Ruben Hassid (@rubenhassid) / X

Ruben Hassid

18.9K posts

Ruben Hassid

@rubenhassid

some people read my substack.com/@ruben

Joined March 2013

Pinned
Ruben Hassid
@rubenhassid
3h
Instead of another YouTube rabbit hole tonight. Take these 11 courses to master Claude (for free): → Level 1 - 20 mins: The basics. Claude certificates: claude101.com Claude For Dummies: ruben.substack.com/p/claude-for-d… AI is (stupidly) simple: ruben.substack.com/p/s Claude
Ruben Hassid
@rubenhassid
Jun 3
Article
7 guides to become (ridiculously) good at Claude:
I have been begging you to switch to Claude since December 20, 2025. And I wrote over 21 guides on how to best use it. But these two newsletters are completely outdated. And most of my other 21...
5.4K
Ruben Hassid
@rubenhassid
Jun 7, 2025
BREAKING: Apple just proved AI "reasoning" models like Claude, DeepSeek-R1, and o3-mini don't actually reason at all. They just memorize patterns really well. Here's what Apple discovered: (hint: we're not as close to AGI as the hype suggests)
14M
Ruben Hassid
@rubenhassid
Jun 17, 2025
BREAKING: Stanford just surveyed 1,500 workers and AI experts about which jobs AI will actually replace and automate. Turns out, we've been building AI for all the WRONG jobs. Here's what they discovered: (hint: the "AI takeover" is happening backwards)
2.6M
Ruben Hassid
@rubenhassid
Dec 17, 2024
I tested Sora vs. the new Google Veo-2. I feel like comparing a bike vs. a starship:
00:00
1.9M
Ruben Hassid
@rubenhassid
Oct 30, 2025
Andrej Karpathy says you should learn AI depthwise, not breadthwise. Most education is breadthwise: watch lectures, memorize formulas, and trust you'll need it later. Karpathy flips this by learning "depthwise, on demand." What this means: Pick a project, start building, and
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Ruben Hassid
@rubenhassid
Jun 7, 2025
Replying to @rubenhassid
All "reasoning" models hit a complexity wall where they completely collapse to 0% accuracy. No matter how much computing power you give them, they can't solve harder problems.
432K
Ruben Hassid
@rubenhassid
Jun 7, 2025
Replying to @rubenhassid
Apple discovered that these models are not reasoning at all, but instead doing sophisticated pattern matching that works great until patterns become too complex. Then they fall apart like a house of cards.
451K
Ruben Hassid
@rubenhassid
Jun 7, 2025
Replying to @rubenhassid
As problems got harder, these "thinking" models actually started thinking less. They used fewer tokens and gave up faster, despite having unlimited budget.
315K
Ruben Hassid
@rubenhassid
Jun 14, 2025
The world's leading AI research center completed the most comprehensive study ever on kids and AI. They surveyed 1,800+ children, parents, and teachers in UK. Here's what they found: (spoiler: children are outsmarting adults on AI)
645K
Ruben Hassid
@rubenhassid
Jun 7, 2025
Replying to @rubenhassid
Apple researchers even tried giving the models the exact solution algorithm. Like handing someone step-by-step instructions to bake a cake. The models still failed at the same complexity points. They can't even follow directions consistently.
312K
Ruben Hassid
@rubenhassid
Jun 7, 2025
Replying to @rubenhassid
Instead of using the same old math tests that AI companies love to brag about, Apple created fresh puzzle games. They tested Claude Thinking, DeepSeek-R1, and o3-mini on problems these models had never seen before. The result ↓
379K
Ruben Hassid
@rubenhassid
Jun 7, 2025
Replying to @rubenhassid
While AI companies celebrate their models "thinking," Apple basically said "Everyone's celebrating fake reasoning." The industry is chasing metrics that don't measure actual intelligence.
220K
Ruben Hassid
@rubenhassid
Jun 7, 2025
Replying to @rubenhassid
The research revealed three regimes: • Low complexity: Regular models actually win • Medium complexity: "Thinking" models show some advantage • High complexity: Everything breaks down completely Most problems fall into that third category.
309K
Ruben Hassid
@rubenhassid
Jun 7, 2025
Replying to @rubenhassid
If these models were truly "reasoning," they should get better with more compute and clearer instructions. Instead, they hit hard walls and start giving up. Is that intelligence or memorization hitting its limits?
263K