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ID

Stuart Sul ✓

@stuart_sul

ml @Cursor_ai (now @SpaceXAI), cs phd @Stanford, @HazyResearch

4 105Followers
162Following
135Posts total
104.8KViews on collected posts

Postingan terbaru

@stuart_sul @bilaltwovec @HazyResearch @pangram ai? (It's a good post, sir) 2K views · 5 likes · 1 reposts · 1 replies Open on X →
@stuart_sul @srush_nlp @HazyResearch Nice, I have a similar one! (https://t.co/PWZSvQkPZm) 1.2K views · 4 likes · 0 reposts · 0 replies Open on X →
@stuart_sul @HazyResearch well yes and no, please everybody!! pivot to verifiable and proved PL & TT approaches to making programs and gpu programs, not adding more arbitrary obscurity and interface layers 2.4K views · 4 likes · 0 reposts · 0 replies Open on X →
(6/6) Read the full blog post, written with @HazyResearch: https://t.co/oz1LD0qDOg 59.7K views · 215 likes · 17 reposts · 7 replies Open on X →
(5/6) We're no longer working with a dumb executor that needs every gap specified, but an intelligent executor that reads underspecified specs and does the right thing. It may be fuzzy, but the ideas travel better. 3.7K views · 33 likes · 0 reposts · 1 replies Open on X →
(4/6) Abstraction as a cognitive offloader is going obsolete. By induction, it appears all the beloved CUDA DSLs are next in line to retire. 11.5K views · 52 likes · 4 reposts · 3 replies Open on X →
(3/6) For instance, we built a library for writing megakernels last year (https://t.co/PO6Cu37FsP). Writing one from scratch was miserable, so we accepted limits like coarse shared memory granularity to overcome the complexity. Today, that tradeoff has become unnecessary. 3.1K views · 34 likes · 4 reposts · 1 replies Open on X →
(2/6) Why? Because the complexity those layers were hiding is now directly manageable, so the intermediate layers turn into pure overhead. 3K views · 37 likes · 1 reposts · 1 replies Open on X →
(1/6) If a prompt can generate every layer of the stack, what are programming abstractions worth? GPU programming is at a weird inflection point. For decades we stacked layers of abstraction to ease our cognitive load. This year, we find ourselves constantly deleting them. https 18.1K views · 184 likes · 32 reposts · 9 replies Open on X →

Dibandingkan akun berukuran sama

9 postingan dari 90 hari terakhir, dibandingkan dengan rentang under 10K pengikut. di bawah akun sekelasnya baik pada jangkauan maupun interaksi.

Median tayangan3 081akun ini4 175median untuk under 10K
Jangkauan, %75.05%akun ini250.82%median untuk under 10K
Interaksi, %0.51%akun ini1.41%median untuk under 10K
MetrikAkun iniMedian untuk under 10KRasio
Median tayangan per postingan3 0814 1750.74×
Jangkauan (tayangan ÷ pengikut)75.05%2.5× audience0.30×
Tingkat interaksi0.51%1.41%0.36×

Akun lain pada rentang ini →   Bandingkan dengan akun lain →   Bagaimana tolok ukur ini disusun →

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

18.1K5 Aug
3K
3.1K
11.5K
3.7K
59.7K
2.4K
1.2K
2K

Last 9 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

1.28%5 Aug
1.30%
1.27%
0.51%
0.91%
0.41%
0.17%
0.32%
0.35%

Reactions — likes, reposts, replies and quotes — divided by views. Median for under 10K accounts is 1.41%.

What the audience does

Likes55.6%568 in total
Reposts5.8%59 in total
Replies2.3%23 in total
Quotes0.9%9 in total
Bookmarks35.5%363 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.

Akun serupa