FruitPunch AI’s Post

🇳🇵 यदि तपाईंले यो पढ्न सक्नुहुन्छ भने हामीलाई तपाईंको मद्दत चाहिन्छ 🇳🇵 (If you can read this we need your help 😉) 🔬 For our upcoming AI for Women Farmers Challenge we are looking for AI for Good Engineers with a very specific profile! 🇳🇵 In collaboration with Heifer International, we will digitize handwritten Nepali databases using AI. Specifically, we will be addressing Optical Character Recognition for Devanagari script, which is the script used for Nepali and some of the most spoken Indian languages such as Hindi. We are doing this to assist agricultural cooperatives in making better use of their data. We would greatly benefit from Nepali-speaking data scientists with expertise in OCR. 🦄🦄 We're aware that those are rare. But if you meet 𝐚𝐧𝐲 𝐨𝐧𝐞 of these requirements we can really use your help: - Nepali native / or roots - Proficient in reading Devanagari script - Experience with OCR for handwritten text The Challenge starts on the 2nd of July and will take 10 weeks to complete! Check out the Challenge on our platform and "Apply as an expert" for free if you meet one of the requirements. https://lnkd.in/eiBe8hKj If you know anyone who meets these requirements please connect them to our Challenge manager Dorian Groen Applications are officially open until the 30th of June, but we can make an exception if you can valuably contribute to the Challenge 😁 #AIforGood #AIforAgriculture #DataScience #SDG

🇳🇵🌾 𝐋𝐚𝐬𝐭 𝐜𝐚𝐥𝐥 𝐭𝐨 𝐣𝐨𝐢𝐧 𝐭𝐡𝐞 𝐀𝐈 𝐟𝐨𝐫 𝐖𝐨𝐦𝐞𝐧 𝐅𝐚𝐫𝐦𝐞𝐫𝐬 2 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞! 🌾🇳🇵 You can use your expertise in this Challenge designed to enhance agricultural practices in Nepal, benefiting both individual farmers and cooperatives. 🔍 𝐂𝐨𝐧𝐭𝐞𝐱𝐭 𝐨𝐟 𝐭𝐡𝐞 𝐏𝐫𝐨𝐛𝐥𝐞𝐦: In Nepal, agricultural data management faces significant hurdles due to its dependence on paper records. This challenge hinders farmers' and cooperatives' ability to make informed decisions, affecting their financial and agricultural productivity. Our goal is to digitize this system using computer vision and AI, offering digital solutions for a brighter, more sustainable future in agriculture. 𝐖𝐡𝐲 𝐄𝐧𝐠𝐚𝐠𝐞 𝐚𝐬 𝐚𝐧 𝐄𝐱𝐩𝐞𝐫𝐭? 𝐑𝐞𝐚𝐥-𝐖𝐨𝐫𝐥𝐝 𝐈𝐦𝐩𝐚𝐜𝐭: Make a tangible difference by translating and analyzing farmer loan data, which will lead to enhanced agricultural operations, improved financial strategies, and more sustainable farming approaches. 𝐒𝐤𝐢𝐥𝐥 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭: Collaborate with a diverse team, acquiring exceptional experience in applying AI to address real-world challenges. 𝐌𝐚𝐤𝐞 𝐚 𝐌𝐞𝐚𝐧𝐢𝐧𝐠𝐟𝐮𝐥 𝐃𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐜𝐞: Play a vital role in upgrading Nepal's agricultural data infrastructure, directly supporting the lives of those predominantly engaged in agriculture. 𝐖𝐡𝐨 𝐖𝐞 𝐍𝐞𝐞𝐝? We are in search of data scientists and AI engineers skilled in optical character recognition technology and language translation. Experience with the Nepali language and Devanagari script is a plus, though not required. 𝐃𝐚𝐭𝐚 𝐀𝐭 𝐘𝐨𝐮𝐫 𝐃𝐢𝐬𝐩𝐨𝐬𝐚𝐥 Access to: - Templates of loan documents. - Over 300 financial loan documents, both filled and unfilled. - Detailed farmer diaries and livestock documents outlining agricultural activities. 𝐋𝐚𝐮𝐧𝐜𝐡 𝐃𝐞𝐭𝐚𝐢𝐥𝐬 The challenge begins on July 2nd, with application submissions closing on June 30th. For more information and to apply, visit: https://lnkd.in/eiBe8hKj Not an expert? Join our mentorship track to test your skills and learn to apply AI in practice. Secure your spot today! 😄 https://lnkd.in/eiBe8hKj #AIForGood #AgricultureTechnology #DataScience #AIChallenge

🚀 Exciting Update on the AI for Women Farmers Challenge! 🌾 Last week, we successfully concluded the first phase of our initiative, focused on developing advanced AI tools to support women farmers. Here’s a brief overview of our achievements: 1️⃣ 🔍 Text Detection Model: Our model skillfully identifies and categorizes text within documents as either printed or handwritten, efficiently routing it to our OCR specialists for further processing. 2️⃣ 📖 Devenagari OCR Model: Employing a sophisticated sliding window technique, this model meticulously classifies each letter, assembling them into words ready for translation. 3️⃣ 🌍 Translation & NER Pipeline: This system is designed to not only translate text but also to extract meaningful information, enhancing our understanding of the document contents. In the second AI for Women Farmers Challenge, we're excited to enhance these models further and seamlessly integrate them into a comprehensive pipeline. 🤝 Join The Challenge: We’re inviting passionate individuals to contribute to this Challenge. Help us empower the agricultural cooperatives of Nepal by signing up here: https://lnkd.in/eiBe8hKj The next Challenge will kick off on the 2nd of July and will take 10 weeks to complete. This is a fantastic opportunity to apply AI in practical settings and expand your skills in the field! #AIforGood #OCR #NepaliFarmers #Agriculture

Check out the results from our AI against Oil Spills Challenge! ⛴️ This detailed case study explores how AI models like SAM and Mask-RCNN can be implemented to help oil spill clean-up by improving the speed and accuracy of volume estimations through segmentation masks. In collaboration with Rijkswaterstaat, we've harnessed drone-captured imagery to train computer vision models that can significantly enhance oil spill assessments, allowing for faster and more effective clean-up operations. Despite challenges like poor visibility and inconsistent annotations, our team managed to refine the dataset, leading to more accurate models and, potentially, better environmental protection. 👉 Read the full story and check out other Challenges on our platform: https://lnkd.in/gBQ6zhZt #AI #EnvironmentalProtection #Innovation #OilSpillCleanup #AIForGood

🚀 𝐉𝐨𝐢𝐧 𝐨𝐮𝐫 𝐒𝐞𝐜𝐨𝐧𝐝 𝐀𝐈 𝐟𝐨𝐫 𝐖𝐨𝐦𝐞𝐧 𝐅𝐚𝐫𝐦𝐞𝐫𝐬 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 🌾 Building on the first challenge, we're excited to announce the second AI for Women Farmers Challenge in collaboration with Heifer International. This phase aims to further support agricultural cooperatives in Nepal, with a special focus on empowering women farmers by transitioning from paper-based systems to digital solutions. 🔍 𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐂𝐨𝐧𝐭𝐞𝐱𝐭: In Nepal, the reliance on paper records for agricultural data management remains a major obstacle. This challenge particularly affects farmers and cooperatives, hindering their ability to make informed decisions and achieve better financial and agricultural productivity. By automating the digitization of these records, we aim to provide the tools necessary for sustainable agricultural practices and financial stability. 💻 𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐀𝐬𝐩𝐞𝐜𝐭𝐬 𝐨𝐟 𝐭𝐡𝐢𝐬 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞: 𝐎𝐂𝐑 𝐟𝐨𝐫 𝐃𝐞𝐯𝐚𝐧𝐚𝐠𝐚𝐫𝐢 𝐒𝐜𝐫𝐢𝐩𝐭: Improve upon the OCR system developed in Part 1 to extract both handwritten and typeset text from loan documents, handling the complexities of the Devanagari script more effectively. 𝐋𝐚𝐧𝐠𝐮𝐚𝐠𝐞 𝐓𝐫𝐚𝐧𝐬𝐥𝐚𝐭𝐢𝐨𝐧: Enhance translation tools to convert Nepali text into English with high accuracy and contextual relevance. 𝐃𝐚𝐭𝐚 𝐃𝐢𝐠𝐢𝐭𝐢𝐳𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: Digitize and structure the data for easy analysis and access. Implement tools to analyze this data, enabling better decision-making. If you’re interested and want to know more, you can join us tomorrow during the live final presentation of the first AI for Women Farmers Challenge! https://lnkd.in/esTKEDbj We're also seeking experts skilled in OCR technology. Familiarity with the Nepali language and Devanagari script will be advantageous. Check out the challenge and apply as expert! 🔗 Join the Challenge: https://lnkd.in/eiBe8hKj 💚 #AIForGood #DigitalAgriculture #TechForGood

🚀 Final week to join the AI for Greener Datacenters Challenge! 🔋💾 Our main focus is to significantly reduce the energy consumed by cooling systems, which accounts for approximately 40% of the total power used in data centers. 🔍Context: Data centers are crucial to our digital infrastructure, supporting everything connected to the internet, from social media platforms to essential banking services. However, they also consume significant energy and contribute to global carbon emissions. In response, we are aiming to reduce the energy usage of data center cooling systems by nearly half using reinforcement learning 💻 Technical Aspects of the Challenge: 𝐑𝐞𝐢𝐧𝐟𝐨𝐫𝐜𝐞𝐦𝐞𝐧𝐭 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠: We will employ reinforcement learning strategies, such as DQN and PPO, to directly manipulate cooling system parameters within a simulated data center environment, optimizing energy usage in real-time. 𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐌𝐨𝐝𝐞𝐥𝐢𝐧𝐠: Utilizing the EnergyPlus model and an RL Gym, our challenge will simulate exact conditions to test and refine the AI's decision-making capabilities. 𝐄𝐱𝐩𝐥𝐚𝐢𝐧𝐚𝐛𝐥𝐞 𝐀𝐈: Transparency in AI decisions is crucial. We will use cause-and-effect modeling and extensive data visualization to ensure that every adjustment made by our AI systems is understandable and justifiable. 🤩 Join the Team: https://lnkd.in/daH8Cxrg This challenge is perfect for individuals eager to apply and enhance their AI skills in real-world scenarios! 💚 #DataCenterEfficiency #AIForGood #SustainableTech #AI

🤔 How can we use Reinforcement Learning to save up to 0.5% of global energy consumption? ⚡️ We’ll tell you how! Data centers, crucial to modern digital infrastructures, consume about 1% to 2% of the world's total electricity. A staggering 40% of this consumption is used solely for cooling systems. As data centers have expanded, their energy consumption has become a major contributor to global carbon emissions. In our AI for Greener Datacenters Challenge, in partnership with Coolgradient, we aim to optimize cooling systems using Reinforcement Learning (RL). By simulating a data center environment connected to an RL Gym, we will explore various control strategies to enhance energy efficiency, utilizing techniques like Deep Q Networks (DQN) and Proximal Policy Optimization (PPO). 🙌 Read more about this Challenge here and sign up: https://lnkd.in/daH8Cxrg 🙋♀️ How You Can Help This challenge offers a unique opportunity for both novices and experts to engage with AI in a real-world context. Participants will gain practical experience across all stages of machine learning, from data simulation to model deployment, contributing to a greener world! 📝 Sign Up Join us by registering for a membership, and we will contact you to discuss how you can contribute based on your skills. Experts in Reinforcement Learning are particularly encouraged to apply for free and help us solve this Challenge! #ReinforcementLearning #AI #AIforGood #Datacenter

📯 Last call for the AI for Forest Elephants Challenge! 🌳🐘 🔗 Register here: https://bit.ly/3JqDMU4 🚀 Goal: We aim to detect elephant rumbles and gunshots in Central Africa using sound recordings with high accuracy. Our goal is to improve our models and develop an automated pipeline for analyzing acoustic data. 🕹️ Technical Enhancements: - Model Optimization: Improving the accuracy, performance, and processing speed. - Model Pruning: Refining models to operate efficiently on edge devices suitable for field deployment. - Pipeline Development: Crafting a streamlined, user-friendly system for handling large volumes of audio data, enabling prompt and insightful analysis 🌍 Impact of the Challenge: Advancements in acoustic AI models can help monitor elephant populations, prevent poaching, and promote coexistence between local communities and wildlife. Check out the Elephant Listening Project and see how they are already helping! 🌟 Who Should Join? This challenge is open to everyone from AI novices keen on applying their learning in practical scenarios, to seasoned experts specialized in audio processing and MLops. Join us to sharpen your skills and contribute to significant conservation efforts. More information about the Challenge: https://lnkd.in/eRVeSBq2 #AIforConservation #AfricaAI #AIforGood #AIChallenge

❗️🐘 Only 2 weeks left until we kick off the new AI for Forest Elephants Challenge! 🌳🌴 Sign up now: https://bit.ly/3JqDMU4 🚀 𝐆𝐨𝐚𝐥: Utilize sound recordings to detect forest elephant vocalizations and gunshots in Central Africa! We aim to refine the models built in our previous Challenge for increased accuracy and efficiency and build a seamless automated pipeline for acoustic data analysis. 🔍 𝐂𝐨𝐧𝐭𝐞𝐱𝐭: Forest elephants, critical to the ecological balance of Central Africa's rainforests, face threats from poaching, habitat loss, and human-wildlife conflicts. With their populations dwindling, it’s crucial to enhance our conservation efforts through innovative technologies. Acoustic monitoring presents a promising solution, offering a less invasive method to track elephant populations and support conservation strategies effectively. 🕹️ 𝐓𝐞𝐜𝐡𝐧𝐢𝐜𝐚𝐥 𝐚𝐬𝐩𝐞𝐜𝐭𝐬: This iteration will focus on: - 𝐌𝐨𝐝𝐞𝐥 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Enhancing performance, accuracy, and speed of existing models. - 𝐌𝐨𝐝𝐞𝐥 𝐏𝐫𝐮𝐧𝐢𝐧𝐠: Streamlining the model to function efficiently on edge devices, ideal for field conditions. - 𝐏𝐢𝐩𝐞𝐥𝐢𝐧𝐞 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭: Creating an efficient, user-friendly pipeline capable of processing extensive audio data and providing actionable insights through detailed analytics. 🔧 𝐓𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 𝐭𝐨 𝐌𝐚𝐬𝐭𝐞𝐫: - Signal Processing - Convolutional Neural Networks (CNN) - Transformers - MLops 🌍 𝐈𝐦𝐩𝐚𝐜𝐭: Improved acoustic AI models will not only help in monitoring elephant populations and preventing poaching but also in mitigating conflicts with local communities, ultimately fostering a sustainable co-existence. 🌟 𝐖𝐡𝐨 𝐜𝐚𝐧 𝐣𝐨𝐢𝐧? Whether you're a learner new to AI, eager to apply your skills in real-world settings or an expert in audio processing and MLops, we have a place for you. Sign up for our challenge, enhance your skills, and make a difference in conservation! We're very excited to collaborate again with Daniela Hedwig & Cornell University ! 😁