Grant Sanderson Add us as a preferred source on Google
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👋 Unclaimed listing — auto-generated from public data; rates are estimates, not set by the creator. 🔒 Paid proposals held safely in escrow — released only when the work's approved.
This is an unclaimed, auto-generated listing. It was built only from Grant Sanderson’s publicly available X information. Grant Sanderson has not claimed, verified, or endorsed it, and is not affiliated with, sponsored by, or a partner of SocialDB — no partnership or endorsement is implied, and any prices shown are estimates, not set by the creator.
Followers
450.2K
Posts
3.7K
Following
373
Account age
12 yrs
💰 Suggested sponsorship rate
$2.5K – $4.1K / sponsored post
Estimated from audience size & typical reach — every deal is negotiable and held in SocialDB escrow.
🎁 Free analysisfor Grant Sanderson
Known for
1.3M views
For the most recent video, I had way too much fun simulating the electric field (or rather, the component of that field responsible for radiation) and how it responds to an accelerating electric charge.
810.4K views
The next chapter about transformers is up on YouTube, digging into the attention mechanism: https://t.co/TWNXiWM2az
The model works with vectors representing tokens (think words), and this is the mechanism that allows those vectors to take in meaning from context.
622.2K views
Excerpt from a video I just posted on YouTube (about the multilayer perception layers in a transformer, and how LLMs may store facts).
538.1K views
Here's a short dynamics-based explanation of the equation e^(πi)=-1
📊 Post performance
Recent posts · views
Jul 11latest
851.7K
Avg views / post
810.4K–1.3M
Typical post (views)
1.9×
Reach vs followers
80/100
Very consistent reach
Oct 2014
On X since
Half of recent posts land between 810.4K and 1.3M views (median 851.7K) — a dependable floor a sponsored post can count on.
🔥 Top post: I learned yesterday the video I made in 2017 explaining how Bitc · 1.9M views
📊 Activity & format
Posting cadence
0.06 / week
A lower-frequency account — each post lands with more weight.
Content mix
Mostly video
Recent: 7 video · 5 image · 6 text.
Follower / following
1.2K×
Follows 373 back. A strong ratio — an audience that follows them, not a follow-for-follow network.
Recent posts
View on X ↗
Ever since I made a video about Fourier Transforms, one of the most requested topics on the channel has been its close cousin, the Laplace Transform.
I've been having a lot of fun animating a mini-series about this topic, and the main par…
▶
Excerpt from a video I just posted on YouTube (about the multilayer perception layers in a transformer, and how LLMs may store facts).
▶
The next chapter about transformers is up on YouTube, digging into the attention mechanism: https://t.co/TWNXiWM2az
The model works with vectors representing tokens (think words), and this is the mechanism that allows those vectors to tak…
Product idea: An app/website that's identical to YouTube in every way, except without any shorts.
▶
For the most recent video, I had way too much fun simulating the electric field (or rather, the component of that field responsible for radiation) and how it responds to an accelerating electric charge.
▶
Here's a short dynamics-based explanation of the equation e^(πi)=-1
It's okay, GPT, you don't have to pretend anymore.
So close and yet so far
Happy e day!
π
▶
What is a convolution? What is a "Gaussian Kernel"?
(This was the main animation used at the intro of last week's convolutions lecture).
▶
Excerpt from a video I just posted on YouTube (about the multilayer perception layers in a transformer, and how LLMs may store facts).
▶
The next chapter about transformers is up on YouTube, digging into the attention mechanism: https://t.co/TWNXiWM2az
The model works with vectors representing tokens (think words), and this is the mechanism that allows those vectors to tak…
Product idea: An app/website that's identical to YouTube in every way, except without any shorts.
▶
For the most recent video, I had way too much fun simulating the electric field (or rather, the component of that field responsible for radiation) and how it responds to an accelerating electric charge.
▶
Here's a short dynamics-based explanation of the equation e^(πi)=-1
It's okay, GPT, you don't have to pretend anymore.
So close and yet so far
Happy e day!
π
▶
What is a convolution? What is a "Gaussian Kernel"?
(This was the main animation used at the intro of last week's convolutions lecture).
💡 Facts
🗓️Joined X in 2014 — 12 years ago.
👁️Averages 851.7K views per post.
📤Posts about 0.1× per week.
💬2.67% engagement rate.
🏅Earned the 100K Followers for passing 100K followers.
🕵️ Fake follower check
Estimated92/100
Excellent
Credibility score
99%
Real
Real audience
Low
Fake-follower risk
High
Data confidence
- Est. 99% real, active audience · Low fake-follower risk.
- Engagement (~1.9× of followers engage each post) is around typical for X.
- Organic base — far more followers than accounts it follows.
- Established account (12+ years old).
- 2.67% engagement — above the ~2.2% typical for a X account this size.
Heuristic estimate from engagement, follower ratios, account age & growth — a screening signal, not a guarantee.
About
Pi creature caretaker.
Contact/faq: http://3blue1brown.com/faq
📸 Gallery
🔀 Audience overlap
EstimatedEstimated shared audience with similar creators — useful for avoiding overlap (or doubling down) when planning a campaign.
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Grant Sanderson has 450,213 followers on X.
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