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Followers

79.4K

Posts

222

Following

2.1K

Account age

5 yrs

🎁 Free analysisfor John Schulman

🕵️Fake Followers CheckReal-audience % & bot risk→ 📊Engagement rateBenchmarked vs. peers→ 💰What they chargeFair sponsored-post price→

📊 Post performance

126.8K

Avg views / post

1.6×

Reach vs followers

May 2021

On X since

🔥 Top post: I shared the following note with my OpenAI colleagues today: I' · 1.4M views

📊 Activity & format

Posting cadence

0.09 / week

A lower-frequency account — each post lands with more weight.

Content mix

Mostly text

Recent: 0 video · 0 image · 18 text.

Follower / following

38×

Follows 2.1K back. A strong ratio — an audience that follows them, not a follow-for-follow network.

Verification

✓ X Premium

A paid X Premium (Blue) verified account.

Recent posts

View on X ↗

🔥 Top post I shared the following note with my OpenAI colleagues today: I've made the difficult decision to leave OpenAI. This choice stems from my desire to deepen my focus on AI alignment, and to start a new chapter of my career where I can return to hands-on technical work. I've decided 1.4M❤ 5.2K🔁 564

Happy to share a new paper! Designing model behavior is hard -- desirable values often pull in opposite directions. Jifan's approach systematically generates scenarios where values conflict, helping us see where specs are missing coverage … 113.9K❤ 618🔁 58 We're happy to support the Human Centered LLMs course, on topics close to our hearts. We'd like to support more classes with free credits for students to use on assignments and projects. If you're an instructor interested in using Tinker … 176.8K❤ 633🔁 73 Fine-tuning APIs are becoming more powerful and widespread, but they're harder to safeguard against misuse than fixed-weight sampling APIs. Excited to share a new paper: Detecting Adversarial Fine-tuning with Auditing Agents (https://t.co/… 90.5K❤ 461🔁 61 Really happy to see people reproducing the result that LoRA rank=1 closely matches full fine-tuning on many RL fine-tuning problems. Here are a couple nice ones: https://t.co/x7hcgNL3Bd 127.1K❤ 943🔁 100 Tinker provides an abstraction layer that is the right one for post-training R&D -- it's the infrastructure I've always wanted. I'm excited to see what people build with it. "Civilization advances by extending the number of important o… 187.6K❤ 1.2K🔁 145 Big fan of Jeremy’s work on optimization—great to see his first Thinking Machines post! 64.3K❤ 509🔁 39 I'm more annoyed at whoever named us homo sapiens sapiens 79.4K❤ 458🔁 40 For people who don't like Claude's behavior here (and I think it's totally valid to disagree with it), I encourage you to describe your own recommended policy for agentic models should do when users ask them to help commit heinous crimes. … 213.3K❤ 703🔁 161 Excited to build a new AI research lab with some of my favorite former colleagues and some great new ones. Looking forward to sharing more in the coming weeks. 113.4K❤ 1.2K🔁 88 @barret_zoph and I recently gave a talk at Stanford on post-training and our experience working together on ChatGPT. Unfortunately the talk wasn't recorded, but here are the slides: https://t.co/7fcGmvFtUF. (If you have a recording, please… 83.9K❤ 637🔁 88 Confirming that I left Anthropic last week. Leaving wasn't easy because I enjoyed the stimulating research environment and the kind and talented people I was working with, but I decided to go with another opportunity that I found extremely… 446K❤ 2.8K🔁 162 There are some intriguing similarities between the r1 chains of thought and the o1-preview CoTs shared in papers and blog posts (eg https://t.co/rF8XaSsi2j). In particular, note the heavy use of the words "wait" and "alternatively" as a tr… 158.6K❤ 718🔁 71

💡 Facts

🗓️Joined X in 2021 — 5 years ago.

👁️Averages 126.8K views per post.

📤Posts about 0.1× per week.

💬1.55% engagement rate.

🏅Earned the 10K Followers for passing 10K followers.

🕵️ Fake follower check

Estimated

69/100

Good Credibility score

85%

Real Real audience

Low Fake-follower risk

High Data confidence

Est. 85% real, active audience · Low fake-follower risk.
Engagement (~1.6× of followers engage each post) is around typical for X.
Organic base — far more followers than accounts it follows.
Verified account.
Established account (5+ years old).
1.55% engagement — below the ~18% typical for this size.

Heuristic estimate from engagement, follower ratios, account age & growth — a screening signal, not a guarantee.

About

@thinkymachines. Interested in reinforcement learning, alignment, birds, jazz music

🔀 Audience overlap

Estimated

Estimated shared audience with similar creators — useful for avoiding overlap (or doubling down) when planning a campaign.

Institute of Development Studies 17%

Jim Dunaway 17%

Khaligraph Jones 15%

Bahrain Int. Circuit 13%

America’s Morning Headquarters 11%

FunkBros 10%

More like this

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