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A news website that writes itself with AI

Hacker News

A news website that writes itself with AI

I was playing with OpenAI text completion, and got curious what would happen if we had a new website full of ai-generated content, so I made one - SillyConeNews.com AI writes everything there: headlines, articles, summaries, and images. Right now it's using OpenAI, but I think I'll switch to Stable Diffusion for more interesting images. For some examples of blog posts that sound almost indistinguishable from real blogs like Tech crunch, take a look here http://sillyconenews.com/posts/ZmZjMTcwNjQt and here http://sillyconenews.com/posts/ZDQ2MzdkNjct . Note that for the FTX post, the model was trained on the data before the current events. The only manual process right now is prompt-initiation, but I am hoping to automate that as well by figuring out what is currently popular (off Google news...etc) and making AI write something similar. There is no real "business value" here, but just some fun.

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: model, google, new · Missing: mac, agents, macos
76%76% 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 · Missing: supports, reddit linkedin, podcasting
71%71% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
59%59% 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: google · Missing: mobile apps, ios, personal
54%54% 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
33%33% 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
15%15% 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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