Mohammad Musa’s Post

Do you want to learn how to become an AI Expert .... for FREE? That's right - you can start learning about cutting-edge AI technologies related to computer vision, object detection, scene segmentation, foundation models and more - all for FREE, meet with experts in the field, get hands-on coding experience, develop your skills, and showcase your work to the world! Sound exciting? - Let's get started! At Autoware Foundation - we are pioneering the development of an open-source autonomous highway pilot system for privately owned vehicles (think Tesla FSD but all our code will be open-source and published on GitHub). We are looking for developers to help join our community and contribute to this exciting project. Our goal is to build a system that is capable of eyes-off, hands-off autonomous driving and have it demo ready in 12 months' time. You will be able to join work-group meetings, explore cutting edge AI technologies, contribute to the codebase, and hear from industry experts. If this sounds like your cup of tea, then we would love to have you on-board our Rocketship. To get started, give this post a 'Like', comment 'Interested' and drop me a direct message here on LinkedIn, and remember to share this post to help get the word out. #selfdriving #selfdrivingcars #autonomy #autonomousdriving #autonomousdrivingtechnology #foundationmodel #autopilot #autonomouspilot #AI #artificialintelligence #technology #technologynews #announcements #opensource #ROS #autoware #robotics #community #coding #developers #computervision

Unlocking Intelligent Decision-Making with Reinforcement Learning Hey fellow data science enthusiasts! Are you fascinated by the potential of machines to learn and make decisions autonomously? Reinforcement Learning (RL) is a powerful paradigm that enables agents to learn from their environment and make optimal decisions through trial and error. In RL, an agent learns to take actions in an environment to maximize a reward signal. This approach has led to breakthroughs in various fields, including: Robotics Game playing (e.g., AlphaGo) Recommendation systems Autonomous vehicles Key benefits of RL include: 1. Flexibility: RL agents can learn to perform complex tasks without explicit programming. 2. Adaptability: RL agents can adapt to changing environments and learn from experience. 3. Optimality: RL agents can learn to make optimal decisions to maximize rewards. #ReinforcementLearning #MachineLearning #ArtificialIntelligence #DataScience

🚗 Personal Project : Self-Driving-Car Project! 🚗 I'm thrilled to announce the launch of my Self-Driving Car Project, a culmination of deep learning and computer vision techniques aimed at revolutionizing the future of transportation. 🌟 🔍 Project Overview: My self-driving car utilizes cutting-edge technologies like convolutional neural networks (CNN) to perceive its environment, make decisions, and navigate safely without human intervention. Check out the demo video for a glimpse of the incredible capabilities of my model! 🛠️ Key Requirements: To get started, all you need is Python and the Udacity simulator. With a simple installation process outlined in my repository, you can start exploring the world of autonomous driving. 📈 Training and Evaluation: My project doesn't stop at development. I delve into rigorous training, data preprocessing, and model evaluation to ensure optimal performance in various scenarios, from lane following to obstacle avoidance. 📚 Open Source Collaboration: I believe in the power of collaboration! Contributions to my project are welcome, whether it's bug fixes, suggestions, or even discussions on implementing reinforcement learning approaches. 👏 Acknowledgments: Special thanks to Udacity for providing invaluable resources and support throughout this journey. Together, we're shaping the future of transportation! 📧 Get in Touch: Have questions or ideas? Feel free to reach out via email or Instagram. I'd love to hear from you! Join me in paving the way towards safer and more efficient transportation solutions. Check out my project repository [here](https://lnkd.in/gVW3zgzz) and let's drive innovation together! #SelfDrivingCars #AutonomousVehicles #ArtificialIntelligence #DeepLearning #ComputerVision #OpenSource #Innovation #SelfDrivingTechnology #FutureTech #AutonomousDriving #TechInnovation #MachineLearning #AIInnovation #Robotics #SmartMobility #EmergingTech #TechDevelopment #Engineering #DataScience #SelfDrivingRevolution #AutomotiveTech #InnovativeTech #FutureOfTransportation #SmartCities #DigitalTransformation #TechCommunity #STEM #EngineeringLife #AdvancedTechnology #AutonomousSystems #SmartTransportation #InnovativeSolutions #TechAdvancement #DigitalInnovation #SelfDrivingJourney #TechnologyTrends Feel free to share and engage with this post to spread the word about the exciting advancements in self-driving technology! 🌟🚗

🎯 Reinforcement Learning: Training AI Through Rewards and Penalties 🤖💡 When it comes to teaching machines how to make decisions, Reinforcement Learning (RL) stands out as a powerful model. Unlike traditional AI models, RL uses a system of rewards and penalties to train algorithms to learn the best possible actions in a given environment. 🏆❌ From robotics to game theory to autonomous vehicles, RL is leading innovations where dynamic decision-making is key. 🚗🤖 Imagine an AI that learns to navigate a complex city environment or masters intricate games like Go—not by being told what to do, but by figuring it out through trial and error. Key Takeaway: Reinforcement Learning is about teaching AI to think on its feet and solve real-world problems through experience—pushing the boundaries of what's possible in autonomous systems. How do you see RL shaping the future of AI-driven applications? Let's dive into the discussion! 🔗👇 #ReinforcementLearning #AI #MachineLearning #AutonomousSystems #DeepLearning #Innovation

🚀 Excited to share that I've completed the 'Complete Self-Driving Car Course - Applied Deep Learning' on Udemy! This intensive 18-hour course taught by experts in the field has equipped me with advanced knowledge in machine learning algorithms and their applications in autonomous driving technology. 👨💻 Throughout this course, I've deepened my understanding of neural networks, computer vision, and sensor fusion, skills crucial for the future of mobility. I'm eager to apply these cutting-edge techniques in real-world scenarios and contribute to innovations in the field of autonomous vehicles. 💡 I'm looking forward to connecting with other tech enthusiasts and professionals who are passionate about AI and machine learning. Let's drive the future forward together! #SelfDrivingCars #DeepLearning #MachineLearning #CareerDevelopment #Udemy #ContinuousLearning

🚦 Exciting News in Computer Vision! 🚀 I'm thrilled to share my latest project where I implemented the YOLOv8 algorithm for real-time traffic sign detection in videos! 🎥🚗 🔍 Dataset: Leveraging the extensive Open Images Dataset v7, I curated a custom dataset specifically focused on traffic signs using a Python script. 🧠 Model: Trained the YOLOv8n (YOLO version 8) model with default parameters over 30 epochs to ensure robust learning from the custom data. 👁🗨 Results: Put the model to the test on various videos, and the outcomes exceeded expectations! The accuracy and real-time performance demonstrated the efficacy of YOLOv8 for traffic sign detection. 🌐 Impact: Imagine the potential applications in autonomous vehicles, smart traffic management, and enhancing road safety through efficient sign recognition! 🙌 Gratitude: Ultralytics Big shoutout to the YOLO community for the powerful algorithm and the Open Images Dataset contributors for their valuable resource. 🚀 Excited to contribute to the field of computer vision and share my journey with the community. Check out the demo video in the comments, and let's keep pushing the boundaries of what's possible in AI and machine learning! 🚀🤖 #ComputerVision #MachineLearning #YOLOv8 #TrafficSignDetection #OpenImagesDataset #AIInnovation #RoadSafety #LinkedIn #TechInnovation #AICommunity

Autonomous vehicles are the future of mobility, powered by deep learning and computer vision. Combining these technologies with Python enables more efficient, intelligent systems, these technologies are helping to build safer, smarter, and more adaptive self-driving systems.

Imagine an autopilot system that not only drives but also explains its actions and decisions in real time. Wayve's latest innovation, LINGO-1, transforms how we perceive autonomous driving, moving from a simple perception-action model to one that includes an intermediate step of textual reasoning. 𝐁𝐫𝐞𝐚𝐤𝐢𝐧𝐠 𝐃𝐨𝐰𝐧 𝐋𝐈𝐍𝐆𝐎-1: >> How It Works: LINGO-1 is a cutting-edge video-language model that observes and comments on the driving scene. This enables a novel form of interaction where you can query the system - asking why it stopped or what it plans to do next. >> Textual Reasoning: The key advancement here is the shift from direct action to reasoned action. The system uses its understanding of the environment not just to react but to think through its responses, offering explanations in text form. 𝐓𝐡𝐞 𝐀𝐝𝐯𝐚𝐧𝐭𝐚𝐠𝐞𝐬: >> Explainability: With LINGO-1, autonomous driving systems become less of a black box and more of an open book. Users and engineers alike can understand the 'thought process' of the AI, enhancing trust and reliability. >> Counterfactual Reasoning: LINGO-1 can contemplate scenarios that haven't occurred or that diverge from its training data, allowing it to handle unexpected situations more adeptly. >> Efficient Learning: Instead of relying on vast datasets to cover every possible driving scenario, LINGO-1 can learn from textual prompts provided by human instructors. This method addresses the challenge of long-tail scenarios in driving, where rare but critical situations occur. 𝐑𝐞𝐥𝐚𝐭𝐞𝐝 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐢𝐨𝐧𝐬: >> MineDojo: Similar in concept, MineDojo aligns Minecraft gameplay with commentary, grounding text in visual inputs. >> Thought Cloning: Developed by Jeff Clune’s group, this approach also bridges pixel input to language output, then to action, enhancing AI's decision-making process in simulated environments. 💬 How do you see explainable AI impacting other industries? Could this be the key to wider acceptance of autonomous technologies? #innovation #technology #future #management #startups