BensenHsu ✓
@BensenHsu
Founder @OpenRead_HQ | Quantum computing YouTuber
3 048Followers
774Following
4 994Posts total
893.5KViews on collected posts
Growth & engagement
How the posts we collected actually performed: views and reaction rate post by post, what the audience did with them, and where the follower count goes.
Views per post
883.4K14 Nov
9.8K15 Nov
24217 Nov
Last 3 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.
Engagement rate per post
0.21%14 Nov
0.65%15 Nov
0.83%17 Nov
Reactions — likes, reposts, replies and quotes — divided by views.
What the audience does
Likes53.5%1 292 in total
Reposts17.5%424 in total
Replies2.3%56 in total
Quotes6.0%144 in total
Bookmarks20.7%501 in total
Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.
The follower curve appears once this account has two daily snapshots — we take one a day, and this one is on its first.
Latest posts
@BensenHsu @ScienceMagazine sol
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51Axtj7EEhstjv9yGDwq9Wzz5t484NgMrtgBEm7pump https://t.co/peJE6xJUgR
242 views · 2 likes
· 0 reposts · 0 replies
17 Nov 2024
· Open on X →
@ScienceMagazine The study focuses on Evo, a genomic foundation model trained on 2.7 million evolutionarily diverse prokaryotic and phage genomes. The goal is to learn the fundamental grammar of DNA, which can then be used for various sequence modeling, prediction, and design tas
9.8K views · 49 likes
· 11 reposts · 3 replies
15 Nov 2024
· Open on X →
A new Science study presents “Evo”—a machine learning model capable of decoding and designing DNA, RNA, and protein sequences, from molecular to genome scale, with unparalleled accuracy.
Evo’s ability to predict, generate, and engineer entire genomic sequences could change the
883.4K views · 1.2K likes
· 413 reposts · 53 replies
14 Nov 2024
· Open on X →
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