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Meet PyPose: A PyTorch-based Robotics-Oriented Library that Provides a Set of Tools and Algorithms for Connecting Deep Learning with Physics-based Optimization https://lnkd.in/gVQEcZBq AI News, AI, AI tools, Innovation, itinai.com, LLM, MarkTechPost, Rachit Ranjan, t.me/itinai 🚀 Introducing PyPose: A Revolutionary Robotics-Oriented Library 🤖 Are you ready to revolutionize your robotics domain with the power of AI? Meet PyPose, a user-friendly toolkit designed to seamlessly integrate deep learning with physics-based optimization. Built on the PyTorch framework, PyPose offers a clean and well-organized architecture, making it easier than ever to enhance robotic performance and adaptability in challenging tasks. Key Features: - Differentiation of Lie groups and Lie algebra - 2nd-order optimizers - Various differentiable filters - Dynamics models - Linear quadratic regulators - Extended and unscented Kalman filters - IMU pre-integration, and more Practical Solutions and Value: - Over 10x computation speed compared to existing alternatives - Efficient building and testing of various robotic tools - Enhanced performance and adaptability in challenging tasks - Bridging classical robotics techniques with contemporary learning methodologies Ready to Evolve Your Company with AI? Leverage PyPose to connect deep learning with physics-based optimization, identify automation opportunities, define KPIs, select AI solutions, and implement gradually to stay competitive and redefine your way of work. Connect with Us for Expert AI Insights: For AI KPI management advice and continuous insights into leveraging AI, connect with us at [email protected] or stay tuned on our Telegram channel or Twitter. Spotlight on a Practical AI Solution: AI Sales Bot Explore the AI Sales Bot from itinai.com/aisalesbot, designed to automate customer engagement 24/7 and manage interactions across all customer journey stages. Discover how AI can redefine your sales processes and customer engagement. Join Our AI Lab in Telegram @aiscrumbot for Free Consultation Stay updated on the latest AI trends and practical solutions by following us on Twitter @itinaicom. Ready to explore the potential of AI in robotics and sales? Visit our blog, tutorial, and GitHub for further details. Let's unlock the power of AI together! #AI #Robotics #PyPose #DeepLearning #PhysicsOptimization

**What is Machine Learning? Machine learning (ML) powers some of the most important technologies we use, from translation apps to autonomous vehicles. ML offers a new way to solve problems, answer complex questions, and create new content. ML can predict the weather, estimate travel times, recommend songs, auto-complete sentences, summarize articles, and generate never-seen-before images. In basic terms, ML is the process of training a piece of software, called a model, to make useful predictions or generate content from data. **Types of ML Systems: ML systems fall into one or more of the following categories based on how they learn to make predictions or generate content:    -Supervised learning: Supervised learning models can make predictions after seeing lots of data with the correct answers and then discovering the connections between the elements in the data that produce the correct answers.                          Two of the most common use cases for supervised learning are regression and classification (A regression model predicts a numeric value, Classification models predict the likelihood that something belongs to a category. Unlike regression models, whose output is a number, classification models output a value that states whether or not something belongs to a particular category.)    -Unsupervised learning: Unsupervised learning models make predictions by being given data that does not contain any correct answers. An unsupervised learning model's goal is to identify meaningful patterns among the data.                            A commonly used unsupervised learning model employs a technique called clustering.                            Clustering differs from classification because the categories aren't defined by you. For example, an unsupervised model might cluster a weather dataset based on temperature, revealing segmentations that define the seasons. You might then attempt to name those clusters based on your understanding of the dataset.    -Reinforcement learning: Reinforcement learning models make predictions by getting rewards or penalties based on actions performed within an environment. Reinforcement learning is used to train robots to perform tasks, like walking around a room, and software programs like AlphaGo to play the game of Go.    -Generative AI: Generative AI is a class of models that creates content from user input. For example, generative AI can create novel images, music compositions, and jokes; it can summarize articles, explain how to perform a task, or edit a photo. #data_science #python #machine_learning #deep_learning #Artificial_Intelligence #robotics #Supervised_learning #Unsupervised_learning #Reinforcement_learning #Generative_AI

🚀 **Elevating 3D Deep Learning with PointNet++! 🌐** Exciting times in the realm of 3D deep learning! 🌟 Let's talk about the game-changer that's shaking up how we process and understand point cloud data - PointNet++! 🔍 **Unraveling PointNet++: Beyond Points to Structures** PointNet++ isn't just a step forward; it's a leap! 🏃♂️ Building on the groundbreaking PointNet architecture, it takes 3D data analysis to a whole new level. By hierarchically learning local and global features, PointNet++ embraces the structural essence of point clouds, enabling us to grasp complex relationships and contexts. 🌆 **Powering Diverse Applications** PointNet++ isn't confined to one domain; its impact is far-reaching. From robotics and autonomous vehicles to augmented reality and medical imaging, the versatility of PointNet++ is reshaping industries. Its ability to process unstructured point cloud data with efficiency and accuracy is redefining how we interact with the 3D world. 🌐 **A Revolution in Understanding** The significance of PointNet++ transcends algorithms. It's about understanding the world in a more profound way. By enabling machines to comprehend spatial relationships, we're paving the way for advancements that were once only in the realm of science fiction. 🛠️ **Turning Dreams into Reality** In the ever-evolving landscape of AI and deep learning, PointNet++ is a prime example of turning dreams into reality. It's bridging the gap between data and comprehension, and as we fine-tune its capabilities, we're unlocking new dimensions of innovation. 🔗 **Join the Conversation!** Are you as fascinated by PointNet++ as I am? Let's connect and discuss its potential in your field. Share your thoughts, experiences, and visions for the future. Together, we're shaping the future of 3D deep learning! #PointNetPlusPlus #AIInnovation #3DDeepLearning #PointClouds #TechAdvancements

A computer scientist pushes the boundaries of geometry https://lnkd.in/gJ_vcNvk AI News, Adam Zewe | MIT News, AI, AI tools, Innovation, itinai.com, LLM, MIT News - Artificial intelligence, t.me/itinai 🔹 *The Power of Geometric Techniques in AI and Data Science* Unlocking insights with modern geometric techniques! MIT's Justin Solomon is using cutting-edge geometric tools to solve complex problems in AI and data science. By comparing datasets with these techniques, valuable insights can be gained into the performance of machine-learning models. 🔹 *Applications of Geometric Techniques* Solomon's team is applying geometric techniques to a wide range of areas. From aligning 3D organ scans in medical imaging to enabling autonomous vehicles to identify pedestrians using spatial data. They're also using geometric tools for high-dimensional statistical research to construct better generative AI models for tasks such as creating new images. 🔹 *Practical Applications* The geometric algorithms developed for computer animation directly relate to today’s generative AI and probability tasks. Solomon's work demonstrates the practical impact of geometric techniques in addressing real-world challenges. 🔹 *Driving Change and Inclusivity in Research* Summer Geometry Initiative: Solomon launched a paid research program for undergraduates, making geometric research accessible to underrepresented students. This initiative has led to a more diverse field of researchers and has impacted the composition of incoming PhD classes at multiple institutions. Solomon emphasizes the need for a more diverse field of researchers to tackle the growing list of problems in machine learning and statistics using geometric techniques. This diversity brings new ideas and perspectives to the field. 🔹 *Practical AI Solutions for Businesses* Implementing AI in Your Company: Evolve your company with AI by identifying key customer interaction points, defining measurable impacts on business outcomes, selecting AI solutions that align with your needs, and implementing AI usage gradually. For AI KPI management advice, connect with us at [email protected]. Practical AI Solution: AI Sales Bot: Explore the AI Sales Bot from itinai.com/aisalesbot designed to automate customer engagement 24/7 and manage interactions across all customer journey stages. 🔗 *List of Useful Links:* - AI Lab in Telegram @aiscrumbot – free consultation - [MIT News – Artificial intelligence](https://lnkd.in/gt9E8nAY) - [Twitter – @itinaicom](https://lnkd.in/e7mfJSf5)

Decoding the Future: A Glimpse into GPT-4 Vision and Google's RTX Endeavor🤖 Advancements in AI have taken a giant leap forward with the unveiling of GPT-4 Vision by OpenAI and Google's colossal RTX Endeavor. This post synthesizes key findings from extensive reports and papers, shedding light on novel capabilities, use cases, and the promising future of Vision Video, Robotics, and Multimodal AI. 🚀 1️⃣ RTX Endeavor: Google has brought forth an enhanced version of their robotic model, pushing the boundaries of conventional robotic learning by utilizing diverse data from different universities globally. 🌎 The RTX series is a monumental step up, showcasing a single model's capability to outperform specialized robots across various tasks such as kitchen manipulation, door opening, and more, when trained on diverse data. 🤯 [https://lnkd.in/dQJ6mCZR] 2️⃣ GPT-4 Vision: OpenAI’s GPT-4 Vision demonstrates remarkable human-level capabilities across numerous domains, introducing a new way of prompting called 'visual prompting'. 🖼️ Its ability to perform complex tasks, like translating flowcharts to code, identifying emotions from facial expressions, and understanding cause-effect scenarios in sports, showcases its potential to revolutionize several industries. 💡 3️⃣ Microsoft's 160+ Page Report: Microsoft released a substantial report accentuating GPT-4 Vision's capabilities, including visual prompting, which simplifies complex questions into more manageable tasks. 📊 Their experiments demonstrated GPT-4 Vision's prowess in recognizing celebrities, landmarks, medical conditions from images, and even deducing humor from social media interactions. 😄 [https://lnkd.in/d3-kUEQU] 4️⃣ Potential Use Cases: The integration of visual and textual understanding paves the way for a variety of applications, from self-monitoring educational tools to aiding medical diagnostics. 🏫🩺 5️⃣ The Future of Multimodal AI: As we tread into the era of large multimodal models, the fusion of visual, textual, and other forms of data could potentially provide unprecedented solutions across various fields. 🔄 The eventual goal could be achieving a level of dexterity and comprehension where AI can seamlessly interact and assist in real-world scenarios, akin to Steve Wozniak's coffee test for AGI. ☕ Conclusion: The journey of AI has now transcended beyond text-based interactions, merging into the realms of visual understanding and real-world applications. The meticulous research laid down by Google, OpenAI, and Microsoft, hints at an imminent revolution in robotics and multimodal AI, setting a path towards a future where AI’s understanding and interaction with the real world is refined and transformative. ✨ #AI #Robotics #MultimodalAI #GPT4Vision #RTXEndeavor #OpenAI #Google #Microsoft #FutureTech #Innovation

🤖 OpenAI's Robot Preview vs 🇪🇺 EU AI Act: Guiding the World in Two Directions Today marks a significant day in the world of artificial intelligence, with two major developments pulling us in seemingly opposite directions. OpenAI's Robot Powered by AI 🦾 On one hand, we have the exciting news of OpenAI offering a first glimpse of a robot powered by their advanced AI. This preview hints at the incredible potential of AI to revolutionize robotics and automation. The integration of cutting-edge AI into physical machines opens up a world of possibilities, from more efficient manufacturing to advanced assistive technologies. OpenAI continues to push the boundaries of what's possible with AI, and this robot preview is just another example of their innovative spirit. It's thrilling to imagine how AI-powered robots could transform industries and improve lives in the near future. Link: https://lnkd.in/eVPWDG9w EU AI Act Passes 📜 On the other hand, today also marks the passing of the EU AI Act - a set of regulations aimed at governing the development and use of artificial intelligence. This legislation is designed to ensure that AI is developed and deployed in an ethical, transparent, and accountable manner. The EU AI Act introduces classifications for AI systems based on their perceived risk, with stricter rules for high-risk applications. It also establishes requirements for transparency, human oversight, and data governance. While some may view regulations as a hindrance to innovation, the EU AI Act aims to foster trust and confidence in AI by addressing concerns around privacy, bias, and safety. It's a crucial step towards ensuring that AI benefits society as a whole. Link: https://lnkd.in/ed9X7YYb Balancing Innovation and Responsibility 🌍 These two developments showcase the delicate balance we must strike as we navigate the rapid advancement of AI. We need to encourage innovation and explore the vast potential of AI, as exemplified by OpenAI's robot preview. At the same time, we must also prioritize ethics, safety, and societal well-being, which is the goal of the EU AI Act. As we move forward in this AI-driven era, it's essential that we find ways to harmonize these two aspects. By fostering responsible innovation and creating appropriate guardrails, we can harness the power of AI to create a better future for all. What are your thoughts on these developments? How do you think we can strike the right balance between innovation and responsibility in the field of AI? Let's discuss in the comments below! #AI #OpenAI #EUAIAct #ResponsibleAI #InnovationvsRegulation

As we step into 2024, the world of technology careers is evolving rapidly, with AI, ML, and Data Science leading the charge. If you're pondering your career path in this dynamic landscape, here's a glimpse into each field and why they might be your next big move. From natural language processing to autonomous vehicles, AI's potential is limitless. Its versatility spans healthcare, finance, gaming, and more, making it a field ripe with opportunities for those who love to solve complex problems and innovate. Data Science stands at the intersection of statistics, ML, and domain knowledge. As businesses increasingly lean on data for strategic decisions, the demand for data scientists is skyrocketing. This field is ideal for those who love to uncover hidden stories in data and influence business strategies. #AI #MachineLearning #DataScience #TechCareers #Innovation

Should you include any information about your experience with reinforcement learning or autonomous agents? Including information about your experience with reinforcement learning (RL) or autonomous agents can be valuable in a data science resume, particularly if the role you are applying for involves artificial intelligence (AI), robotics, or autonomous systems. Here's why: 1. Demonstrates expertise in AI and machine learning: Reinforcement learning is a subfield of machine learning that focuses on teaching agents to make sequential decisions through interactions with an environment. By showcasing your experience with RL, you demonstrate your expertise in AI and your ability to develop intelligent systems capable of learning and decision-making. 2. Autonomous systems and robotics: RL is commonly used in the development of autonomous agents and robotic systems, enabling them to learn and adapt to their environment. If you have worked on projects involving autonomous agents or robotics, mention your experience with RL to highlight your ability to develop intelligent systems that can navigate and interact with their surroundings. 3. Algorithmic knowledge: Reinforcement learning involves understanding and implementing algorithms such as Q-learning, deep Q-networks (DQN), policy gradients, or actor-critic methods. Mentioning your experience with these algorithms showcases your knowledge of RL techniques and your ability to apply them to solve complex problems. 4. Simulation and experimentation: RL often involves conducting simulations and experiments to train and evaluate agents' performance. Highlight any experience you have with designing experiments, setting up simulation environments, or conducting RL training runs. 5. Multi-agent systems: If you have experience with RL in the context of multi-agent systems, such as cooperative or competitive environments, mention that in your resume. 6. Technical skills: Specify the programming languages, libraries, or frameworks you have used for RL and autonomous agent development. This could include popular RL libraries like TensorFlow, PyTorch, or OpenAI Gym. Highlight any additional skills relevant to RL, such as experience with deep learning or familiarity with simulation tools like Unity or Gazebo. 7. Publications or contributions: If you have published research papers or made contributions to the RL or autonomous systems field, mention them in your resume. This showcases your thought leadership and engagement with the broader AI community. 8. Tangible outcomes: Describe any tangible outcomes or achievements resulting from your work with RL or autonomous agents. This could include successful deployment of RL-based systems, improvements in performance or efficiency, or real-world applications of autonomous agents. Do you need help writing your data science resume/CV, cover letter or optimizing your LinkedIn profile? Contact me now via inbox or WhatsApp: +254727498426

📅 January 25, 2024 🚀 Exciting Daily Newsletter! Dive into the fascinating world of Artificial Intelligence and be the first to learn about the latest AI news: 1. **Google Unveils Lumiere: A Revolutionary AI Video Generator** 🎥   • Lumiere uses a space-time diffusion model for ultra-realistic video generation.   • The model's Space-Time U-Net architecture can generate full video duration in one pass.   • Capable of text-to-video generation, image-to-video conversion, and various editing tasks.   • Readmore: https://lnkd.in/gsYXkvA4 2. **Adept's Fuyu-Heavy: A Multimodal Model That's Making Waves** 🌊   • Fuyu-Heavy is a new multimodal model tailored for digital agents, ranking third globally.   • Despite its image modeling focus, it matches or exceeds text-based benchmark performances.   • The model showcases scalability and efficiency in handling variable image sizes.   • Readmore: https://lnkd.in/gnU6UXpm 3. **DataTrove: AI Toolkit for Large-Scale Text Processing** 📚   • DataTrove is a library for processing, filtering, and deduplicating text data at scale.   • Offers a set of prebuilt processing blocks and supports custom functionality.   • Platform-agnostic and designed to assist in evaluating music-and-language models.   • Readmore: https://lnkd.in/gpGaAasR 4. **LabelGPT: Transforming Raw Images into Labeled Data** 🏷️   • LabelGPT is an auto-labeling tool leveraging generative AI for efficient data labeling.   • Enables ML teams to generate a large volume of labeled data swiftly.   • Utilizes zero-shot label generation powered by foundation models.   • Readmore: https://lnkd.in/gaVjZ5QN 5. **Vanna AI: Simplifying SQL Generation with RAG Framework** 💻   • Vanna AI is an open-source Python RAG framework aimed at streamlining SQL generation.   • Train a RAG model on your data and receive SQL queries to run on your database automatically.   • Designed for ease of use and integration into existing systems.   • Readmore: https://lnkd.in/gUU8Q4RS #AI #MachineLearning #LLMs #ArtificialIntelligence #VideoGeneration #MultimodalModels #DataProcessing #DataLabeling #SQL #Technology #Innovation #DigitalAgents #NeuralNetworks #SoftwareEngineering #TechNews