Why Hardware-Software Co-Design Is AI's Real 100x: Dylan Patel of SemiAnalysis
Published June 30, 2026
At a glance
Views
107,082
Likes
1,738
Comments
123
Performance vs. channel
All-time outlier score
Engagement rate
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About
Dylan Patel, founder of SemiAnalysis, argues the biggest gains in AI don't come from faster chips, they come from software-hardware co-design. Optimizing the model, the kernels, and the silicon together turns a 2x here and a 2x there into 100x. He explains why DeepSeek's experts were shaped for Nvidia's Hopper (and why…
- Published
- June 30, 2026
- Made for kids
- No
More features coming
We're working on new analytics and tools. Stay tuned.
How Why Hardware-Software Co-Design Is AI's Real 100x: Dylan Patel of SemiAnalysis is doing
It has 107K views in total. It ranks #11,705,399 among tracked YouTube videos by views.
Key facts about Why Hardware-Software Co-Design Is AI's Real 100x: Dylan Patel of SemiAnalysis
- Total views
- 107K
- Total likes
- 1.73K
- Total comments
- 123
- Published
- June 30, 2026
- Global rank by views
- #11,705,399
Frequently asked questions
How many views does Why Hardware-Software Co-Design Is AI's Real 100x: Dylan Patel of SemiAnalysis have?
Why Hardware-Software Co-Design Is AI's Real 100x: Dylan Patel of SemiAnalysis has 107,082 views, 1,738 likes and 123 comments, ranking #11,705,399 among tracked YouTube videos by views.
How accurate are these YouTube video analytics?
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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