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Theos AI - development platform for AI

Hacker News

Theos AI - development platform for AI

Hey everyone! I created a startup with a friend to make it easier for anyone to create AIs without any prior experience or knowledge in the field. We started with computer vision, specifically object detection, but we plan to add all subfields of AI eventually, like natural language processing, speech and all the cool generative stuff. You can do everything inside the platform: create datasets, train artificial neural networks and use them to give intelligence to your web apps, mobile apps, machines, security cameras, robots, drones, cars and everything else. It is free to use forever without any credit card required. You can connect google colab notebooks to our platform and use their free GPUs for training. Forget about all the different labeling file formats and running complex code yourself, just connect colab to Theos, click the Start Training button and the metrics will stream directly to your browser, and we will automatically upload weights checkpoints every epoch so you don't have to worry about colab shutting down and losing all your AI training progress. Also, we have an autolabeler feature to let your current AI's version help you make a better version of itself 100 times faster than labeling manually. Finally, you can deploy your AI as a rest API and use it in your software with simple http requests. Here's the getting started guide for object detection: https://docs.theos.ai/get-started/object-detection Please let me know if you find it helpful and what subfield of AI you think we should tackle next. (the landing page is not finished yet, soon we will release a way better version, but for now you can sign up and use the app for free) Thanks!

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, started · Missing: supports, reddit linkedin, podcasting
89%89% 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: mac, google, apps · Missing: agents, macos, agent
86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
64%64% 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: mobile apps, apps, google · Missing: ios, personal, entrepreneurs
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, soon · Missing: plus, intuitive, reviews
34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: training · 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.

Incorrect prediction on native model

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