Think AI means massive models, GPUs, and compliance reviews? Think again. The same mathematical magic that powers search engines, recommendation systems, and knowledge graphs is already at your fingertips, and it’s calle…
Think AI means massive models, GPUs, and compliance reviews? Think again. The same mathematical magic that powers search engines, recommendation systems, and knowledge graphs is already at your fingertips, and it’s called embeddings.
We’ll uncover how embeddings quietly encode meaning, context, and relationships into numbers and how you can harness them to bring “smart” features into your existing stack today. From semantic search to personalized recommendations and intelligent knowledge retrieval, you’ll see how embeddings turn ordinary data into something that understands.
You’ll learn: - How embeddings capture the meaning behind text, images, and more - Practical patterns for search, recommendation, clustering, and knowledge bases - How to build embedding-powered features with minimal setup - How embeddings can be your on-ramp to AI — without diving into LLM chaos
Bring your curiosity and leave knowing how to add genuine intelligence to your apps today. Sobre Alex Soto: Alex Soto is a Developer Advocate at IBM. He is passionate about the Java world and software automation and believes in the open-source software model. Alex is the co-author of Manning and O'Reilly books Testing Java Microservice, Quarkus Cookbook, Kubernetes Secrets Management, GitOps Cookbook, RHCE Ansible Automation Study Guide, Applied AI for Enterprise Java Development, and AI Agents with Java. A Java Champion since 2017, he is also an international speaker (Devoxx, KubeCon, DevNexus, JavaOne, JavaLand, ...) and teacher at Salle URL University. You can follow him on Twitter (@alexsotob) to stay tuned to what’s happening in Java.
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