Willow: the fastest and most private open source voice assistant

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Hey HN! Voice assistants like Amazon Alexa and Google Home have sold hundreds of millions of devices. Unfortunately, they come with less-than-ideal things like an always on microphone (doing who knows what), data collection, and limited integration options. Echo devices especially also end up being advertising billboards you pay for and install in your own home. No thanks, I've already heard of the Barbie movie... Willow is an open source hardware and supporting software voice assistant platform. For $50 Willow hardware (from Espressif) is competitive with commercial products in every regard while being open source and completely self-hosted. Did I mention it's at least twice as fast as Alexa? Willow supports integrations to Home Assistant, OpenHAB, and just about anything else with our REST command endpoint support. With our initial release Willow received overwhelming interest here on HN and elsewhere when we first announced it several months ago. Today (to the day) we're celebrating six months of Willow development! I made a (rare) demo video demonstrating our most recent release with features like wake only on device closest to the person talking, speaker voice authentication, dynamic configuration, over the air updates, device location, and our new web interface. All faster than ever. Check out our latest demo video: https://www.youtube.com/watch?v=qlhSEeWJ4gs The team and I really enjoyed the feedback and discussion in our first Show HN post months ago and we'd love to hear what you think about our progress. We also feel that at this point we've optimized accuracy and speed and are interested to hear any ideas for new functionality, etc.

Visit product View on Hacker NewsOct 12, 2023

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

93%93% 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.

Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created

87%87% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

65%65% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: video, month, google · Missing: mobile apps, ios, personal

40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

18%18% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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