Towards AI
“Towards AI” is a platform that delves into various aspects of artificial intelligence and machine learning. The content covers topics such as data augmentation for machine learning, Python programming scripts, and the use of Python in web3, blockchain, and smart contracts. Additionally, it explores the challenges and solutions in building AI applications with features like short-term memory and persistent conversation history. The platform also discusses the importance of understanding and utilizing enterprise-grade tools like Spark, EMR on EKS, and Airflow 3 for creating secure and efficient knowledge bases for AI applications.
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LAI #119: Prompting, Retrieval, or Retraining?
Understanding what actually changes a model, plus SVD, LeJEPA, MCP scaling, and CLIP search. Good morning, AI enthusiasts, A lot of AI conversations right now blur together very different ideas: prom...
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The Junior Developer Crisis of 2026: AI Is Creating Developers Who Can’t Debug
Beyond the Prompt: Why AI is creating a generation of coders who can ship features but can’t find bugs. Every few decades, a technological shift fundamentally alters the “barrier to entry” for human ...
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Crack ML Interviews with Confidence: Deep Learning (20 Q&A)
Data Scientist & Machine Learning Interview Preparation Continue reading on Towards AI
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Building a Real-Time Face Recognition Attendance System with OpenCV
An end-to-end computer vision project using LBPH, Tkinter, and classical techniques Continue reading on Towards AI
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How to Effectively Apply OpenClaw
Read my experiences from using OpenClaw. Continue reading on Towards AI
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Tracking AI’s Fingerprints Across Millions of Github Commits
AI is Now Writing 3% of All Public Code on GitHub. Here's What It's Building. Continue reading on Towards AI
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What 81,000 People Actually Want From AI: The Dirty Secret Behind Anthropic’s Massive Global Survey
Anthropic used its own AI to interview tens of thousands of people about AI. The findings are fascinating. The methodology is more… Continue reading on Towards AI
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I Ran the Same Multi-Agent Prompts on Claude Code, Codex, and Cursor. Here’s What Actually Happened
I Ran the Same Multi-Agent Prompts on Claude Code, Codex, and Cursor. Here’s What Actually Happened. A hands-on comparison of three multi-agent coding systems across research, data extraction, and bu...
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Chapter 3: Fine-Tuning for Alignment and Robustness
Fine-Tuning for Alignment Continue reading on Towards AI
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Chapter 2: The Efficiency Revolution: PEFT and Its Next Generation
LoRA (Low-Rank Adaptation) Continue reading on Towards AI
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Your Users Will Never Pick the Right Model. Build a Router Instead.
Auto mode isn’t optional anymore — it’s what really help the customer harnest the value from your agent. The Problem Nobody Wants to Admit You built a great AI agent. Multiple models available — Opus...
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The Algorithm That Cheats at Math (And Why That’s Genius)aka HNSW
You Never Find the Closest Vector. And That’s the Whole Point. Continue reading on Towards AI
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