Hackathon Overview
Hackathon Overview
Taxi service form an integral part of Dubai's mobility scene, carrying over half a million people daily through its 12000 taxis. RTA is responsible for the smooth and safe operation of taxi, and aim to improve its public availability through technology-driven solutions. Alibaba Cloud together with RTA in this hackathon to develop innovative AI-driven solutions for further improvement of taxi services in Dubai. Topic not limited in below suggestions:
Optimizing Taxi Pick-up Points
Route Anomaly Detection
Smart Taxi Dispatch
Dynamic Taxi Ranks/Stands
Accident Hotspots
Taxi Charging Infrastructure

Prizes and Benefits

The final winners will get prizes including cash and Alibaba Cloud credits.

1st Prize: 1 Team
$3,000 USD Cash Prize(Pre-Tax)
$10,000 USD Alibaba Cloud Credits
Trophy and Certificate
GITEX 4-day Pass
Opportunity to participate Apsara Conference in China Hangzhou
Special Souvenirs & Global Exposure
2nd Prize: 2 Teams
$2,000 USD Cash Prize(Pre-Tax)
$5,000 USD Alibaba Cloud Credits
Trophy and Certificate
GITEX 4-day Pass
Special Souvenirs & Global Exposure
3rd Prize: 3 Teams
$1,000 USD Cash Prize(Pre-Tax)
$3,000 USD Alibaba Cloud Credits
Trophy and Certificate
GITEX 4-day Pass
Special Souvenirs & Global Exposure

Schedule for Participants

  • 27th Aug - 20th Sep
    Registration
  • 1th Oct - 4th Oct
    Online Alibaba Training
  • 8th Oct - 10th Oct
    Onsite Coding & Hacking
  • 17th Oct
    Awards Ceremony

How to Join?

Please follow the steps below to register for the hackathon.

Register for the Hackathon

Follow the step to finish the registration for hackathon by 6th Sept.

Create an Alibaba Cloud Account

A valid Alibaba Cloud account is required to activate required Alibaba Cloud products, and to receive Alibaba Cloud credits for the hackathon.

Online Training

Participate the online training to get the basic knowledge of Alibaba Cloud and be well-prepared for on-site coding.

On-site Coding & Presentation

Participate the on-site coding as a team and complete your projects submission by Sept 28th 7pm. Team presentation will be on 29th and top 3 winner will be selected in the following week.

Awards Ceremony

All the team will be invited to GITEX AI Summit and witness the awards ceremony. Top 3 winner will present your projects to GITEX audience.

Judging Criteria

Judging Criteria
All the projects submitted will be reviewed by judges on-site on 8th March with the criteria below.

Technical Implementation

    It evaluates the technical excellence of the solution, with a special emphasis on AI integration, and the quality and efficiency of the AI implementation. The use of AI should enhance the solution's capabilities, demonstrating innovation and effective problem-solving. The assessment will look for robustness, scalability, and adherence to AI best practices.

Feasibility of Solution

    This criterion evaluates the practicality and integration of the solution within RTA’s operational framework in Dubai. It examines how well the solution aligns with existing systems and processes, its ease of implementation, and its ability to scale effectively. The focus is on the solution’s usability, its adaptability to current technologies, and its capacity to handle future growth or increased demand.

Impact of the Solutions

    This criterion measures the overall effectiveness of the solution in terms of return on investment (ROI) and its contribution to enhancing the quality of life for Dubai's residents. It considers the balance between implementation effort and benefits, as well as improvements in convenience, safety, and user satisfaction with taxi services.

Innovation and Creativity

    It focus on the originality and imaginative aspects of the solution, and looks for novel ideas and approaches, evaluating the project's ability to introduce new concepts or propose unique solutions to existing challenges. The inventive use of technology, the originality of the design, and the project's capacity to stand out from conventional solutions are key components.

Usage of Alibaba Cloud

    It evaluates the integration and use of Alibaba Cloud products within the project, particularly PAI, AnalyticDB and other recommended services. Projects are expected to demonstrate the use of Alibaba Cloud's services, taking advantage of their specific features to optimize the solution, and showcasing the benefits of incorporating these products into the technological stack.

Meet Our Mentors and Judges

Dr. Salim Alkaabi

Acting Director of Technology Strategy and Governance

Mr. Khaled Al Awadi

Director of Transportation Systems Department

Mandana Al Obeidli

Director, Innovation & Pioneering

Dr. Kushnazarov Farruh [Mentor]

Senior Data Scientist, Alibaba Cloud Intelligence

Haoran Wang [Mentor]

Chief Data Intelligence Architect, Alibaba Cloud Intelligence

Yong Zhou [Mentor]

Senior Solution Architect, Alibaba Cloud Middle East, Africa & Turkey

Dr. Salim Alkaabi

Acting Director of Technology Strategy and Governance

Mr. Khaled Al Awadi

Director of Transportation Systems Department

Mandana Al Obeidli

Director, Innovation & Pioneering

Dr. Kushnazarov Farruh [Mentor]

Senior Data Scientist, Alibaba Cloud Intelligence

Haoran Wang [Mentor]

Chief Data Intelligence Architect, Alibaba Cloud Intelligence

Yong Zhou [Mentor]

Senior Solution Architect, Alibaba Cloud Middle East, Africa & Turkey

Learning Resources

This article describes how to create a RAG service using Compute Nest with LLMs on PAI-EAS, AnalyticDB for PostgreSQL as the vector store, Gradio for ... Learn more
This article discusses the seamless integration of Llama 2 models on Alibaba Cloud's PAI-EAS platform, which offers significant speed boosts and cost savings for users through PAI Blade. Learn more
Explore the integration of AnalyticDB for PostgreSQL with large language models on Alibaba Cloud's PAI platform, empowering businesses with efficiency. Learn more
Explore the integration of AnalyticDB for PostgreSQL with large language models on Alibaba Cloud's Compute Nest, empowering businesses with efficiency. Learn more
Explore the integration of AnalyticDB for PostgreSQL with large language models on Alibaba Cloud's Compute Nest, empowering businesses with efficiency. Learn more
Explore the integration of AnalyticDB for PostgreSQL with large language models on Alibaba Cloud's PAI, empowering businesses with efficiency. Learn more
This article introduces Compute Nest, a comprehensive cloud integration Platform-as-a-Service (PaaS) solution. Learn more
In this article, we will explore how you can create your own GenAI model without the need for costly investments or extensive time commitments. Learn more
In this tutorial, we will explore the rapid deployment of AI painting with stable diffusion WebUI using Alibaba Cloud's PAI-EAS. Learn more
This article introduces Alibaba Cloud PAI, a platform that combines AI capabilities with Langchain and LLM to revolutionize the field of Generative AI. Learn more
This article provides a comprehensive guide on deploying a large language model (LLM) application using the Platform for AI - Elastic Algorithm Service. Learn more
This topic describes how to deploy the open source Kohya_ss and train a Low-Rank Adaptation (LoRA) model by using the Kohya_ss in the Elastic Algorithm Service (EAS) of Platform for AI (PAI). In AI painting scenarios, you can apply the trained LoRA model in the Stable Diffusion (SD) service as an auxiliary model to improve the SD painting performance. Learn more
Stable Diffusion is an open source text-to-image diffusion model that can generate images based on text prompts. You can use Elastic Algorithm Service (EAS) to deploy a Stable Diffusion model as an AI-powered web application, and use the deployed application to perform model inference and generate images. Learn more
You can use Elastic Algorithm Service (EAS) to deploy a web application for AI video generation based on ComfyUI and Stable Video Diffusion models. You can quickly implement an AI-powered text-to-video solution that helps you complete tasks such as generating short videos or animation on social platforms. This topic describes how to deploy an AI video generation application, related inference services and answers to FAQ during the deployment. Learn more
You can use a vector database as a dedicated enterprise knowledge base to perform vector search, and perform model inference based on large language models (LLMs) in Elastic Algorithm Service (EAS) of Machine Learning Platform for AI (PAI). You can also use the open source framework LangChain to integrate vector search and model inference into your business by using EAS to achieve optimized inference results. This topic describes how to use PAI and a vector database to implement intelligent dialogue based on LLMs. Learn more
You can use Elastic Algorithm Service (EAS) of Platform for AI (PAI) to deploy a large language model (LLM) as an AI-powered web application. After you deploy the model, you can call the application by using the web UI or API operations. You can also use the LangChain framework to integrate enterprise knowledge base to implement intelligent conversation and automation capabilities. EAS also provides BladeLLM and vLLM inference acceleration engines that support high concurrency and low latency. Learn more
The model deployment section below has Elastic Algorithm Service (EAS) which houses the deployment models already available and acts as a platform to deploy the customized models created by the users. Learn more
Our ultimate purpose is to mount this OSS image dataset to the DSW instance and enable the usage of the dataset the same way I used in the standalone . Learn more

Supporting Partners

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