Pedro Domingos ✓

@pmddomingos · Seattle, WA · joined 07 Jul 2015

Professor of computer science at UW and author of '2040' and 'The Master Algorithm'. Into machine learning, AI, and anything that makes me curious.

134 580Followers

178Following

26 794Posts total

1.9MViews on collected posts

Neueste Beiträge

Pedro Domingos ✓@pmddomingos14 Sep

@pmddomingos How did you estimate this ? 27.9K views · 66 likes · 0 reposts · 10 replies Open on X →

Pedro Domingos ✓@pmddomingos13 Sep

@pmddomingos That’s the really crazy number, but AI is improving rapidly 337.6K views · 5.6K likes · 240 reposts · 418 replies Open on X →

Pedro Domingos ✓@pmddomingos13 Sep

@pmddomingos Training time, humans 1B years LLM 10 years 4.6K views · 169 likes · 0 reposts · 12 replies Open on X →

Pedro Domingos ✓@pmddomingos12 Sep

IQ points per watt: Humans: 5 AI: 0.000001 512K views · 5.4K likes · 326 reposts · 260 replies Open on X →

Pedro Domingos ✓@pmddomingos10 Sep

@pmddomingos Thanks for letting know, I’ve been trying to create an infinite vortex in my teacup for an hour now 1.1K views · 16 likes · 0 reposts · 0 replies Open on X →

Pedro Domingos ✓@pmddomingos10 Sep

@pmddomingos And here I was worried about my water faucet exploding 2.1K views · 43 likes · 0 reposts · 1 replies Open on X →

Pedro Domingos ✓@pmddomingos10 Sep

@pmddomingos And because of the sound speed. Fluids with higher velocity stop being incompressible 576 views · 9 likes · 0 reposts · 0 replies Open on X →

Pedro Domingos ✓@pmddomingos10 Sep

BTW, in the real world fluids can't accelerate to infinite speeds because of special relativity. 46K views · 594 likes · 28 reposts · 56 replies Open on X →

Pedro Domingos ✓@pmddomingos9 Sep

@pmddomingos I think it's simpler than that: acceleration is linear in force, but it doesn't mean that the resulting motion can't be nonlinear. 4K views · 11 likes · 0 reposts · 0 replies Open on X →

Pedro Domingos ✓@pmddomingos9 Sep

A: Because in Navier-Stokes the velocity is not the velocity of a particle, but the velocity at a point. The particle at a point keeps changing, and the faster the motion, the faster it changes, making the acceleration quadratic. Without this there'd be no turbulence. (2/2) 12.9K views · 179 likes · 4 reposts · 7 replies Open on X →

Pedro Domingos ✓@pmddomingos9 Sep

Q: Navier-Stokes is just Newton's laws for fluids, and Newton's laws are linear, so why is Navier-Stokes nonlinear? (1/2) 74K views · 328 likes · 26 reposts · 19 replies Open on X →

Pedro Domingos ✓@pmddomingos9 Sep

AlphaGo did not beat Lee Sedol. The humans who built AlphaGo beat Lee Sedol. 4.2K views · 48 likes · 5 reposts · 11 replies Open on X →

Pedro Domingos ✓@pmddomingos9 Sep

Resist the delusional/dishonest attempt by OpenAI and Anthropic to redefine AGI as what they've already done. 6.7K views · 196 likes · 26 reposts · 20 replies Open on X →

Pedro Domingos ✓@pmddomingos9 Sep

And meanwhile LLMs still can't add two numbers of arbitrary length. 10.2K views · 132 likes · 8 reposts · 27 replies Open on X →

Pedro Domingos ✓@pmddomingos22 Oct 2025

Slides from the @ECMLPKDD 2025 opening keynote: https://t.co/hQaSaxJeZP 9.1K views · 20 likes · 3 reposts · 4 replies Open on X →

Pedro Domingos ✓@pmddomingos15 Oct 2025

@pmddomingos @pmddomingos where is the compiler/interpreter, system libs, an examples repo? 10.1K views · 26 likes · 0 reposts · 1 replies Open on X →

Pedro Domingos ✓@pmddomingos15 Oct 2025

I've found the path to AGI: https://t.co/NRvZViBVUc 802.9K views · 2.1K likes · 258 reposts · 205 replies Open on X →

Im Vergleich zu Konten gleicher Größe

14 Beiträge aus den letzten 90 Tagen, verglichen mit der Größenklasse 100K–1M Follower. wird weit über das eigene Publikum hinaus gezeigt, und es reagiert.

Medianaufrufe8 413dieses Konto5 983Median für 100K–1M

Reichweite, %6.25%dieses Konto1.49%Median für 100K–1M

Interaktion, %1.53%dieses Konto0.93%Median für 100K–1M

Kennzahl	Dieses Konto	Median für 100K–1M	Verhältnis
Medianaufrufe pro Beitrag	8 413	5 983	1.41×
Reichweite (Aufrufe ÷ Follower)	6.25%	1.49%	4.20×
Interaktionsrate	1.53%	0.93%	1.64×

Weitere Konten dieser Größe → Mit einem anderen Konto vergleichen → Wie diese Vergleichswerte entstehen →

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

10.2K9 Sep

6.7K

4.2K

74K

12.9K

46K10 Sep

576

2.1K

1.1K

512K12 Sep

4.6K13 Sep

337.6K

27.9K14 Sep

Last 14 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

1.68%9 Sep

3.70%

1.62%

0.51%

1.48%

0.28%

1.47%10 Sep

1.56%

2.08%

1.49%

1.20%12 Sep

3.97%13 Sep

1.87%

0.28%14 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 0.93%.

What the audience does

Likes72.7%14 985 in total

Reposts4.5%924 in total

Replies5.1%1 051 in total

Quotes1.0%207 in total

Bookmarks16.7%3 436 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.

Neueste Beiträge

Im Vergleich zu Konten gleicher Größe

Growth & engagement

Views per post

Engagement rate per post

What the audience does

Ähnliche Konten