Published inTowards Explainable AINew Trends in Large Reasoning Models for Machine TranslationLarge Reasoning Models (LRMs) challenge in Machine TranslationMar 19A response icon1Mar 19A response icon1
Published inAI Simplified in Plain EnglishReinforcement Learning (RL): Understanding Bellman Equation (Part-II)State Value, Bellman Equation, Action ValueMar 12Mar 12
Published inEveryday AITinyR1–32B-Preview: How Model Merging Bridges the Gap Between Small and Giant LLMs (DeepSeek-R1)Model Merging Arcee Fusion approach & Effective Model distillationMar 10Mar 10
Published inAI Simplified in Plain EnglishBeyond ChatGPT Voice: The Rise of Emotionally Intelligent AI VoicesHow Sesame is pioneering expressive and engaging AI conversationsMar 5A response icon1Mar 5A response icon1
Published inEveryday AIMeta’s SWE-RL: Reinforcement Learning Meets Software EngineeringSWE-RL: First approach to scale RL-based LLM reasoning on SEMar 2Mar 2
Published inEveryday AIClaude 3.7 Sonnet: The AI Revolution for Software EngineersBoosted Real-world software development taskFeb 25Feb 25
Published inEveryday AILLMs vs. Machine Translation: The Next Frontier of ChallengesStrengths, Limitations, and Future of AI in TranslationFeb 25Feb 25
Published inAI Simplified in Plain EnglishReinforcement Learning (RL): Basic Introduction (Part-I)State, Action, Policy, Reward & TrajectoryFeb 22Feb 22
Published inGenerative AIAttention in Transformer — Simple Diagram ExplanationToday, I will explain Attention used in the transformer in a much easier way, as much as possible to readers. To help readers understand…Feb 22Feb 22
X-ALMA: PLUG & PLAY MODULES AND ADAPTIVE REJECTION FOR QUALITY TRANSLATION AT SCALE — Explained…‘’Curse of Multilinguality — Reduces Quality in Translation’’Feb 19Feb 19
