AI Answering
24/7 AI call center for inbound and outbound calls
What it does
AI Answering is a 24/7 AI call center that handles inbound calls, outbound follow-ups, intake, lead qualification, appointment scheduling, and call routing. Unlike tools focused only on answering calls, it supports the full call workflow from first contact through follow-up. Businesses can configure scripts, intake flows, routing rules, business hours, and human escalation around the way their team operates.
AI Answering is an intelligent AI voice agent that handles phone calls, schedules appointments, and engages clients 24/7 with natural, human-like conversations.
AI Answering is a 24/7 AI call center powered by AI voice agents and live human support, keeping every call answered and every lead captured. Handle inbound calls, outbound follow-ups, intake, and scheduling from one platform. Most answering services take messages and stop there. AI Answering is an AI call center built to manage the full call workflow, from answering the first call and capturing the lead to intake, follow-up, and a booked appointment. The only call center that answers every incoming call and proactively makes outbound follow-up calls from one platform. Full AI handling for routine calls. Live human agents step in for complex situations. You control when and how. Intake,…from aianswering.ai
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
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I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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