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Sergey Levine

@svlevine · Berkeley, CA · joined 29 Apr 2018

Associate Professor at UC Berkeley Co-founder, Physical Intelligence

136 192Followers
144Following
2 625Posts total
753.8KViews on collected posts

Against accounts of the same size

11 posts from the last 90 days, next to the 100K–1M follower range. shown widely, but few of those viewers react.

Median views48 357this account5 495median for 100K–1M
Reach, %35.51%this account2.30%median for 100K–1M
Engagement, %0.48%this account1.45%median for 100K–1M
MetricThis accountMedian for 100K–1MRatio
Median views per post48 3575 4958.80×
Reach (views ÷ followers)35.51%2.30%15.4×
Engagement rate0.48%1.45%0.33×

Others in this range →   Compare with another account →   How these benchmarks are built →

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

107.4K7 Aug
81.6K
110.3K12 Aug
38.6K14 Aug
256.6K15 Aug
5K
51616 Aug
463
68.2K24 Aug
36.7K26 Aug
48.4K

Last 11 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.48%7 Aug
1.02%
0.37%12 Aug
0.75%14 Aug
1.00%15 Aug
0.16%
0.39%16 Aug
0.43%
0.47%24 Aug
0.60%26 Aug
0.72%

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 1.45%.

What the audience does

Likes53.5%4 816 in total
Reposts6.1%546 in total
Replies1.2%112 in total
Quotes0.4%34 in total
Bookmarks38.8%3 491 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

Seohong wrote a mystery novel. You won't believe whodunit 48.4K views · 328 likes · 13 reposts · 5 replies 26 Aug 2026 Thanks Ryan for coming by! This was a fun chat. 36.7K views · 206 likes · 12 reposts · 3 replies 26 Aug 2026 Sergey Levine (@svlevine) is one of the world's top robotics researchers and co-founder of Physical Intelligence. We talked about where humanoid robotics is today, thoughts on the Chinese robotics ecosystem, and his predictions for future timelines. In this episode: • https:/ 68.2K views · 278 likes · 32 reposts · 5 replies 24 Aug 2026 @svlevine @seohong_park free and current is rare for a graduate course. thanks for putting it up. 463 views · 2 likes · 0 reposts · 0 replies 16 Aug 2026 @svlevine @seohong_park Seriously, this class is amazing. Thanks a alot🙏 516 views · 2 likes · 0 reposts · 0 replies 16 Aug 2026 @svlevine @seohong_park Your 2018 class was genuinely life-changing for me. Thank you for making it freely available, and for continuing to put your lectures out there. 5K views · 7 likes · 0 reposts · 1 replies 15 Aug 2026 Latest Deep RL class lectures are now online! https://t.co/GvqI1v3hgD Thanks to @seohong_park, we now have CS185/285 for spring 2026 available to everyone to watch. Course website here: https://t.co/U16rasTOAo Apologies for a few recording glitches (it's not a perfect system). 256.6K views · 2.2K likes · 302 reposts · 29 replies 15 Aug 2026 Chelsea doing another rock star presentation. Robots can indeed fold laundry and make espresso! 38.6K views · 274 likes · 11 reposts · 3 replies 14 Aug 2026 Robots can already fold laundry, make espresso, clean kitchens, and assemble things. The harder problem is getting them to do those tasks reliably, for long periods of time, without a human babysitting them. At Startup School 2026, @physical_int cofounder @chelseabfinn explains 110.3K views · 320 likes · 46 reposts · 37 replies 12 Aug 2026 Action chunking is a mysteriously effective method. Modern large-scale imitation learning basically doesn't work without it. But why does it actually help? In our new paper, we try to break down the reasons. As the saying goes, what happened next might surprise you... 81.6K views · 744 likes · 70 reposts · 16 replies 07 Aug 2026 Action chunking is a critical component in virtually all modern approaches to imitation learning for robotics. But why is it so critical, and do we really need action chunking? Check out our latest work to find out! (1/n) https://t.co/s5AYfCoVpG https://t.co/tXqhzeEXKo 107.4K views · 440 likes · 60 reposts · 13 replies 07 Aug 2026

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