Technical

IT industry technical articles covering AWS, Azure, Java, Python, SQL, DevOps, and more.

Sparrow Paper: Training Trustworthy Dialogue Agents with Rule-Conditional Reward Models

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The CI/CD pipeline is red again. You switch back to the logs and find the model confidently inventing an API endpoint that does not exist. DeepMind’s Sparrow paper proposes an RCRM architecture that uses rule-conditional reward models and evidence chains to let the model automatically verify sources while generating. This is not about making the model smarter. It is about teaching it how to prove that its answer is correct.

Kaplan 2020: Scaling Laws and Their Limits

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In 2020, OpenAI proposed a power-law relationship between model size and data volume, which led many teams toward a simple idea: bigger models, less data. Two years later, Chinchilla revised that picture with a compute-optimal view, showing that data volume mattered far more than many people had assumed. This matters if you’re deciding whether the next gain should come from more GPUs, a larger parameter count, or a larger corpus. The history of scaling laws is not just academic. It changes how you think about training efficiency, model selection, and where your cost structure really sits.