Students Travel App

Created by team STA- app on March 03, 2023

With a large and growing market opportunity, we are confident in the success of our business. This app is designed to target the student community globally, providing an innovative and rewarding way for students to save up for travel using their travelfund wallet. while enjoying social, educational and physical activity. With users digital Wallet, users will store, manage, and transact their travelfunds. Travelfunds will support multiple currencies, making it easy for users to convert their funds to the local currency when they travel to a new country and the transactions will be secure transactions using advanced security features, such as encryption and multi-factor authentication, to protected from fraud. Loyalty program integration from airlines, hotels, and other travel-related businesses, which we would build, will allow users to earn and redeem rewards easily. We have a well designed action plan for acquiring 2 million users in just six months. This includes Student travel App University Tours to partner with schools, user generated content from travelogue while co-gaming and co-studying, influencer marketing, referral programs and SEOS. The app is to track and monitor the reward system's performance, including the number of travelfund earned and redeemed, to evaluate its effectiveness. We are yet to set up a backend database and APIs but we have system for users to earn rewards and redeem them. The co-studying feature is to enable users to connect with other students who are studying similar subjects, creating study groups and facilitating peer-to-peer learning. Users can earn travel credits by participating in study groups and helping others with their studies. The app is to also organize virtual study sessions and provide access to online resources such as study materials, practice tests, and educational videos.

Category tags:

Explore more applications


We attempted to instill the deterministic, rule-based reasoning found in ELIZA into a more advanced, probabilistic model like an LLM. This serves a dual purpose: To introduce a controlled variable in the form of ELIZA's deterministic logic into the more "fuzzy" neural network-based systems. To create a synthetic dataset that can be used for various Natural Language Processing (NLP) tasks, beyond fine-tuning the LLM. [ ] [ ] ELIZA Implementation: We implemented the script meticulously retaining its original transformational grammar and keyword matching techniques. Synthetic Data Generation: ELIZA then generated dialogues based on a seed dataset. These dialogues simulated both sides of a conversation and were structured to include the reasoning steps ELIZA took to arrive at its responses. Fine-tuning: This synthetic dataset was then used to fine-tune the LLM. The LLM learned not just the structure of human-like responses but also the deterministic logic that went into crafting those responses. Validation: We subjected the fine-tuned LLM to a series of tests to ensure it had successfully integrated ELIZA's deterministic logic while retaining its ability to generate human-like text. Challenges Dataset Imbalance: During the process, we encountered issues related to data imbalance. Certain ELIZA responses occurred more frequently in the synthetic dataset, risking undue bias. We managed this through rigorous data preprocessing. Complexity Management: Handling two very different types of language modelsโ€”rule-based and neural network-basedโ€”posed its unique set of challenges. Significance This project offers insights into how the strength of classic models like ELIZA can be combined with modern neural network-based systems to produce a model that is both logically rigorous and contextually aware.


LlamaIndexLlama 2
application badge

Auto Recruit

Our platform revolutionizes recruitment with personalized experiences for candidates and streamlined processes for employers. Challenges with traditional recruitment system are: 1. TIme consuming 2. Screening Hassles 3. Inconsistent result 4. In effective methods Solutions - AutoRecruit AI is a comprehensive and cutting-edge solution to these problems. It puts the candidate at the center of its process and applies a breakthrough llama-based algorithmic approach to achieve unprecedented accuracy at speeds that haven't been seen before! Features 1. Candidate sourcing 2. Resume parsing 3.Candidate scoring and summary 4. Personalized Engagement Benefits 1. Time Saving 2. Cost-Effective 3. Efficiency Optimization 4. Better Candidate Fit

AutoHire AI

LangChainLlama 2

Visionary Plates

Visionary Plates: Advancing License Plate Detection Models is a project driven by the ambition to revolutionize license plate recognition using cutting-edge object detection techniques. Our objective is to significantly enhance the accuracy and robustness of license plate detection systems, making them proficient in various real-world scenarios. By meticulously curating and labeling a diverse dataset, encompassing different lighting conditions, vehicle orientations, and environmental backgrounds, we have laid a strong foundation. Leveraging this dataset, we fine-tune the YOLOv8 model, an architecture renowned for its efficiency and accuracy. The model is trained on a carefully chosen set of parameters, optimizing it for a single classโ€”license plates. Through iterative experimentation and meticulous fine-tuning, we address critical challenges encountered during this process. Our journey involves overcoming obstacles related to night vision scenarios and initial model performance, with innovative solutions like Sharpening and Gamma Control methods. We compare and analyze the performance of different models, including YOLOv5 and traditional computer vision methods, ultimately identifying YOLOv8 as the most effective choice for our specific use case. The entire training process, from dataset curation to model fine-tuning, is efficiently facilitated through the use of Lambda Cloud's powerful infrastructure, optimizing resources and time. The project's outcome, a well-trained model, is encapsulated for easy access and distribution in the '' file. Visionary Plates strives to provide a reliable and accurate license plate detection system, with the potential to significantly impact areas such as traffic monitoring, parking management, and law enforcement. The project signifies our commitment to innovation, pushing the boundaries of object detection technology to create practical solutions that make a difference in the real world.

AI Avengers


Business Llama

๐Ÿ“ฃ Exciting News from Business Llama! ๐Ÿ“ˆ ๐Ÿš€ We're thrilled to introduce "Business Llama: Optimized for Social Engagement," our latest project that's set to transform the way you approach business planning and go-to-market (GTM) strategies. ๐ŸŒŸ ๐Ÿค– With the power of advanced, fine-tuned models, driven by the renowned Clarifai platform, we're taking your business strategies to the next level. Here's what you can expect: ๐ŸŽฏ Enhanced Decision-Making: Make smarter, data-driven decisions that lead to business success. ๐Ÿ“Š Improved Business Plans: Develop robust and realistic plans backed by deep insights. ๐ŸŒ Optimized Go-to-Market Strategies: Reach your target audience more effectively than ever before. ๐Ÿ† Competitive Advantage: Stay ahead in the market by adapting quickly to changing conditions. ๐Ÿ’ฐ Resource Efficiency: Maximize resource allocation and reduce costs. ๐Ÿค Personalization: Tailor your offerings to individual customer preferences. โš™๏ธ Scalability: Apply successful strategies across various products and markets. ๐Ÿ›ก๏ธ Risk Mitigation: Identify and address potential risks proactively. ๐Ÿ”„ Continuous Improvement: Keep your strategies aligned with evolving market conditions. Join us on this journey to elevate your business game! ๐Ÿš€ Stay tuned for updates and exciting insights. The future of business planning and GTM strategies is here, and it's more engaging than ever. ๐ŸŒ๐Ÿ’ผ #BusinessLlama #SocialEngagement #DataDrivenDecisions #Clarifai #GTMStrategies

Team Tonic

ClarifaiLlama 2OpenAIVercelCohere
application badge

Lec2Learn - Finetuning AI Models

We present our solution Lec2Learn that works on Finetuning open source learning data for providing learning objectives. We start by obtaining all textbooks from opentextbookbc, we Process HTML to obtain the lecture and learning objectives, We then have pairs of lectures with their corresponding question groups, On the server we use Microsoft Phi 1.5 model and we fine tune it, We fine tune on the opentext data which is used so that model gets better at generating learning objectives, For the Prompt we give the lecture and learning objectives, we always start with Describe so model does not generate random data.



"Your project seems to be an innovative and practical solution for students who want to save up for travel while enjoying social, educational, and physical activities. The app's features, including the ability to store and manage travel funds, support multiple currencies, and secure transactions, are impressive. The inclusion of loyalty program integration and co-studying features are also thoughtful additions that will likely appeal to students. Your action plan for acquiring 2 million users in just six months through various strategies such as University Tours, influencer marketing, and referral programs shows a well-designed and feasible plan. However, more information is needed regarding the back-end database and APIs. Overall, your project has great potential to succeed in the market and provide value to its users"


Theodoros Ampas

Co-Founder of Content-Hive