openai-realtime-embedded-SDK Build AI assistants on microcontrollers

Hacker News

Hi HN! This is an SDK for ESP32s (microcontrollers) that runs against OpenAI's new WebRTC service [0] My hope is that people can easily add AI to lots of 'real' devices. Wearable devices, speakers around the house, toys etc... You don't have to write any code, just buy a device and set some env variables. If you have any feedback/questions I would love to hear! I hope this kicks off a generation of new interesting devices. If you aren't familiar with WebRTC it can do some magical things. Check out WebRTC for the Curious[1] and would love to talk about all the cool things that does also. [0] https://platform.openai.com/docs/guides/realtime-webrtc [1] https://webrtcforthecurious.com

Visit product View on Hacker NewsDec 18, 2024

Share card

Actual performance

63points

14comments

Made the leaderboard

Launch Intel predictions

Analyze your own launch →

Product HuntOn track for Day 1 leaderboard · Strong signals: new, openai, code · Missing: mac, agents, macos

82%82% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

56%56% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

30%30% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

4%4% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Zoom Meeting AI Assistants Powered by OpenAI's Realtime API59%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Zoom Meeting AI Assistants Powered by OpenAI's Realtime API

Hacker News6

SiteAssist80%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Build AI Assistants trained only on your own data

Product Hunt+103Productivity

Using OpenAI Realtime API to Build an AI Phone Agent: Video41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Using OpenAI Realtime API to Build an AI Phone Agent: Video

Hacker News1

Chat Interface for OpenAI Assistants47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Chat Interface for OpenAI Assistants

Hacker News9

a Lispy, embedded Forth48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

a Lispy, embedded Forth

Hacker News3

A Lispy, embedded Forth48%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A Lispy, embedded Forth

Hacker News61

G-

G-Fu – a pragmatic Lisp embedded in Go60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

G-Fu – a pragmatic Lisp embedded in Go

Hacker News123

Runnable embedded "Gists"40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Runnable embedded "Gists"

Hacker News3

Assistable?60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Skilled Assistants for Everyone!

Indie Hackers1marketplaces

Realtime AI and Telephony and DTMF61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Realtime AI and Telephony and DTMF

Hacker News2

Browse all products Analyze your launch