Assess the Role of AI in Your Product: Determine whether AI is the central component of your product, an enhancement to existing features, or a tool for internal improvement. This understanding is critical for formulating your product strategy, estimating resources, and ensuring the feasibility of your AI integration. For instance, integrating pre-trained Large Language Models can extend the value of products like Notion and Miro, transforming them into innovative AI-powered services.
Understand the Nature of Your Learning Problem: AI, at its core, is about learning. Define your learning problem by understanding the inputs and expected outcomes. Ensure that the inputs contain appropriate learning signals that allow the model to generalize to new examples. For example, in sentiment analysis, words like “enjoyed” or “fantastic” can be strong indicators of positive sentiment and serve as learning signals for the model.
From Human-in-the-Loop Machine Learning by Robert (Munro) Monarch
From Machine Learning for Business by Doug Hudgeon and Richard Nichol
In this article, you’ll see how SageMaker and the Random Cut Forest algorithm can be used to create a model that will highlight the invoice lines that Brett should query with the law firm. The result will be a repeatable process that Brett can apply to every invoice that will keep the lawyers working for his bank on their toes and will save the bank hundreds of thousands of dollars per year. Off we go!
From Math for Programmers by Paul Orland
Six Questions for Yan Cui, instructor of Production-Ready Serverless
Bio: Yan Cui has worked with AWS for almost a decade, and has contributed his knowledge of production AWS Lamda to the Well-Architected whitepaper published by AWS. Based in London, he travels all over the world giving talks and workshops on serverless. This year he has presented in Copenhagen, Milan, Las Vegas, Portland, Tel Aviv, Krakow, and many more. His blog on The Burning Monk covers his favorite topics, including AWS, serverless, functional programming and chaos engineering.
From Machine Learning for Business by Doug Hudgeon, and Richard Nichol
From Writing Great Specifications by Kamil Nicieja
A ubiquitous language has to be a language that grows out of blending technological expertise with business expertise in reasonable proportions. This article discusses how to ‘distill’ business domains from the ubiquitous language of a business or project.
From Writing Great Specifications by Kamil Nicieja
This article dives head-first into writing specifications using Specification by Example and Gherkin.
