Michael Black ✓

@Michael_J_Black

VP Digital Human Research, Epic Games. Emeritus Director, Max Planck Institute for Intelligent Systems (@MPI_IS). Opinions are my own.

104 024Followers

739Following

3 741Posts total

595.9KViews on collected posts

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Michael Black ✓@Michael_J_Black10 Sep

There are multiple things going on here that I didn't fully separate and that the comments bring out. * Academia does not have the resources to even evaluate top models as I suggest. This is a critical problem that should be addressed by a coordinated effort between the 4.6K views · 17 likes · 1 reposts · 1 replies Open on X →

Michael Black ✓@Michael_J_Black9 Sep

@Michael_J_Black This resonates with me. One option is to work less on solving tasks and more on understanding the solutions. A paper that analyzes Astra + open models might have more lasting impact than one that tries to solve a new task that Astra+ will inevitably solve. 5.5K views · 146 likes · 8 reposts · 6 replies Open on X →

Michael Black ✓@Michael_J_Black9 Sep

To be clear - I'm not knocking VIGA. I think VIGA is a great paper, which changed my thinking entirely. And it clearly changed the thinking of others. But all of this happened by putting it on arXiv and social media. The follow-on work on inverse graphics has happened outside of 9.9K views · 41 likes · 0 reposts · 1 replies Open on X →

Michael Black ✓@Michael_J_Black9 Sep

What is the role of academic computer vision research in the age of increasingly powerful large models? Is GPT-6 Astra a step change? How can a researcher have an impact today in academia? These are the questions I ask myself as I head off to ECCV 2026, a conference I’ve 576K views · 2.1K likes · 340 reposts · 85 replies Open on X →

เทียบกับบัญชีขนาดเดียวกัน

4 โพสต์จาก 90 วันที่ผ่านมา เทียบกับช่วง 100K–1M ผู้ติดตาม แสดงในวงกว้าง แต่มีผู้ชมตอบสนองน้อย.

ยอดดูมัธยฐาน7 666บัญชีนี้6 070ค่ามัธยฐานของ 100K–1M

การเข้าถึง, %7.37%บัญชีนี้1.62%ค่ามัธยฐานของ 100K–1M

การมีส่วนร่วม, %0.44%บัญชีนี้0.98%ค่ามัธยฐานของ 100K–1M

ตัวชี้วัด	บัญชีนี้	ค่ามัธยฐานของ 100K–1M	อัตราส่วน
ยอดดูมัธยฐานต่อโพสต์	7 666	6 070	1.26×
การเข้าถึง (ยอดดู ÷ ผู้ติดตาม)	7.37%	1.62%	4.55×
อัตราการมีส่วนร่วม	0.44%	0.98%	0.45×

บัญชีอื่นในช่วงนี้ → เปรียบเทียบกับบัญชีอื่น → ค่าอ้างอิงเหล่านี้คำนวณอย่างไร →

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

576K9 Sep

9.9K

5.5K

4.6K10 Sep

Last 4 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

0.45%9 Sep

0.43%

2.96%

0.44%10 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 0.98%.

What the audience does

Likes60.3%2 288 in total

Reposts9.2%349 in total

Replies2.4%93 in total

Quotes1.6%62 in total

Bookmarks26.4%1 004 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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เทียบกับบัญชีขนาดเดียวกัน

Growth & engagement

Views per post

Engagement rate per post

What the audience does

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