Denis Rothman

Building Business-Ready Generative AI Systems (eBook, ePUB)

Build Human-Centered Generative AI Systems with Agents, Memory, and LLMs for Enterprise

• Format: ePub

Produktbeschreibung

In today's rapidly evolving AI landscape, standalone LLMs no longer deliver sufficient business value on their own. This guide moves beyond basic chatbots, showing you how to build advanced, agentic ChatGPT-grade systems capable of sophisticated semantic and sentiment analysis, powered by context-aware AI controllers. You'll design AI controller architectures with multi-user memory retention to dynamically adapt your system to diverse user and system inputs. You'll architect a Retrieval-Augmented Generation (RAG) system with Pinecone, designed to combine instruction-driven scenarios. Enhance your system's intelligence with powerful multimodal capabilities-including image generation, voice interactions, and machine-driven reasoning-leveraging Chain-of-Thought orchestration to address complex, cross-domain automation challenges. Seamlessly integrate generative models like OpenAI's suite and DeepSeek-R1 without disrupting your existing GenAISys ecosystem. Your GenAISys will apply neuroscience-inspired insights to marketing strategies, predict human mobility, integrate smoothly into human workflows, visualize complex scenarios, and connect to live external data, all wrapped in a polished, investor-ready interface. By the end, you'll have built a GenAISys capable of deploying intelligent agents in your business environment.

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Produktdetails

• Verlag: Packt Publishing
• Seitenzahl: 444
• Erscheinungstermin: 25. Juli 2025
• Englisch
• ISBN-13: 9781837020683
• Artikelnr.: 75178324

Autorenporträt

Denis Rothman graduated from Sorbonne University and Paris-Diderot University, designing one of the very first word2matrix patented embedding and patented AI conversational agents. He began his career authoring one of the first AI cognitive Natural Language Processing (NLP) chatbots applied as an automated language teacher for Moet et Chandon and other companies. He authored an AI resource optimizer for IBM and apparel producers. He then authored an Advanced Planning and Scheduling (APS) solution used worldwide.