<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/eb44015201554d11ac841cd1700653ce&quot; frameborder=&quot;0&quot; width=&quot;1220&quot; height=&quot;915&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>915</height><width>1220</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>915</thumbnail_height><thumbnail_width>1220</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/eb44015201554d11ac841cd1700653ce-1e812004e9bff2a0.gif</thumbnail_url><duration>102.605</duration><title>y30 voice AI: an unscripted reminiscence call</title><description>An unscripted conversation with y30, the voice AI I&apos;m building for older adults and their caregivers.

The thing to watch is the turn-taking: it waits through a long mid-thought pause without cutting in, and yields the instant I interrupt it.

When the conversation turns to my late mother, it softens its tone on its own.

Under the hood it&apos;s a streaming speech-to-text to LLM to text-to-speech pipeline with deterministic flow control and a safety floor that runs independent of any model, every conversation becomes structured signal a caregiver can act on.

Part of my portfolio: whoischrislam.github.io</description></oembed>