Lak Lakshmanan

A framework to select the simplest, fastest, cheapest architecture that will balance LLMs’ creativity and risk Lak Lakshmanan · Follow Published in Towards Data Science · 16 min read · 9 hours ago — Look at any LLM tutorial and the suggested usage involves invoking the API, sending it a prompt, and using the response. Suppose you want the LLM to generate a thank-you note, you could do: import openairecipient_name = “John Doe”reason_for_thanks = “helping

Using Gemini + Text to Speech + MoviePy to create a video, and what this says about what GenAI is becoming rapidly useful for Lak Lakshmanan · Follow Published in Towards Data Science · 10 min read · 1 day ago — Like most everyone, I was flabbergasted by NotebookLM and its ability to generate a podcast from a set of documents. And then, I got to thinking: “how do they do that, and where

Comparing Autogen and LangGraph from a developer standpoint Lak Lakshmanan · Follow Published in Towards Data Science · 10 min read · 12 hours ago — GenAI models are good at a handful of tasks such as text summarization, question answering, and code generation. If you have a business process which can be broken down into a set of steps, and one or more those steps involves one of these GenAI superpowers, then you will