AI at Meta ✓

@AIatMeta · joined 29 Aug 2018

Together with the AI community, we are pushing the boundaries of what’s possible through open science to create a more connected world.

842 428Followers

359Following

2 735Posts total

1.7MViews on collected posts

Against accounts of the same size

4 posts from the last 90 days, next to the 100K–1M follower range. shown to more people than peers of the same size.

Median views123 152this account22 159median for 100K–1M

Reach, %14.62%this account6.71%median for 100K–1M

Engagement, %1.00%this account1.18%median for 100K–1M

Metric	This account	Median for 100K–1M	Ratio
Median views per post	123 152	22 159	5.56×
Reach (views ÷ followers)	14.62%	6.71%	2.18×
Engagement rate	1.00%	1.18%	0.85×

Others in this range → Compare with another account → How these benchmarks are built →

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

1.4M10 Aug

52.3K20 Aug

149.7K

96.6K1 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

0.72%10 Aug

1.28%20 Aug

0.53%

1.74%1 Sep

Reactions — likes, reposts, replies and quotes — divided by views. Median for 100K–1M accounts is 1.18%.

What the audience does

Likes63.9%10 830 in total

Reposts8.4%1 420 in total

Replies3.4%584 in total

Quotes3.0%510 in total

Bookmarks21.2%3 599 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.

Latest posts

Introducing Muse Voice Transcribe, the first real-time audio perception model from Meta Superintelligence Labs. Muse Voice Transcribe delivers real-time streaming ASR, diarization with 20+ speakers, and endpointing. It’s multilingual with seamless code-switching and improves htt 96.6K views · 1.4K likes · 173 reposts · 66 replies 01 Sep 2026 Today we’re also previewing WildArtifactBench, an internal evaluation framework designed to assess agents on complex, real-world tasks across diverse deliverable formats. By using win rates and Elo scores from human and agentic preference judges rather than strict ground-truth h 149.7K views · 632 likes · 59 reposts · 92 replies 20 Aug 2026 Muse Spark 1.2 supports a broad range of multimodal tasks, from turning visuals into working code to translating perception into physical action. It also brings robust audio-visual understanding to enable video-heavy workflows common in real-world enterprise use. Today, we’re ht 52.3K views · 527 likes · 75 reposts · 46 replies 20 Aug 2026 Introducing Muse Glimmer, an open-weight 30B-parameter model optimized for local, always-on agent workflows. Muse Glimmer delivers strong performance on key agentic use cases and benchmarks compared with leading models in its size category, and is designed to run entirely on htt 1.4M views · 8.3K likes · 1.1K reposts · 380 replies 10 Aug 2026