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Empowering LLMs to Think Deeper by Erasing Thoughts

Introduction Recent large language models (LLMs) — such as OpenAI’s o1/o3, DeepSeek’s R1 and Anthropic’s Claude 3.7 — demonstrate that allowing the model to think deeper and longer at test time can significantly enhance model’s reasoning capability. The core approach underlying their deep thinking capability is called chain-of-thought (CoT), where the model iteratively generates intermediate…

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Distributed Tracing: A Powerful Approach to Debugging Complex Systems | by Hareesha Dandamudi | Dec, 2024

Why distributed tracing is the key to resolving performance issues (Image by Author) - Distributed tracing — ideaMy articles are free for everyone to read! If you don’t have a Medium subscription, feel free to explore the full article directly on my blog: https://blog.bytedoodle.com/distributed-tracing-a-powerful-approach-to-debugging-complex-systems/ M odern applications are increasingly built using microservices, where hundreds of…

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How Cheap Mortgages Transformed Poland’s Real Estate Market | by Lukasz Szubelak | Jan, 2025

Insights from a synthetic control group 16 min read · 10 hours ago Photo by Maria Ziegler on UnsplashReal estate is a bedrock of modern economies, serving as both a tangible asset and an essential component of wealth accumulation for individuals and investment portfolios. Real estate price fluctuations have far-reaching implications, influencing…

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Advancing AI Reasoning: Meta-CoT and System 2 Thinking | by Kaushik Rajan | Jan, 2025

How Meta-CoT enhances system 2 reasoning for complex AI challenges Image created by the author using Generative AI (Flux-pro)What makes a language model smart? Is it predicting the next word in a sentence ‒ or handling tough reasoning tasks that challenge even bright humans? Today’s Large Language Models (LLMs) create smooth text plus solve simple…

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A Beginner’s 12-Step Visual Guide to Understanding NeRF: Neural Radiance Fields for Scene Representation and View Synthesis | by Aqeel Anwar | Jan, 2025

A basic understanding of NeRF’s workings through visual representations Who should read this article? This article aims to provide a basic beginner level understanding of NeRF’s workings through visual representations. While various blogs offer detailed explanations of NeRF, these are often geared toward readers with a strong technical background in volume rendering and 3D graphics.…

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Predicting a Ball Trajectory. Polynomial Fit in Python with NumPy | by Florian Trautweiler | Jan, 2025

Polynomial Fit in Python with NumPy Ball Tracking and Trajectory PredictionIn a previous project I visualized the trajectory of a ball that I threw vertically into the air with a real-time position, velocity and acceleration plot. Extending upon this project, I wanted to calculate and visualize a trajectory prediction based on a simple physics model.…

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