Thoughts, learnings, and deep dives from my AI and full-stack journey.
What if AI didn’t just respond - but reasoned, planned, and acted? Generative AI agents are redefining intelligence by combining powerful language models with tools, real-world data, and decision-making frameworks. Like a master chef in a fast-paced kitchen, these agents observe, think, and execute - continuously adapting to achieve their goals. From ReAct to RAG, from APIs to orchestration layers, we’re stepping into an era where AI doesn’t just assist - it acts. Dive into the future of autonomous intelligence and discover how agents are transforming the way we build, think, and innovate.
Before 2017, models like RNNs and LSTMs processed text one word at a time, which meant: - Slow training - Poor long-term memory -No parallel processing Everything changed by Google 's paper “Attention Is All You Need” - Instead of reading sequentially - The model looks at all words at once and focuses on what matters most using Attention. This idea led to the Transformer, the foundation of modern models like GPT and BERT. In this article, we’ll quickly understand the paper and how Transformers works.
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