AI’nt That Easy #36: Build Crew Agent GeneratorLast month, I found myself drowning in AI agent configurations. As a developer working on multiple AI projects, I was spending hours…13h ago13h ago
AI’nt That Easy #35: Large-Scale Algorithms in the Age of LLMsPerformance, Elasticity, and Parallel Processing1d ago1d ago
AI’nt That Easy #34: Vertical AI Agents ExplainedYou’re the CEO of a company in a specialized domain. Every hire you make is carefully chosen, every role assigned based on the unique…Jan 18Jan 18
AI’nt That Easy #33: IBM Docling with CrewAI and WatsonX🔔 This tutorial is originally published at developer.ibm.comJan 111Jan 111
AI’nt That Easy #32: From Messy Data to Answers: Simplifying Workflows with LLMsImagine you’re running a customer support team for a fast-growing tech company. Every day, you’re bombarded with thousands of tickets, chat…Jan 7Jan 7
AI’nt That Easy #31: LCM vs LLMIn late 2022, the release of ChatGPT brought AI into the global spotlight, and with it, the rise of Large Language Models (LLMs). These…Jan 7Jan 7
AI’nt That Easy #30: MLOps for LLM (LLMOps) vs. LLM System DesignLarge Language Models (LLMs) are transforming the world, powering everything from chatbots to automated content generation. But here’s the…Dec 16, 2024Dec 16, 2024
AI’nt That Easy #29: Systematic Approach to Solving ML System Design Problems: Advanced Generative…In building an end-to-end machine learning system, the journey often begins with selecting the right database, tailored to the data type…Dec 11, 2024Dec 11, 2024
AI’nt That Easy #28: Evaluating LLM AgentsWe have come a long way from building models to working on models directly. Large Language Models (LLMs) have become indispensable tools…Dec 2, 2024Dec 2, 2024
AI’nt That Easy #27: How to Calculate the Cost of Running LLM-Based Applications in ProductionLaunching and scaling an LLM-powered application in production can be expensive. Whether you’re a startup or an enterprise, understanding…Dec 1, 2024Dec 1, 2024
