I built a VR and AI microverse explorer

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https://dynamoid.com/blog/10k-science-launch It all started when I got an NSF grant back in 2010 and produced the award-winning app, Powers of Minus Ten (as seen in the original iPad 2 commercial "Alive" https://www.youtube.com/watch?v=JYmXvOeoNk0). The idea actually came from the planetarium community, who wanted a way to explore real scientific datasets on the dome. Since at the time I was producing 3D dome shows about biology and using real structural datasets, I was like "I want to make this happen." Long story short, it was a success (700,000+ downloads) but producing new content was a super manual process and it wasn't feasible for a small team to produce enough to make it work financially. So we switched to automating the data visualization pipelines, boostrapping through contracts. Around 2015 when VR became a thing (again), we saw that there was an opportunity beyond a cool way to view our content - for the first time it became possible for non-3d experts to produce 3D content and we realized we could get scientists/researchers to directly import and visualize their data. We worked on the VR creator tools to make this a reality, worked with scientists to visualize their data, worked with our educational partners to adapt the content for educational contexts. Several pilots and one NIH grant later, we're launching 10k Science on Meta Quest App Lab today. Just in the last couple months, we've done some really exciting work with OpenAI APIs to create audio tours with GPT-powered Q&A around the content (in my opinion, the real game changer here, I'm incredibly excited about it) You can grab it here, it's free: https://www.meta.com/experiences/5616986801647861/ More info: https://dynamoid.com/blog/10k-science-launch 10k Science: https://10k.science

Visit product View on Hacker NewsDec 20, 2023

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

90%90% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

58%58% 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 · Strong signals: month, visualize, way · Missing: mobile apps, ios, personal

57%57% 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

37%37% 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

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

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

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

Incorrect prediction on native model

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