Yaroslav Bulatov ✓

@yaroslavvb · San Francisco, CA · joined 26 Feb 2011

@southparkcommons (early OpenAI, Google Brain, Meta) https://t.co/bxo5udY3ib https://t.co/SLix8Hrt4w https://t.co/Ur3GWKpmp6

11 630Followers

1 153Following

2 480Posts total

62.7KViews on collected posts

Against accounts of the same size

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

Median views5 303this account1 637median for 10K–100K

Reach, %45.60%this account5.01%median for 10K–100K

Engagement, %1.15%this account1.81%median for 10K–100K

Metric	This account	Median for 10K–100K	Ratio
Median views per post	5 303	1 637	3.24×
Reach (views ÷ followers)	45.60%	5.01%	9.10×
Engagement rate	1.15%	1.81%	0.63×

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

39.4K23 Dec

1.2K26 Aug

1.2K28 Aug

9.4K30 Aug

11.5K4 Sep

Last 5 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.57%23 Dec

1.14%26 Aug

0.41%28 Aug

1.15%30 Aug

1.23%4 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.81%.

What the audience does

Likes55.6%444 in total

Reposts2.9%23 in total

Replies2.4%19 in total

Quotes1.1%9 in total

Bookmarks38.0%303 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

I sometimes ask people why we formulate learning algorithms the way we do. Do we need linear algebra? Do we need arithmetic? Stephen Wolfram tracked down root of some of the modern conventions to 1943 McCulloch/Pitts paper, and his reason was that "McCulloch really liked linear 11.5K views · 129 likes · 2 reposts · 9 replies 04 Sep 2026 Bill Dally argues that algorithmic complexity should be modeled in terms of movement on a 2D grid (2022 CACM), here's this model turned into competition https://t.co/0gS77mdHGq https://t.co/8FZ2S32uQ7 9.4K views · 96 likes · 10 reposts · 1 replies 30 Aug 2026 Overview Energy has an interesting take on datacenters in space: "power beats compute per unit of launch mass". IE, choose between 150 GW of solar panels+GPUs in space vs getting this amount of energy received at any point on Earth for the same price. 1.2K views · 5 likes · 0 reposts · 0 replies 28 Aug 2026 Thinking of criteria for simple yet relevant models of computation. We could start by banning all the "reward hacks" of impractical algorithms, below are some, any other examples? 1) Galactic Algorithms -> don't ignore constants 2) unbounded computation packed into a single 1.2K views · 12 likes · 1 reposts · 0 replies 26 Aug 2026 Gradients are energy-inefficient due to long-range dependencies, yet we lack a viable alternative. What if we crowdsource the discovery of what's next? Starting a weekly in-person reading group in SF. WebGPU, online learning, Hinton. Email yaro.slavvb@gmail.com. 39.4K views · 202 likes · 10 reposts · 9 replies 23 Dec 2025