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DeepSeek-V2 introduces a major architectural innovation that enhances its efficiency as a language model – Multi-Headed Latent Attention (MLA). MLA stands out as a game-changing technique that significantly reduces memory overhead while maintaining strong performance. In this post, we will explore the fundamental concepts behind
Robots in unstructured spaces, such as homes, have struggled to generalize across unpredictable settings. In this context, a few projects stand out more than the rest – for example, the Everyday Robot project at Google X and Figure’s 01 home robot. After being tied to
Hey folks, welcome to another weekend! I love drones, they give us new perspective to look at the world around us. These machines possess the ability to traverse all three dimensions, traversing vast distances in any desired direction to fulfill our desires. Among the illustrious
Historically, we humans have developed models to understand our world. For example, Newton’s second law of motion gives us the equation , which tells us that a force ‘F’ applied to a static free body in space of mass ‘m’ would accelerate it with amount
Boston Dynamics’ Spot robot is something that has always fascinated me. But the price tag of $75000 is hard to digest considering I’m just a regular guy. Luckily, folks at SpotMicroAI had started designing the Spot Micro – an open-source project where anyone could 3D
Hey folks! I’m thrilled to share with you a research paper that I’ve been working on, diving deep into the fascinating realm of vision-based navigation for indoor robots. In my research paper titled “Real-time Vision-based Navigation for a Robot in an Indoor Environment”, I explore
Today we’re going to dive into a fascinating paper called “LOGIC-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning.” The authors of this paper claim that Large Language Models (LLMs) often struggle when faced with complex logical reasoning problems. Well, LLMs primarily
Sagar Manglani
manglanisagar@gmail.com
Blogger
I strive for research that transforms abstract theory into technical depth, making computer vision more precise, scalable, and impactful.
