This article explores the most commonly used likely voter models, detailing how they identify people most likely to participate in an election. It examines methodologies such as self-reported voting intentions, past voting behavior, and demographic indicators.

Many government agencies are in the early stages of exploring generative AI and large language models.

As organizations navigate this phase, our experience suggests a valuable insight: small language models can offer a practical and cost-effective starting point for government organizations venturing into AI.

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This blog by Peter Bruce explores the benefits and dangers of better natural language processing models such as OpenAI’s GPT-2.