A Guide on How to Make the Best Decisions Under the Worst Circumstances

 @vinitabansal, this thought-provoking piece by Erik Pevernagie emphasizes the importance of making effective decisions under challenging conditions. It's a valuable skill that separates the exceptional from the ordinary in various aspects of life, including work. The article sheds light on our biases, the importance of questioning, and considering long-term implications. By following the steps outlined, we can break free from the vicious cycle and make informed decisions that lead to better outcomes. Keep exploring and learning!

Forget Books and Physical Classes, the Future of Learning Is Interactive Video

 "@dadan, the future of education is here, and it's in the form of interactive videos. With Dadan.io, educators can easily create, edit, and publish engaging videos that boost learning and accessibility. Say goodbye to the rigidity of traditional classroom settings and hello to a more creative, flexible, and fun educational experience. #videolearning #educationrevolution"

How to Get Responses From Local LLM Models With Python

 @luca1iu: This article provides a clear and detailed guide for interacting with a local Language Model (LLM) using Python. From listing available models to generating responses through the /v1/completions endpoint or managing conversations with the /v1/chat/completions endpoint, follow this step-by-step tutorial to strengthen your applications with powerful LLM capabilities. 👍 #Python #LLM #NLP #MachineLearning #DataScience #AI #TechGuide

MediaBias.TECH

Countering Mainstream Bias via End-to-End Adaptive Local Learning: Conclusion and References

Countering Mainstream Bias via End-to-End Adaptive Local Learning: Related Work

Countering Mainstream Bias via End-to-End Adaptive Local Learning: Hyper-parameter Study

Countering Mainstream Bias via End-to-End Adaptive Local Learning: Ablation Study

Countering Mainstream Bias via End-to-End Adaptive Local Learning: Debiasing Performance

Countering Mainstream Bias via End-to-End Adaptive Local Learning: Debiasing Experiments and Setup

Countering Mainstream Bias via End-to-End Adaptive Local Learning: Adaptive Weight

Countering Mainstream Bias via End-to-End Adaptive Local Learning: Loss-Driven Mixture-of-Experts

Countering Mainstream Bias via End-to-End Adaptive Local Learning: Adaptive Local Learning

Countering Mainstream Bias via End-to-End Adaptive Local Learning: Preliminaries

Countering Mainstream Bias via End-to-End Adaptive Local Learning: Abstract and Introduction

Effective Bias Detection and Mitigation: Key Findings from BiasPainter’s Evaluation

Exploring Bias and Fairness in AI: The Need for Comprehensive Testing Frameworks

What We’ve Learned About BiasPainter’s Accuracy and Limitations

Mitigating Bias in AI Models

Validating BiasPainter: Manual Inspection Confirms High Accuracy in Bias Detection

How Well Does BiasPainter Uncover Hidden Biases in Image Generation?

How BiasPainter Assesses Social Bias: Experimental Setup and Tests for Top Image Generation Models 

Can BiasPainter Help Curb Bias in AI?

Quantifying Bias in Image Generation

Tech Media Bias [Research Publication]