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Inherent

@inherent_labs

Living within the experiment

4 932Followers
12Following
11Posts total
422.4KViews on collected posts

Neueste Beiträge

@inherent_labs Congrats! 🙌 2.9K views · 32 likes · 0 reposts · 0 replies Open on X →
Paper: https://t.co/d1kg4X9Fua. Blogpost: https://t.co/DIlZYI8VZL. https://t.co/tIUtp2HhGH
5.6K views · 87 likes · 8 reposts · 1 replies Open on X →
6/ Many of the skills needed to replicate research are similar to those required for true innovation. We create 20 paper variants containing results not seen in the original. Faraday outperforms GPT-5.5 on these “imagined” tasks, innovating without realising it. https://t.co/zQ59
5.5K views · 59 likes · 4 reposts · 1 replies Open on X →
7/ Faraday is a first step in a new paradigm that combines a layer of scientific intuition with the advancing capabilities of coding agents. We believe that better AI Scientists, powered by novel infrastructure and new forms of human-machine teaming, can benefit all of society. 5.2K views · 52 likes · 3 reposts · 1 replies Open on X →
8/ We are designing Inherent so Faraday’s improvements compound through the entire company, enabling us to discover new knowledge while firmly keeping humans in the loop. To join us on our mission, apply here: https://t.co/0yjqM8xQhG. 5.8K views · 63 likes · 5 reposts · 1 replies Open on X →
5/ Faraday discovers new insights at test time, with no special-purpose harness and no test-time reward. In other words, Faraday learns to value new insights intrinsically. https://t.co/0cOdgKbtLR
GIF
6.1K views · 65 likes · 5 reposts · 1 replies Open on X →
4/ Faraday uses GPT-5.5 Codex as a tool, much like human scientists use coding agents. Faraday directs a model several orders of magnitude larger, improving replication on domains as diverse as meta-learning, structural biology and materials science. https://t.co/5AmxNLVVUV
8.4K views · 76 likes · 6 reposts · 1 replies Open on X →
3/ Replication is a non-verifiable task, requiring “research taste” to succeed, especially when a paper must be scaled down to fit new constraints. Faraday learns this kind of taste by training with turn-level credit provided by a self-consistent, human-validated judge. https://t
8.1K views · 81 likes · 3 reposts · 1 replies Open on X →
2/ To train Faraday, we develop Replica, a scalable task space for paper replication. Each task requires an agent to replicate a figure from a machine learning or AI for science research paper with a limited time and compute budget, and without access to the original plot. https:
11.7K views · 108 likes · 5 reposts · 2 replies Open on X →
1/ Today, we introduce Faraday, a 27B-parameter AI Scientist that extends the capabilities of coding agents with a layer of scientific intuition. Trained via long-horizon RL, Faraday outperforms Claude Opus 4.8 and GPT-5.5 on the task of replicating research papers. 🧵 https://t.c
363.1K views · 1.8K likes · 228 reposts · 76 replies Open on X →

Im Vergleich zu Konten gleicher Größe

10 Beiträge aus den letzten 90 Tagen, verglichen mit der Größenklasse under 10K Follower. liegt bei Reichweite und Interaktion unter vergleichbaren Konten.

Medianaufrufe5 950dieses Konto2 702Median für under 10K
Reichweite, %120.65%dieses Konto175.75%Median für under 10K
Interaktion, %1.09%dieses Konto1.47%Median für under 10K
KennzahlDieses KontoMedian für under 10KVerhältnis
Medianaufrufe pro Beitrag5 9502 7022.20×
Reichweite (Aufrufe ÷ Follower)120.65%175.75%0.69×
Interaktionsrate1.09%1.47%0.74×

Weitere Konten dieser Größe →   Mit einem anderen Konto vergleichen →   Wie diese Vergleichswerte entstehen →

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

363.1K14 Aug
11.7K
8.1K
8.4K
6.1K
5.8K
5.2K
5.5K
5.6K
2.9K

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

0.59%14 Aug
0.98%
1.05%
0.98%
1.17%
1.19%
1.07%
1.17%
1.71%
1.11%

Reactions — likes, reposts, replies and quotes — divided by views. Median for under 10K accounts is 1.47%.

What the audience does

Likes56.4%2 387 in total
Reposts6.3%267 in total
Replies2.0%85 in total
Quotes2.1%89 in total
Bookmarks33.2%1 403 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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