Editing Openai/691bd6f8-a5e8-8005-9752-1925a60e6a18 (section)

=== Short summary (TL;DR) ===
* Early Alexa used engineered, modular pipelines (wake-word → ASR → NLU → dialog manager → scripted responses + TTS) and a human-designed “brand voice” to sound friendly, helpful, and efficient. About Amazon<ref>{{cite web|title=About Amazon|url=https://www.aboutamazon.com/news/devices/how-our-scientists-are-making-alexa-smarter|publisher=About Amazon|access-date=2025-11-20}}</ref>
* Training relied heavily on curated voice recordings, large labeled speech/NLU datasets (Appen & crowd annotators), supervised learning and manual conversation design. Encyclopedia Britannica<ref>{{cite web|title=Encyclopedia Britannica|url=https://www.britannica.com/technology/Amazon-Alexa|publisher=Encyclopedia Britannica|access-date=2025-11-20}}</ref>
* Research programs (Alexa Prize, Amazon Science) and lots of human-in-the-loop labeling improved multi-turn conversation and engagement over years. Amazon Science<ref>{{cite web|title=Amazon Science|url=https://www.amazon.science/alexa-prize|publisher=Amazon Science|access-date=2025-11-20}}</ref>
* Alexa+ moves Alexa from mostly scripted/modular responses to a generative-AI backbone (LLMs + retrieval from Alexa’s knowledge + safety filters), more contextual, more “natural” and personalized — trained with modern LLM methods (supervised fine-tuning, human preference data and RLHF workflows), and heavier cloud processing. About Amazon<ref>{{cite web|title=About Amazon|url=https://www.aboutamazon.com/news/devices/new-alexa-generative-artificial-intelligence|publisher=About Amazon|access-date=2025-11-20}}</ref>

Below is a bit more detail, with what Amazon themselves and reporters have documented.