📌 The Step-by-Step Process of Adding a New Feature to My IOS App with Cursor

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2025-12-05 | ⏱️ Read time: 6 min read

This article provides a step-by-step walkthrough of adding a new feature to an iOS app using the AI-powered editor, Cursor. It offers practical insights for developers, highlighting how Cursor excels at code generation but is less effective for UI/UX design tasks. This guide demonstrates a real-world workflow for integrating AI coding assistants into the development process, showcasing both their strengths and limitations.

#iOSDev #AICoding #AppDevelopment #Cursor

📌 The Machine Learning “Advent Calendar” Day 5: GMM in Excel

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-12-05 | ⏱️ Read time: 6 min read

Explore Gaussian Mixture Models (GMM), a powerful clustering algorithm that serves as a natural extension and improvement over k-Means. This guide, part of a Machine Learning Advent Calendar series, uniquely demonstrates how to implement and understand GMMs entirely within Microsoft Excel. It's a practical approach for grasping core ML concepts without requiring a dedicated coding environment, making advanced data science techniques more accessible.

#MachineLearning #GMM #Excel #DataScience #Clustering

📌 A Product Data Scientist’s Take on LinkedIn Games After 500 Days of Play

🗂 Category: DATA SCIENCE

🕒 Date: 2025-12-05 | ⏱️ Read time: 14 min read

A product data scientist offers a unique analysis of LinkedIn's puzzle games after 500 consecutive days of play. The article delves into key takeaways on user engagement, experimentation, and data-driven product thinking, revealing how observing a simple game can provide valuable lessons for complex product strategy and development in the tech industry.

#DataScience #ProductManagement #UserEngagement #Experimentation

📌 YOLOv1 Paper Walkthrough: The Day YOLO First Saw the World

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2025-12-05 | ⏱️ Read time: 17 min read

A deep dive into the original YOLOv1 paper, exploring the revolutionary "You Only Look Once" algorithm. This technical walkthrough breaks down the foundational object detection architecture and guides readers through a complete implementation from scratch using PyTorch. It's an essential resource for understanding the core mechanics of single-shot detectors and the history of computer vision.

#YOLO #ObjectDetection #ComputerVision #PyTorch

📌 On the Challenge of Converting TensorFlow Models to PyTorch

🗂 Category: DEEP LEARNING

🕒 Date: 2025-12-05 | ⏱️ Read time: 19 min read

Converting legacy TensorFlow models to PyTorch presents significant challenges but offers opportunities for modernization and optimization. This guide explores the common hurdles in the migration process, from architectural differences to API incompatibilities, and provides practical strategies for successfully upgrading your AI/ML pipelines. Learn how to not only convert but also enhance your models for better performance and maintainability in the PyTorch ecosystem.

#PyTorch #TensorFlow #ModelConversion #MLOps #DeepLearning

📌 Do Labels Make AI Blind? Self-Supervision Solves the Age-Old Binding Problem

🗂 Category: DEEP LEARNING

🕒 Date: 2025-12-04 | ⏱️ Read time: 16 min read

A new NeurIPS 2025 paper suggests that traditional labels may hinder an AI's holistic image understanding, a challenge known as the "binding problem." Research shows that self-supervised learning methods can overcome this, significantly improving the capabilities of Vision Transformers (ViT) by allowing them to better integrate various visual features without explicit labels. This breakthrough points to a future where models learn more like humans, leading to more robust and nuanced computer vision.

#AI #SelfSupervisedLearning #ComputerVision #ViT

📌 The Machine Learning “Advent Calendar” Day 4: k-Means in Excel

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-12-04 | ⏱️ Read time: 7 min read

Discover how to implement the k-Means clustering algorithm, a fundamental machine learning technique, using only Microsoft Excel. This guide, part of a "Machine Learning Advent Calendar" series, walks through building a training algorithm from scratch in a familiar spreadsheet environment, demystifying what "real" ML looks like in practice.

#MachineLearning #kMeans #Excel #DataScience #Tutorial

📌 Build and Deploy Your First Supply Chain App in 20 Minutes

🗂 Category: PROGRAMMING

🕒 Date: 2025-12-04 | ⏱️ Read time: 21 min read

A factory operator that discovered happiness by switching from notebook to streamlit – (Image Generated…

#DataScience #AI #Python

📌 Bootstrap a Data Lakehouse in an Afternoon

🗂 Category: DATA ENGINEERING

🕒 Date: 2025-12-04 | ⏱️ Read time: 12 min read

Using Apache Iceberg on AWS with Athena, Glue/Spark and DuckDB

#DataScience #AI #Python

📌 The Best Data Scientists are Always Learning

🗂 Category: DATA SCIENCE

🕒 Date: 2025-12-04 | ⏱️ Read time: 7 min read

Why continuous learning matters & how to come up with topics to study

#DataScience #AI #Python

📌 Reading Research Papers in the Age of LLMs

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2025-12-06 | ⏱️ Read time: 10 min read

How I keep up with papers with a mix of manual and AI-assisted reading

#DataScience #AI #Python

🤖🧠 Supervised Reinforcement Learning: A New Era of Step-Wise Reasoning in AI

🗓️ 23 Nov 2025
📚 AI News & Trends

In the evolving landscape of artificial intelligence, large language models (LLMs) like GPT, Claude and Qwen have demonstrated remarkable abilities from generating human-like text to solving complex problems in mathematics, coding, and logic. Yet, despite their success, these models often struggle with multi-step reasoning, especially when each step depends critically on the previous one. Traditional ...

#SupervisedReinforcementLearning #StepWiseReasoning #ArtificialIntelligence #LargeLanguageModels #MultiStepReasoning #AIBreakthrough

🤖🧠 CALM: Revolutionizing Large Language Models with Continuous Autoregressive Learning

🗓️ 23 Nov 2025
📚 AI News & Trends

Large Language Models (LLMs) such as GPT, Claude and Gemini have dramatically transformed artificial intelligence. From generating natural text to assisting in code and research, these models rely on one fundamental process: autoregressive generation predicting text one token at a time. However, this sequential nature poses a critical efficiency bottleneck. Generating text token by token ...

#CALM #ContinuousAutoregressiveLearning #LargeLanguageModels #AutoregressiveGeneration #AIEfficiency #AIInnovation

🤖🧠 Agent-o-rama: The End-to-End Platform Transforming LLM Agent Development

🗓️ 23 Nov 2025
📚 AI News & Trends

As large language models (LLMs) become more capable, developers are increasingly using them to build intelligent AI agents that can perform reasoning, automation and decision-making tasks. However, building and managing these agents at scale is far from simple. Challenges such as monitoring model behavior, debugging reasoning paths, testing reliability and tracking performance metrics can make ...

#AgentoRama #LLMAgents #EndToEndPlatform #AIIntelligence #ModelMonitoring #AIDevelopment

Our Group on Signal (only for Programmers)

https://signal.group/#CjQKIPcpEqLQow53AG7RHjeVk-4sc1TFxyym3r0gQQzV-OPpEhCPw_-kRmJ8LlC13l0WiEfp

🤖🧠 DeepEyesV2: The Next Leap Toward Agentic Multimodal Intelligence

🗓️ 23 Nov 2025
📚 AI News & Trends

The evolution of artificial intelligence has reached a stage where models are no longer limited to understanding text or images independently. The emergence of multimodal AI systems capable of processing and reasoning across multiple types of data has transformed how machines interpret the world. Yet, most existing multimodal models remain passive observers, unable to act ...

#DeepEyesV2 #AgenticMultimodalIntelligence #MultimodalAI #AIEvolution #ActiveReasoning #AIAction

📌 The Machine Learning “Advent Calendar” Day 6: Decision Tree Regressor

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-12-06 | ⏱️ Read time: 10 min read

During the first days of this Machine Learning Advent Calendar, we explored models based on…

#DataScience #AI #Python

🤖🧠 Reducing Hallucinations in Vision-Language Models: A Step Forward with VisAlign

🗓️ 24 Nov 2025
📚 AI News & Trends

As artificial intelligence continues to evolve, Large Vision-Language Models (LVLMs) have revolutionized how machines understand and describe the world. These models combine visual perception with natural language understanding to perform tasks such as image captioning, visual question answering and multimodal reasoning. Despite their success, a major problem persists – hallucination. This issue occurs when a ...

#VisAlign #ReducingHallucinations #VisionLanguageModels #LVLMs #MultimodalAI #AISafety

🤖🧠 LEANN: The Bright Future of Lightweight, Private, and Scalable Vector Databases

🗓️ 24 Nov 2025
📚 AI News & Trends

In the rapidly expanding world of artificial intelligence, data storage and retrieval efficiency have become major bottlenecks for scalable AI systems. The growth of Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) has further intensified the demand for fast, private and space-efficient vector databases. Traditional systems like FAISS or Milvus while powerful, are resource-heavy and ...

#LEANN #LightweightVectorDatabases #PrivateAI #ScalableAI #RAG #AIDataStorage