C++, Lucene, ANN, Inverted Index	@Felix Wang, @Joan Martínez, @Girish Chandrashekar	Hard	350 hours, Large
Make ANNLite the go-to Vector Search library to be scaled by Jina using the StatefulExecutor feature	ANN, C++, Python, Databases	@Felix Wang, @Joan Martínez	Hard	350 Hours, Large
JAX support in DocArray v2	Python, AI/ML, JAX Framework experience	@Sami Jaghouar	Hard	175 hours, Medium

🧬 Project idea X: Your own idea!

If you have any ideas of your own, Please feel free to use Issues to draft your project ideas, ask questions, and collaborate. Project ideas need to be approved by the instructor before they can be formally accepted.

Project idea template

1. Title
2. Summary: Short Project Description
3. Expected outcomes
4. Desired skills
5. Details
	- Skill needed
	- Project size
	- Difficulty level
	- Mentor: Email address
	- Suggested by: Person who suggested the idea

🤙 Contact

• GitHub: Please use Issues to comment on project ideas, ask questions and collaborate.

• Slack: We have our own Slack Community for communication.

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🎓 What you will get

As a contributor in Jina AI's GSoC program, you will have the opportunity to:

1. Gain hands-on experience with real-world projects and technologies in the field of search and AI.
2. Work with a mentor from the Jina AI who will support and guide you throughout the program.
3. Upon successful project completion, get invited as a speaker for our community events.
4. Regular feedback and help on your efforts, including blogposts, with quick responses from us
5. Develop your technical skills, including software development, machine learning, and open-source contributions.
6. Build your professional network and make connections with other students, developers, and experts in the field.
7. Receive a stipend from Google for your participation in the program.

📝 How to improve your chances of being accepted?

The best way to increase your chances of being accepted as a Jina AI GSoC student is to start contributing now. Read up on Jina's contribution documentation and make yourself known to the other contributors by your contributions (Preferably related to your proposal area). This way, when it comes time to evaluate student applications, you will be a recognized individual and more likely to receive the attention you need to develop a successful proposal.

We are looking for candidates who can demonstrate that they can work independently on a project. We are here to help, but we cannot monitor your progress every step of the way. Therefore, it is important to show us your motivation. Being active before the submission process is the best way to demonstrate this.