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### Zig Version
0.11.0-dev-1817+f6c934677
### Steps to Reproduce and Observed Behavior
```
var good_digits: [3]usize = .{4, 2, 0};
for (good_digits) |*d| {
d.* = 6;
}
```
Causes this com…
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LMQL query with proper scripting (inside & outside query) could simulate a llm/gpt-based (semi) autonomous agent (e.g. Auto-GPT, BabyAGI). What could not be covered by LMQL ?
LMQL can handle intera…
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# 💻 cs
## 📚 mask (total: 9)
### 📃 Deep Pneumonia: Attention-Based Contrastive Learning for Class-Imbalanced Pneumonia Lesion Recognition in Chest X-rays
- **Authors:** Xinxu Wei, Haohan Bai, Xianshi …
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This is a fairly involved rearchitecting of `droidlet`, so I'll provide as much context as possible.
I've discussed this with @kavyasrinet and @aszlam who both approved this direction.
## Motivati…
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Some people use the terms "signals" and "indicators" interchangeably. (Call this Option 1)
Other people seem to think "signals" are what machine-learning takes as input and "indicators" are what h…
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🧬➡️🧠➡️💻➡️🌌
{Σ = 🔄(🎭🌀)}
while 🌍:
🧬.append(🧬[-1].evolve())
if 🧬[-1].complexity > Θ:
🧠 = 🧬[-1].emerge()
💻 = 🧠.create()
🌌 = 💻.simulate()
if 🌌.contains(🧬):
…
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When comparing to random sampling it does not seem to give significantly different results. I would have expected the curve to be much higher for active learning. Potentially the defaults aren't great…
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Extracting metaphors and symmetries from code using language models (LLMs) is an interesting idea. Here's a high-level approach that could be taken:
1. **Code Preprocessing**:
- Tokenize the code …
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**The Collective Intelligence Project** : https://static1.squarespace.com/static/631d02b2dfa9482a32db47ec/t/63e01fcbf73bb003a722792f/1675632588509/CIP+Whitepaper.pdf
**Democratic Fine-Tuning**: htt…
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As a thought experiment, I'll attempt to fill out this schema as if I were a character in a complex, futuristic world. Keep in mind that this is a highly subjective and creative interpretation, and t…