The Worst Ways to Use AI Are the Ones That Feel Productive
Author(s): Hayanan Originally published on Towards AI. Nine ordinary AI habits that quietly waste time, weaken judgment, and create technical problems, and how to replace them with workflows you can actually trust. The moth is still there, under a piece of aging …
Can We Kill the Term “Artificial Intelligence” Yet?
Author(s): Hayanan Originally published on Towards AI. Calling everything AI is a little like giving every variable in a program the type any. It saves us the trouble of being specific. It also hides the mistakes we most need to catch. I …
Surviving the Tectonic Shifts in Large Language Model Scaling: A Field Guide for Practitioners
Author(s): Hayanan Originally published on Towards AI. In January 2025, DeepSeek released a technical report that caused OpenAI, Anthropic, and Google to convene emergency meetings. The report described a frontier language model 671 billion parameters, performance matching GPT-4 on virtually every benchmark …
Vector Databases: Unlocking the Future of Intelligent AI and Semantic Search
Author(s): Hayanan Originally published on Towards AI. How AI Learns Meaning, Not Just Keywords Modern AI systems are no longer judged by how fast they retrieve data, but by how well they understand it. As users interact with applications in increasingly natural …
From Perceptrons to Sigmoid Superstars: Building Smarter Neural Networks
Author(s): Hayanan Originally published on Towards AI. Unveiling the Magic of Gradient Descent, Feedforward Architectures, and Universal Function Approximation in AI Neural networks form the backbone of modern artificial intelligence, powering breakthroughs in computer vision, natural language processing, recommender systems, and scientific …
Recent Posts
![[Day 37/100] Build Your Own Agent Memory Layer with Postgres and pgvector](https://miro.medium.com/v2/resize:fit:700/1*-Doos2nmUT3FPZ-Qxbk3Hw.png "[Day 37/100] Build Your Own Agent Memory Layer with Postgres and pgvector")
