@thomasabato
Tribe v2 is insane, I have to use this more. What I found interesting was someone tested a bunch of YouTube thumbnails and it wasn't the one that lit up the brain most that went viral, it were the ones that lit up the least... scary lol
70% supportive, 15% confronting responses to a tweet about predicting video virality with a local model. Overview of support, key objections, and engagement.
YOU CAN NOW PREDICT IF A VIDEO WILL GO VIRAL BEFORE POSTING IT USING A LOCAL MODEL https://t.co/GZwe3QFksy
Real-time analysis of public opinion and engagement
What the community is saying — both sides
Multiple replies ask bluntly: “Where can I run Tribe v2?” — people can’t find how or where to use it.
Users call Tribe v2 “insane” and a “game‑changer” because it can predict virality before posting and inform what to make.
Several replies fear Meta or other players training local models on user data and using brain‑prediction tech in harmful ways.
One experiment found thumbnails that “lit up the least” were likeliest to go viral, suggesting the model surfaces non‑obvious predictors.
A user who trained it on shorts saw the model flag 90% as flops and was often right, but the “hits” still needed paid boosts to reach large audiences.
People note you can build this if you know how to assemble systems — and others shared a public GitHub repo analyzing thumbnails and pages using BERG/TRIBE.
Commenters see this as AI making choices before humans react — a nascent field of “trend/viral prediction.”
models that learn from what already went viral will prioritize familiar patterns, making it harder for genuinely novel or breakthrough ideas to surface.
if every creator uses tools to engineer maximal neural engagement, attention spans could shrink and manipulative content becomes widely accessible, not just to big companies.
experienced creators claim they already predict what will work and therefore don’t need algorithmic guidance.
Most popular replies, ranked by engagement
Tribe v2 is insane, I have to use this more. What I found interesting was someone tested a bunch of YouTube thumbnails and it wasn't the one that lit up the brain most that went viral, it were the ones that lit up the least... scary lol
earlier the algorithms to what will work were just guesses and now if every creator will use this and design high dopamine content then attention span which is already at low will go down further future is scary where not just big companies even small creators will ha
this is actually insane predicting virality before you even post if you actually think about it, AI making decisions before humans even react is the whole game and we're just getting started 👀
trained one on our shorts, it flagged 90% as flops and was right 8/9 times. the "hits" still needed paid boost to break 50k views
well, I already know it before posting any video. So, I dont need it.
if it's trained on past virality, you're optimizing for what already saturated the feed, not what breaks through it.
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