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Awni Hannun ✓

@awnihannun · joined 31 Jan 2011

ow knee

44 972Followers
357Following
5 064Posts total
2.4MViews on collected posts

Ultimi post

> Apple already offers a tool for efficiently running AI models on Apple hardware called MLX Let's go! 8.2K views · 81 likes · 6 reposts · 5 replies Open on X →
Apple is plotting a return to selling enterprise servers for the first time since 2011, and is talking to Nvidia about providing the networking tech Relations between Apple and Nvidia appear to be warming up https://t.co/oiC3NaMu6m https://t.co/AH2YKCSoRW
10.3K views · 9 likes · 5 reposts · 2 replies Open on X →
$47.9 million mistake not naming the company 🫶 Heart Hands 83.9K views · 672 likes · 20 reposts · 12 replies Open on X →
Qwen 27B dense at 105 tok/s output on an m5 max is pretty bonkers. Breaking down the memory wall one brick at a time. 38.5K views · 345 likes · 20 reposts · 22 replies Open on X →
Interesting that Apple pays Google ~billion per year for Gemini when they can get a better model for free (GLM 5.2 and soon Kimi K3). 186.9K views · 2.1K likes · 33 reposts · 162 replies Open on X →
The video from @angeloskath on local agentic AI with MLX is excellent. I also hear it's one of the most viewed videos in WWDC history 👏 Goes through the basics of agentic AI and how to set it all up to run locally in a very approachable and simple way. The demos are excellent h
13.6K views · 196 likes · 17 reposts · 11 replies Open on X →
@awnihannun 😂 62.6K views · 1.6K likes · 50 reposts · 137 replies Open on X →
@awnihannun https://t.co/KsFw9kjguX
25.4K views · 648 likes · 45 reposts · 4 replies Open on X →
@awnihannun You’re right to call that out. The spec clearly called for “clean dishes”. You even said “make no mistakes”. Next time I’ll make sure to clean the dishes and make no mistakes. Ready to clean? 103.1K views · 2.8K likes · 34 reposts · 9 replies Open on X →
Adopting Claude speak in my regular life, episode 1: Partner: Did you do the dishes tonight? Me: Yes they're done. Partner: Why are they still dirty? Me: You're right to push back. I didn't actually do them. 1.9M views · 55K likes · 3.7K reposts · 388 replies Open on X →

Rispetto ad account della stessa dimensione

5 post degli ultimi 90 giorni, accanto alla fascia di 10K–100K follower. arriva a molti, ma pochi di loro reagiscono.

Visualizzazioni mediane38 547questo account924mediana per 10K–100K
Copertura, %85.71%questo account3.62%mediana per 10K–100K
Interazione, %1.01%questo account1.52%mediana per 10K–100K
MetricaQuesto accountMediana per 10K–100KRapporto
Visualizzazioni mediane per post38 54792441.7×
Copertura (visualizzazioni ÷ follower)85.71%3.62%23.7×
Tasso di interazione1.01%1.52%0.66×

Altri account di questa fascia →   Confronta con un altro account →   Come sono costruiti questi parametri →

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

1.9M24 Apr
103.1K
25.4K
62.6K
13.6K12 Jun
186.9K21 Jul
38.5K3 Sep
83.9K
10.3K16 Sep
8.2K17 Sep

Last 10 collected posts, oldest on the left. The scale is logarithmic: one post can outrun the rest a hundred times over.

Engagement rate per post

3.21%24 Apr
2.79%
2.75%
2.89%
1.66%12 Jun
1.21%21 Jul
1.01%3 Sep
0.84%
0.18%16 Sep
1.13%17 Sep

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

What the audience does

Likes87.5%63 497 in total
Reposts5.4%3 939 in total
Replies1.0%752 in total
Quotes0.4%267 in total
Bookmarks5.6%4 078 in total

Share of every reaction we collected for this account. Replies mean argument, reposts mean endorsement, bookmarks mean the post was worth keeping.

Followers by day

17 Sep

Daily snapshots since 17 Sep 2026; the dashed line is the starting count.

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