We just launched MegaAI. It's a 4k30fps, 4W, 4TOPS inference powerhouse

Hacker News

Hey HN - super exited to share with you the launch of MegaAI from Luxonis! MegaAI is a tiny module that unleashes the full power of Movidius' Myriad X VPU. We're starting things out with a Crowdsupply campaign with Early Bird edition price at only $149[1]. Damn good deal for a 4k30fps, 2.5W, 4TOPS device that's essentially plug-n-play over USB 3! The savvy among you might say, "but wait, isn't there a super expensive SDK that goes along with the Myriad X?" Don't worry! We took care of that with the DepthAI API![2] The DepthAI API allows pretty much anyone to dig into the functionality of the Myriad X VPU in order to run any model you can put through OpenVino. In fact, you can get MegaAI up and running with a Raspberry Pi in under 7 minutes.[3] Definitely checkout the Crowdsupply page for full set of specs[1]. Would love to hear your feedback! Thanks!! [1] https://www.crowdsupply.com/luxonis/megaai [2] https://github.com/luxonis/depthai [3] https://www.youtube.com/watch?v=RuzDiJuQswE

Visit product View on Hacker NewsMay 22, 2020

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

74%74% 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: io · Missing: https docs, excited, just released

68%68% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

34%34% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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