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Research

We train small, specialized models that outperform general-purpose LLMs on grid operations.

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Decoupling reasoning and facts in language models
Decoupling reasoning and facts in language models

On decoupling reasoning and facts in language models

Mahmoud
Mahmoud
10 min
The Limits of prompt optimization in high-alignment model pairs
The Limits of prompt optimization in high-alignment model pairs

The Limits of prompt optimization in high-alignment model pairs

Eya Gammoudi
Eya
5 min
Utilization rate forecasting for EV charging infrastructure
Machine learning
Utilization rate forecasting for EV charging infrastructure

Utilization rate forecasting for EV charging infrastructure

Abdulrahman Elbanna
Abdulrahman
8 min
Real-Time Human Activity Recognition Using the H2O AutoML Framework and Imbalance Handling
Machine learning
Real-Time Human Activity Recognition Using the H2O AutoML Framework and Imbalance Handling

Real-Time Human Activity Recognition Using the H2O AutoML Framework and Imbalance Handling

Eya Gammoudi
Eya
5 min
The few-shot distraction effect
AI
The few-shot distraction effect

The Few-shot distraction effect —> when more examples degrade LLM constraint adherence

4 min
Small vs Big - NanoChat vs GPT-OSS 20B
AI
Small vs Big - NanoChat vs GPT-OSS 20B

nanochat implements a dense transformer decoder with several architectural refinements that have become mainstream since the original GPT-2 paper.

MNN
, MNN
10 min
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