Say: Remember Everything (open source)

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An open source approach to remotely transcribe everything you say on your Apple Silicon computer. Note: Relies on Apple Silicon, and configured to only produce Apple Silicon builds. I think the idea of transcribing everything you say has the potential to change how we interact with our computers, and believe it should be open source. By "it", I mean everything you say. Also, from a privacy / security perspective, this is like... pretty scary stuff, and I want the code open so we know for certain that everything is leaving your laptop. It's like exposure therapy: if it hurts, do it more often. (Copycat of "Show HN: Rem: Remember Everything (open source)" by jasonjmcghee) Original Post: https://news.ycombinator.com/item?id=38787892

Visit product View on Hacker NewsDec 31, 2023

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

87%87% 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: open source, ide · Missing: https docs, excited, just released

76%76% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

52%52% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

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

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

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

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

13%13% 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

3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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