Patrick Mineault ✓
@patrickmineault · New York City · joined 06 Apr 2011
NeuroAI researcher @ Amaranth Foundation, safety, open science. Previously engineer @ Google, Meta, Mila.
23 515Followers
2 576Following
5 570Posts total
158.1KViews on collected posts
Postingan terbaru
Mencari postingan baru…
Are virtual flies playing Beat Saber? SM64? Doom? No.
The new fly connectome is an incredible achievement! Less is going on in the sim videos than it seems. I'm stoked to see people engage with neuroscience though. My breakdown: https://t.co/W7NCosFMCT
8.2K views · 121 likes
· 25 reposts · 5 replies
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CC @MWCvitkovic @JacquesCarolan @zenbrainest @michaelzlin @BrainCaRMA
1.1K views · 5 likes
· 0 reposts · 0 replies
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I was floored when I heard that there are chemogenetics trials in humans. We're engineering neurons to have synthetic receptors that can be activated using normally inert drugs! How big of a deal is this? Can we cure epilepsy? PD? I did a deep dive into human chemogenetics
11.2K views · 68 likes
· 8 reposts · 1 replies
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❤️❤️❤️Big milestone today: 3,000 of you have agreed to occasionally bless their inboxes with extremely niche deep dives into NeuroAI. Thank you so much for the support ❤️❤️❤️ https://t.co/NvJ3VVYwM8
6.6K views · 55 likes
· 3 reposts · 8 replies
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How does the brain know how to wire itself up? Tony Zador and Stan Kerstjens use an algorithmic frame (o notation in space and time), and it’s quite compelling https://t.co/Ndar5dWDqD
3K views · 54 likes
· 4 reposts · 1 replies
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@patrickmineault Research Summary: “NeuroAI for AI Safety” https://t.co/FXaFcbTMMc
2.1K views · 7 likes
· 0 reposts · 0 replies
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Last but not least, a huge thanks to @jamesfickel and to our collaborators @JoanneZPeng, @nc_znc, Eli Bingham @BasisOrg, Julian Jara-Ettinger, @e_mackevicius, @adammarblestone, @marcelomattar, @Andrew_C_Payne, @naturecomputes, @schroeder_ke, @ZennaTavares, @atoliaslab. Without
1.3K views · 23 likes
· 0 reposts · 0 replies
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Beyond AI safety, we’ve synthesized a lot of literature (90 pages and 700+ references). Intermediate milestones on this path to safe AI will shorten the time to translate new neurotechnologies and quicken the scientific feedback loop with virtual neuroscience experiments. 8/N
1.5K views · 14 likes
· 1 reposts · 1 replies
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Traditional neuroscience moves far too slowly to impact AI development on relevant timescales. To meaningfully contribute to AI safety, we need to dramatically accelerate our ability to record, analyze, simulate, and understand neural systems. 6/N
913 views · 15 likes
· 1 reposts · 1 replies
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Nothing about safer AI is inevitable. We think now is the time to pursue this differential path, because scalable neuroscience tools and technology make collecting high-res datasets possible, accelerated by ML progress and decreased compute costs 7/N
1.1K views · 19 likes
· 1 reposts · 1 replies
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The proposals we evaluate span the whole gamut of NeuroAI: biophysically detailed models, embodied and sensory digital twins, cognitive architectures, fine-tuning conventional AI models with brain data, reverse-engineering the loss functions of the brain and mech interp. 5/N http
1K views · 18 likes
· 0 reposts · 1 replies
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We adopt @deepmind’s framework and evaluate 7 concrete proposals to enhance safety without dramatically increasing capabilities. For each approach, we identify specific opportunities for how neuroscientists can contribute to building safer AI systems. 4/N https://t.co/COGyWOkNr6
1.4K views · 17 likes
· 0 reposts · 1 replies
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Building safe AI is more pressing as AI becomes more powerful. The human brain remains our only example of safe general intelligence. Despite our flaws, we have robust senses, cooperate with others, & recover from mistakes. Understanding the brain is a promising route toward AI
1.7K views · 18 likes
· 0 reposts · 3 replies
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ArXiV PDF: https://t.co/wpSDPRagTt
Read online: https://t.co/VMBZZ2K8Wz
2/N
2.5K views · 31 likes
· 4 reposts · 1 replies
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Excited to release what we’ve been working on at Amaranth Foundation, our latest whitepaper, NeuroAI for AI safety! A detailed, ambitious roadmap for how neuroscience research can help build safer AI systems while accelerating both virtual neuroscience and neurotech. 1/N https://
110.5K views · 378 likes
· 99 reposts · 18 replies
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Dibandingkan akun berukuran sama
6 postingan dari 90 hari terakhir, dibandingkan dengan rentang 10K–100K pengikut. tampil luas, tetapi sedikit penonton yang merespons.
Median tayangan5 184akun ini924median untuk 10K–100K
Jangkauan, %22.05%akun ini3.62%median untuk 10K–100K
Interaksi, %0.92%akun ini1.52%median untuk 10K–100K
| Metrik | Akun ini | Median untuk 10K–100K | Rasio |
|---|---|---|---|
| Median tayangan per postingan | 5 184 | 924 | 5.61× |
| Jangkauan (tayangan ÷ pengikut) | 22.05% | 3.62% | 6.09× |
| Tingkat interaksi | 0.92% | 1.52% | 0.61× |
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
1.7K2 Dec
1.4K
1K
1.1K
913
1.5K
1.3K
2.1K
3K22 Aug
6.6K26 Aug
11.2K2 Sep
3.7K
1.1K
8.2K14 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
1.20%2 Dec
1.28%
1.83%
1.89%
1.86%
1.04%
1.74%
0.33%
1.95%22 Aug
1.01%26 Aug
0.72%2 Sep
0.83%
0.45%
1.88%14 Sep
Reactions — likes, reposts, replies and quotes — divided by views. Median for 10K–100K accounts is 1.52%.
What the audience does
Likes56.4%866 in total
Reposts9.8%151 in total
Replies2.8%43 in total
Quotes2.2%34 in total
Bookmarks28.8%442 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.
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