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Ethan Caballero ✓

@ethanCaballero · joined 12 Jan 2015

ML @Mila_Quebec ; previously @GoogleDeepMind

13 044Followers
2 068Following
4 723Posts total
610.9KViews on collected posts

Latest posts

This shot from the trailer is the dinner in which OpenAI was founded. The dinner attendees in this shot are: sam, greg, ilya, dario, elon, paul christiano, jacob steinhardt, chris olah, and patrick collison https://t.co/oLP2Att7fq
52.9K views · 407 likes · 5 reposts · 5 replies Open on X →
@ethanCaballero I don’t understand why they make doc examples so hard to read. It’s complexity for the sake of complexity The first sentence was enough to make me roll my eyes > Mannered prose substitutes metaphor and flourish for direct statement 20.8K views · 71 likes · 0 reposts · 7 replies Open on X →
@ethanCaballero amusingly, the entire prompt is also 100% on pangram the prompt itself contains claudese "it makes the reader work harder so the writer can perform." So I am sceptical that a claudese prompt can dispel claudese 13.8K views · 78 likes · 0 reposts · 3 replies Open on X →
@ethanCaballero Oh so it’s called “mannered prose”? In contrast to the ill-mannered prose I’ve been responding to Claude with when it writes in Claudish 14.4K views · 66 likes · 1 reposts · 0 replies Open on X →
anthropic released a new prompt that eliminates claudese: https://t.co/JYHotoZlyr 452.3K views · 2.6K likes · 161 reposts · 67 replies Open on X →
does fable 5.1 eliminate the claudese? 6.9K views · 8 likes · 0 reposts · 5 replies Open on X →
@ 6:57:10 onward: https://t.co/6ABdPtYE5m 815 views · 1 likes · 0 reposts · 0 replies Open on X →
New paper: We present a "Unified Neural Scaling Law" functional form that accurately models & extrapolates the multivariate scaling behaviors of artificial neural networks as the variables listed in this attached video are varied. (1/N) https://t.co/wAZEXZDzRX
0:13
48.9K views · 484 likes · 63 reposts · 12 replies Open on X →

Against accounts of the same size

7 posts from the last 90 days, next to the 10K–100K follower range. shown widely, but few of those viewers react.

Median views14 431this account924median for 10K–100K
Reach, %110.63%this account3.62%median for 10K–100K
Engagement, %0.46%this account1.52%median for 10K–100K
MetricThis accountMedian for 10K–100KRatio
Median views per post14 43192415.6×
Reach (views ÷ followers)110.63%3.62%30.6×
Engagement rate0.46%1.52%0.31×

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

48.9K27 May
81527 Aug
6.9K1 Sep
452.3K2 Sep
14.4K
13.8K
20.8K
52.9K9 Sep

Last 8 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

1.15%27 May
0.12%27 Aug
0.19%1 Sep
0.64%2 Sep
0.46%
0.59%
0.38%
0.79%9 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.

What the audience does

Likes36.3%3 737 in total
Reposts2.2%230 in total
Replies1.0%99 in total
Quotes0.4%42 in total
Bookmarks60.1%6 199 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.

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