Mira Murati ✓
@miramurati · San Francisco, CA · joined 18 Aug 2010
Now building @thinkymachines. Previously CTO @OpenAI
1 012 693Followers
645Following
405Posts total
75.8MViews on collected posts
Derniers posts
Recherche de nouveaux posts…
We’re building machine intelligence to expand human will & judgement. Glad to have you on the team to help us figure out how to make this future safe.
175.9K views · 2K likes
· 79 reposts · 85 replies
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I’ve joined @thinkymachines to work on safety & alignment.
The default trajectory is that as AI gets more powerful, control over it will concentrate in the hands of a few. I’d rather build safety systems that let control over AI be shared widely.
Longer thoughts below.
269.7K views · 962 likes
· 31 reposts · 42 replies
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An important conversation about where AI is going and the work that is cut out for us.
143.7K views · 1.5K likes
· 96 reposts · 49 replies
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Our own @johnschulman2 talks with Dwarkesh about where human judgment still matters as models improve and self-improve: teaching them to handle messy real-world tasks, applying taste to what works in the long run, and, above all, specifying what we actually want.
225.2K views · 599 likes
· 56 reposts · 25 replies
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We share our approach to open-weights releases, how we assessed Inkling, why safety depends on both the model and the ecosystem it enters, and how testing, staged access, and stronger defenses can create a path toward greater openness.
217.6K views · 1.6K likes
· 121 reposts · 76 replies
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Releasing weights indiscriminately isn't safe. Neither is keeping capable models inside a few labs.
We think there's a path between them. We haven't mapped all of it. Our new post covers the part we can see: how we assessed Inkling, and why access should widen in stages.
560K views · 1.3K likes
· 149 reposts · 68 replies
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Inkling-Small is comparable to Inkling at a quarter the size. Weights are open, fine-tunable on Tinker today. Look forward to seeing what people make with it.
472.6K views · 3.7K likes
· 283 reposts · 148 replies
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Today, we are releasing Inkling-Small.
Inkling-Small achieves comparable performance to Inkling at a quarter of its size. It features 276B total parameters, 12B active. We are making the full weights available.
https://t.co/NzFVYVkuQI
Fine-tune it on Tinker today, or chat with
1.6M views · 3.3K likes
· 452 reposts · 165 replies
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The knowledge that makes AI useful is diffused. It lives with scientists, engineers, clinicians, firms. For AI to benefit from distributed knowledge, it must itself be distributed. Agree with Jensen that this is a future worth building.
1.1M views · 8.9K likes
· 1K reposts · 334 replies
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For my first post, I’m sharing a letter @NVIDIA signed on why open models matter.
AI will transform every industry, power every company, and be built by every country.
Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty.
66.4M views · 172.7K likes
· 29.6K reposts · 16.1K replies
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Our first model, Inkling. Trained from scratch, weights are open, fine-tunable on Tinker today.
1.6M views · 13.6K likes
· 1.1K reposts · 399 replies
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A year ago we set out to empower humanity with a focus on multimodal AI, custom models, and open science.
We previewed interaction models that collaborate the way people do. Tinker lets anyone train their own open weights models. We published our research on Connectionism.
409K views · 1.8K likes
· 112 reposts · 59 replies
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@miramurati sir mira posted an update https://t.co/YE5oeeIMYV
18.1K views · 138 likes
· 3 reposts · 5 replies
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@miramurati Please honor the nickname everyone uses, Thinky
54.3K views · 431 likes
· 0 reposts · 7 replies
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Thinking Machines Lab exists to empower humanity through advancing collaborative general intelligence.
We're building multimodal AI that works with how you naturally interact with the world - through conversation, through sight, through the messy way we collaborate. We're
2.7M views · 7.7K likes
· 673 reposts · 632 replies
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Face aux comptes de taille comparable
8 posts des 90 derniers jours, à côté de la tranche de 1M–10M abonnés. diffusé à plus de monde que les comptes de taille comparable.
Vues médianes247 428ce compte14 648médiane pour 1M–10M
Portée, %24.43%ce compte0.74%médiane pour 1M–10M
Engagement, %0.62%ce compte0.70%médiane pour 1M–10M
| Indicateur | Ce compte | Médiane pour 1M–10M | Rapport |
|---|---|---|---|
| Vues médianes par post | 247 428 | 14 648 | 16.9× |
| Portée (vues ÷ abonnés) | 24.43% | 0.74% | 33.0× |
| Taux d'engagement | 0.62% | 0.70% | 0.88× |
Autres comptes de cette tranche → Comparer avec un autre compte → Comment ces repères sont établis →
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
18.1K15 Jul
12.4K
409K10 Jul
1.6M15 Jul
66.4M24 Jul
1.1M
1.6M30 Jul
472.6K
560K31 Jul
217.6K
225.2K11 Sep
143.7K
269.7K14 Sep
175.9K
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
0.81%15 Jul
1.04%
0.49%10 Jul
0.96%15 Jul
0.35%24 Jul
0.98%
0.26%30 Jul
0.89%
0.29%31 Jul
0.85%
0.30%11 Sep
1.13%
0.39%14 Sep
1.25%
Reactions — likes, reposts, replies and quotes — divided by views. Median for 1M–10M accounts is 0.70%.
What the audience does
Likes66.1%220 540 in total
Reposts10.1%33 789 in total
Replies5.5%18 238 in total
Quotes3.5%11 794 in total
Bookmarks14.7%49 165 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
24 Sep
Daily snapshots since 24 Sep 2026; the dashed line is the starting count.
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