G Herbowiczainode.hashnode.dev·Nov 4, 2024A Four-Level BiasThere is a bias against bias. In many contexts, bias is seen as a negative thing. It's often associated with prejudice, discrimination, and unfairness. There's a strong desire to eliminate bias, particularly in areas like artificial intelligence and ...DiscussBias
G Herbowiczainode.hashnode.dev·Nov 4, 202425 Intersectionality BiasesIntersectionality is a framework that examines how various social and political identities, such as race, class, gender, and sexual orientation, intersect to create unique systems of discrimination and privilege. It recognizes that individuals may ex...Discuss·39 readsintersectionality
Arya M. Pathakarya2004.hashnode.dev·Nov 3, 2024GAN Disadvantages. VAEs and Bias: A Detailed ExplorationGenerative Adversarial Networks (GANs) have become one of the most popular and effective models for generating high-quality synthetic data, excelling in applications like image synthesis, data augmentation, and video generation. However, understandin...DiscussThe GAN Guide: From Basics to BreakthroughsArtificial Intelligence
William Stetarcopin43.hashnode.dev·Aug 8, 2024Understanding Large Language Models as Social, Metafunctional, Semiotic SystemsIn the rapidly evolving field of artificial intelligence, Large Language Models (LLMs) like GPT-4o have garnered significant attention for their impressive capabilities in natural language understanding and generation. Traditionally, these models hav...Discussmetafunctions
William Stetarcopin43.hashnode.dev·Aug 3, 2024Unleashing the True Potential of AI: Zero-Shot Generalization and BeyondArtificial Intelligence (AI) has made significant strides in recent years, yet there remains an untapped potential that could revolutionize the field: zero-shot generalization. This capability, where AI models perform tasks they were not explicitly t...Discussllm
Retzam Tarleretzam.hashnode.dev·Jun 3, 2024Supervised Learning Regressionprint("Supervised learning regression") Regression in supervised learning tasks uses continuous values to make predictions. This uses quantitative feature vectors. In our previous chapters, we talked about supervised learning classification, which is...DiscussMAE
Peter Merrillpeterm.hashnode.dev·Feb 21, 2024The Anti-Assumption Mindset: Embracing Intellectual Humility in Software EngineeringHave you ever launched a feature with confidence, only to find it leaving users scratching their heads? It's a scenario familiar to many software engineers, regardless of experience. Often, the culprit resides in the shadows: assumptions. These unspo...Discuss·48 readsAssumptions
Krish Parekhkrishparekh.hashnode.dev·Jan 14, 2024Bias Variance TradeoffIntroduction Having a proper understanding of Bias and Variance, is the key to achieve accuracy and robustness for your machine learning model. It helps us address the issue of Overfitting and Underfitting The Basic : Why Worry About Overfitting and ...Palak Varma and 3 others are discussing this4 people are discussing thisDiscuss·25 likes·160 readsMachine Learning
Aviral Srivastavaaviralcodess.hashnode.dev·Dec 24, 2023More Than a Glitch: A Humorous and Thought-Provoking Look at Tech Bias"More Than a Glitch" is a book by Meredith Broussard that explores the role of technology in society, particularly how it can perpetuate social inequalities. The book argues that the idea of technology as a neutral force is a myth and that it's impor...Discuss·16 likes·62 readstechnology
Joshua Ofosujoeokat.hashnode.dev·Sep 29, 2023Unveiling the Bias Challenge in UX DesignLet's talk about something we all have – biases. They're pretty normal, but when you're a UX designer, it's crucial to minimize them during your research. Why? Because this helps you truly understand what your users need. Now, let's break this down. ...DiscussBias
