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New Book: 0 and 1 – From Elemental Math to Quantum AI
Quantum Dynamics, Logistic Map, and Digit Distribution of Special Math Constants
Doing Better with Less: LLM 2.0 for Enterprise
What is LLM 2.0?
LLMs – Key Concepts Explained in Simple English, with Focus on LLM 2.0
10 Must-Read Articles and Books About Next-Gen AI in 2025
A Universal Dataset to Test, Enhance and Benchmark AI Algorithms
A Clear Intro to MCP (Model Context Protocol) with Code Examples
Multilayer Perceptron Explained with a Real-Life Example and Python Code: Sentiment Analysis
Least Squares: Where Convenience Meets Optimality
What Do Machine Learning Engineers Do?
From Fuzzy to Precise: How a Morphological Feature Extractor Enhances AI’s Recognition Capabilities
Build Your Own AI Coding Assistant in JupyterLab with Ollama and Hugging Face
A Coding Implementation to Build a Conversational Research Assistant with FAISS, Langchain, Pypdf, and TinyLlama-1.1B-Chat-v1.0
Sea AI Lab Researchers Introduce Dr. GRPO: A Bias-Free Reinforcement Learning Method that Enhances Math Reasoning Accuracy in Large Language Models Wi...
Evolving Product Operating Models in the Age of AI
No More Tableau Downtime: Metadata API for Proactive Data Health
What Germany Currently Is Up To, Debt-Wise
Google’s Data Science Agent: Can It Really Do Your Job?
Bias Detection in LLM Outputs: Statistical Approaches
R.E.D.: Scaling Text Classification with Expert Delegation
Algorithm Protection in the Context of Federated Learning
Mastering the Poisson Distribution: Intuition and Foundations
Six Organizational Models for Data Science
Understanding RAG Part VIII: Mitigating Hallucinations in RAG
Mastering Hadoop, Part 3: Hadoop Ecosystem: Get the most out of your cluster
LLM Challenge with Petabytes of Data to Prove Famous Number Theory Conjecture
Guide to Uber’s H3 for Spatial Indexing
How to Build an Anime Recommendation System with Hugging Face?
Piercing the Deepest Mathematical Mystery
10 Tips to Design Hallucination-Free RAG/LLM Systems
Blueprint: Next-Gen Enterprise RAG & LLM 2.0 – Nvidia PDFs Use Case
How the Brain Estimates Distances, Heights and Velocities, with Computer Vision Applications
From 10 Terabytes to Zero Parameter: The LLM 2.0 Revolution
LLM 2.0, the New Generation of Large Language Models
LLM Deep Contextual Retrieval and Multi-Index Chunking: Nvidia PDFs, Case Study
xLLM: New Generation of Large Language Models for Enterprise
Visualizing Trading Strategies that Consistently Outperform the Stock Market
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