BURKOV ✓

@burkov · Québec, Canada · joined 14 Jun 2009

Books: https://t.co/0EmPM3De9B & https://t.co/45NGbbXIzC App: https://t.co/n2jvMtYhVm PhD in AI, author of 📖 The Hundred-Page LMs Book & The Hundred-Page ML Book

58 554Followers

127Following

24 406Posts total

91.8KViews on collected posts

Последние посты

BURKOV ✓@burkov7 Sep

@burkov The issue is that we expect it to know this. 1.7K views · 2 likes · 0 reposts · 1 replies Open on X →

BURKOV ✓@burkov7 Sep

The revolutionary doc2vec paper is now on @ChapterPal: https://t.co/4cb0RMCeRX This paper made the notion of a document/sentence embedding mainstream. And even if today doc2vec is no longer the SOTA algorithm, it has influenced everything we are taking for granted today. 1.3K views · 7 likes · 1 reposts · 1 replies Open on X →

BURKOV ✓@burkov7 Sep

@burkov You guys change your definition of agi constantly. 424 views · 2 likes · 0 reposts · 0 replies Open on X →

BURKOV ✓@burkov7 Sep

@burkov funny bar for agi, can it nail quadruped locomotion better than a physics engine from 2015 could 1.6K views · 12 likes · 0 reposts · 0 replies Open on X →

BURKOV ✓@burkov7 Sep

That what happens when your AI is primarily text-based. Try to verbally explain how a running animal must move. No, really, try it. 59.2K views · 242 likes · 9 reposts · 23 replies Open on X →

BURKOV ✓@burkov7 Sep

The paper addresses a core inefficiency in large language models: next-token prediction produces high-quality outputs but forces slow, sequential generation that wastes accelerator capacity and inflates latency and training cost, especially for long traces and concurrent agentic 1.4K views · 13 likes · 3 reposts · 4 replies Open on X →

BURKOV ✓@burkov7 Sep

Test-time scaling improves language model performance on hard problems by allowing longer reasoning traces, yet full attention keeps every prior token in memory. This causes compute costs to grow linearly with length, plus problems such as distraction by irrelevant tokens, 2K views · 22 likes · 2 reposts · 2 replies Open on X →

BURKOV ✓@burkov22 May

As you know, last year I resigned from my full-time job and become a professional technical book writer. I have plans for The Hundred-Page Books about reinforcement learning, computer vision, diffusion models, and more. Not having a full-time job has put a significant strain on

24.2K views · 61 likes · 4 reposts · 10 replies Open on X →

На фоне аккаунтов своего размера

7 постов за последние 90 дней рядом с диапазоном 10K–100K подписчиков. ниже своих по обоим показателям — и по охвату, и по отклику.

Медианные просмотры1 578этот аккаунт924медиана для 10K–100K

Охват, %2.69%этот аккаунт3.62%медиана для 10K–100K

Вовлечённость, %0.71%этот аккаунт1.52%медиана для 10K–100K

Показатель	Этот аккаунт	Медиана для 10K–100K	Отношение
Медианные просмотры на пост	1 578	924	1.71×
Охват (просмотры ÷ подписчики)	2.69%	3.62%	0.74×
Вовлечённость	0.71%	1.52%	0.47×

Другие в этом диапазоне → Сравнить с другим аккаунтом → Как считаются эти ориентиры →

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

24.2K22 May

2K7 Sep

1.4K

59.2K

1.6K

424

1.3K

1.7K

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

0.31%22 May

1.36%7 Sep

1.38%

0.47%

0.76%

0.47%

0.72%

0.18%

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

What the audience does

Likes70.5%361 in total

Reposts3.7%19 in total

Replies8.0%41 in total

Quotes0.6%3 in total

Bookmarks17.2%88 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.

Последние посты

На фоне аккаунтов своего размера

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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