Neel Jabuvani·Oct 20Bidirectional RNNs : How AI Understands Context from Both DirectionsIntroductionA response icon6A response icon6
Sharad Bharadwaj·Mar 29The AI Series : Transformer Architecture 101: Encoder vs Decoder (BERT vs GPT)Stop using massive chat models for everything. Here is how to actually choose the right AI engine for your architecture. — By Sharad…A response icon2A response icon2
Nishita Jain·Mar 14Why Your AI Forgets What It Just ReadThe memory problem that stumped researchers for a decade and the beautiful failure that led to transformers.A response icon1A response icon1
Tushar Soni·Jan 23Simple to Advance RNN (Part 1)In the 1990s, when the groundwork for contemporary computer vision was laid, cognitive scientist Jeffrey Elman introduced the Recurrent…
Sivaram S·Nov 30, 2025Predicting Overhang Defects in 3D Printing: A CNN-RNN Pipeline for Real-Time Melt Pool InsightsTackling overhang defects in laser powder bed fusion with deep learning. From 766 layers of sensor data to predictive insights — R²=0.87…
Rezowanur Rahman Robin·Aug 15, 2025The Attention Mechanism: Understand the in depth architectureIntroduction
Rezowanur Rahman Robin·Aug 14, 2025Bidirectional RNNs: Unlocking Deeper Context in Sequential DataIntroductionA response icon1A response icon1
Gaurang Solanki·Jul 28, 2025Attention Changes Everything: Focus Like a HumanTools like ChatGPT or Google Gemini can process language in a way that feels natural. This post explains the idea called Attention that…
Komal Mandal·Jul 5, 2025Working of RNN, LSTM,GRU and Bidirectional Models with Practical Python ImplementationIn this article, we explore how RNN, LSTM, GRU, Bidirectional LSTM work, and how they are used to process and learn from sequential data…
