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TAU CS Student Club is proud to announce its fourth annual hackathon!
HACKADEMIA
Ever since the release of ChatGPT in 2022, LLMs and other AI have boomed into a global industry and have become an integral part of our day-to-day life. Who, better than us students, would know how important AI has become in work, entertainment, and especially, learning and education.
In this years' hackathon, we will focus on revolutionizing learning and education through the use of AI, bridging the gap between "AI assistant" and "AI educator".
THE CHALLENGE
Adapting to Rapid Technological Change
Accessible Lifelong Learning: Develop flexible, practical training programs to help learners stay current with evolving technologies.
Continuous Workforce Upskilling: Implement ongoing development initiatives that equip employees with the latest industry tools and knowledge, ensuring their skills remain relevant.
Equitable Access to Education
Assistive Technologies for Learners with Disabilities: Provide customized learning aids, such as screen readers or adaptive interfaces, to accommodate different needs.
Reaching Economically and Geographically Disadvantaged Learners: Address individuals who, due to their remote location or limited resources, often do not have the same educational opportunities as those in more central or affluent areas.
Educators’ Challenges
Time-Intensive Grading: Address the prolonged effort of evaluating student work to free educators for more direct engagement and support.
Ensuring No Student Falls Behind: Implement strategies to monitor understanding and progress, intervening early to keep the entire class on track.
Personalized Adaptive Learning
Tailored Approaches for Diverse Learning Paces and Styles: Implement flexible strategies and resources that adjust to each individual’s speed, preferences, and strengths.
Adaptive Assessment Tools: Utilize real-time evaluation methods that adapt questions and tasks based on a learner’s performance, helping to identify and address gaps promptly.
Making Learning Engaging and Enjoyable
Gamification (e.g., Duolingo): Boost motivation and retention by incorporating rewards, levels, and challenges into educational experiences.
Hands-On, Real-World Projects: Introduce scenario-based tasks, real-life case studies, and collaborative activities to help learners apply concepts and maintain enthusiasm.
Creative Road
For those ideas worth pursuing which don't fall into any of the above categories.
DETAILS
WHEN?
May 22-23
~30-hour event
WHERE?
Neiman Library of Exact Sciences and Engineering
Tel Aviv University
WHO?
All undergraduate students
(at least one TAU student in each team)
HOW?
You can register in groups of 3-5 students.
You may also sign up alone or as a pair, and we will match you up with a team!
PRIZES
This year, like in our previous hackathons, the winners will receive a monetary prize as well as the opportunity to continue expanding their idea with the guidance of the startup industry's foremost experts.
NEED TO KNOW
What is a Hackathon?
A collaborative event where people work together to develop innovative solutions to a specific problems. Usually, a hackathon lasts for 24 hours or more.
Who is this event for?
Most accepted participants come with some coding or design background, to make sure they can contribute to the event. If you believe you are able to contribute in another way, we encourage you to apply.
What to prepare before the event?
It's helpful to have an idea of what you want to do before the event, but if you don't, that's okay! The event is designed to give you plenty of time to think and come up with ideas.
Will we get any help?
Of course! We personally picked the brightest minds in the Israeli Hi-Tech industry to provide you with technical and professional guidance throughout the entire event.
What if I don't have a team?
No problem! You can register as a pair/individual and we will help you form a team.
Or join our WhatsApp to find potential teammates.
Any other questions?
Feel free to reach out to anyone on the team or contact us on hackcstau@gmail.com
RESOURCES
Here's a list of tools and databases we recommend you use during the event:
Bright Data
Bright Data is a global technology company that offers web data collection and proxy services.
Additionally, they offer a plethora of widely-used and verified datasets, many of which can be viewed and sampled with a free account HERE (under "Popular pre-built datasets"), as well as many which cannot be freely accessed. If you find a dataset you would like to work with, which is not publicly accessible, make sure to ping us at hackcstau@gmail.com and we will assist you.
You can find their site HERE.
Open-Source Data
In addition to Bright Data's datasets and tools, there also exist many libraries and datasets which we recommend you to use:
Data.Gov: the official datasets of the government.
Central Bureau of Statistics: The official datasets of the Central Bureau of Statistics.
Data-IL: An open-source project for aggregating publicly available data.
GPT4All
GPT4All is a neat framework that optimizes inference on LLMs for use on personal computers, no GPUs needed!
They offer both an application with a built in GUI for running chats locally, and a python library for adding inference to your code.
Since you will be running the models locally, GPT4All requires you download them to your local machine. We recommend using some of the optimized models defined by GPT4All, however it is also compatible with the HuggingFace CLI (described below) opening up many more possibilities.
You can find the application installation HERE and their GitHub repository HERE.
HuggingFace
HuggingFace is a free database of various AI models to download and run locally on your machine. Whether you choose to run them with GPT4All or directly, there is a large variety of models which will fit your needs.
You can find the website HERE.
LangChain & Langroid
LangChain and Langroid are frameworks for building LLM powered applications, especially agents.
Each offers support for LLM tool use, API integration and other capabilities.
We reccomend Langroid, since it is more lightweight and should be simpler to learn, however, Langchain should be more robust and capable.
Langroid: GITHUB
Our Partners
In Collaboration with:
