How to Hack an AI Model with Weight Space Programming
Published November 3, 2026
At a glance
Views
6,978
Likes
74
Comments
7
Performance vs. channel
All-time outlier score
Engagement rate
More features coming
We're working on new analytics and tools. Stay tuned.
About
A team at MIT had GPT-6 Astra edit the weights of Qwen3.5-0.8B directly, with no training and no gradients. It changed 0.016% of the weights, and the authors report MATH-500 going from 7.9% to 48.1%. In this video I break down what weight editing actually is, why most of that jump comes from stopping the model's thinki…
- Published
- November 3, 2026
- Made for kids
- No
More features coming
We're working on new analytics and tools. Stay tuned.
How How to Hack an AI Model with Weight Space Programming is doing
It has 6.97K views in total. It ranks #15,512,559 among tracked YouTube videos by views.
Key facts about How to Hack an AI Model with Weight Space Programming
- Total views
- 6.97K
- Total likes
- 74
- Total comments
- 7
- Published
- November 3, 2026
- Global rank by views
- #15,512,559
Frequently asked questions
How many views does How to Hack an AI Model with Weight Space Programming have?
How to Hack an AI Model with Weight Space Programming has 6,978 views, 74 likes and 7 comments, ranking #15,512,559 among tracked YouTube videos by views.
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View, like, and comment counts come from YouTube's public API and refresh regularly. Growth and revenue figures are estimates built from tracked historical data, so they can differ slightly from what the creator sees privately in YouTube Studio.
What is the outlier score?
How this video's views compare to the channel's usual Shorts or long-form video. A 2x score means double the usual views for that channel, 0.5x means half.
What is engagement rate and how is it calculated?
Likes and comments per view, compared to this channel's typical engagement rate — shown as above or below what's usual for the channel.
How is the revenue estimate calculated?
It's a rough public estimate based on a $0.7–$2.0 CPM (revenue per 1,000 views) applied to view count — not actual creator earnings, which depend on ad rates, audience geography, and monetization settings YouTube doesn't expose publicly.
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