📉 AI Models Face "Collapse" When Trained on AI-Generated Data

+ Design a URL Shortener 💻, Data Mesh Implementation Tips 🛠, eBook on PCA 📙

Oct 08, 2024

Hi there!

Thanks for tuning in to another edition of our newsletter! We've handpicked some top job listings, articles and resources to help you level up your career.

Top Job Picks 🔝

Full Stack Software Engineer - Postman (Remote)
Data Scientist - Whatnot (Remote)
Data Engineer - Brex (Hybrid)

Looking for more opportunities? Join our Talent Pool for personalized job matches and explore all our listings at TopAIsJobs.com.

Engineering Edge 💻

Essential reads to enhance your coding and design practices

TDD: 5 test smells - 5 solutions 5 practical tips to improve the quality of your tests

- written by Daniel Moka

Daniel shares five common test smells: fragile tests, eager tests, mystery guest, irrelevant data, and tests with logic. He explains how to spot these issues and offers practical solutions for each. The article aims to help developers write cleaner, more effective tests by focusing on key principles like behavior-driven testing and simplicity.

Design a URL Shortener - System Design Interview

Written by Ashish Pratap Singh

"Don't talk to strangers" also applies to software development

Written by Raul Junco

10 Caching Fundamentals for System Design Interviews

Written by javinpaul

Data Engineering Hub 🛠

Core knowledge for data engineers

Building A Generative AI Platform

- written by Chip Huyen

Understand how to build a generative AI platform, starting simple and adding complexity. This article covers enhancing input, adding safety measures, and optimizing performance.

How To Implement Data Mesh: Top Tips From 4 Data Leaders

Written by Monte Carlo

How to Solve Data Engineering Problems

Written by Daniel Beach

Data Science Spotlight 🔬

📙 [Free eBook] Unraveling Principal Component Analysis

- Author: Peter Bloem

This book offers a detailed look at principal component analysis, a key method in data science and machine learning. It explains the math behind PCA in a story-like way, making complex ideas easier to grasp. The author walks readers through all the important details, giving a full picture of how PCA works.

An Introduction to Time Series Forecasting with Generative AI

By Databricks

Grid Search vs. Random Search vs. Bayesian Optimization

Written by Avi Chawla

Data Analytics Digest 📊

Key insights from the world of analytics

Statistics and Probability for Data Analysis

Understand key statistics and probability concepts for data analysis. It covers descriptive and inferential statistics, defines 14 fundamental terms, and explains how statistics can be applied to data science and machine learning.

7 Tips for Killer Presentations

Written by Raviraj Achar

📺 [Video] Advanced SQL Course For Data Analytics

by Data with Baraa

Machine Learning Marvels 🤖

Important reads on ML algorithms and models

📑 [Research Paper] AI models collapse when trained on recursively generated data

The paper explores the risks of training AI models on data generated by other AI models. It highlights a phenomenon called "model collapse," where the diversity of content diminishes, leading to irreversible defects in models like GPT and others. The study emphasizes the importance of using human-generated data to maintain the quality and reliability of AI systems, especially as AI-generated content becomes more prevalent online.

Developing an LLM: Building, Training, Finetuning

Written by Sebastian Raschka, PhD

The mathematics of optimization for deep learning

Written by Tivadar Danka

Career Development 📈

Advice on leading and growing in tech

Don't Manage Up, Team Up Instead

- written by Nicola Ballotta

This article challenges the concept of "Managing Up" in engineering, proposing "Teaming Up" as a better alternative. It emphasizes collaboration, shared responsibility, and open communication among team members, regardless of their roles. The author shares practical tips for implementing this approach and overcoming potential challenges.