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The landscape of AI language models has evolved significantly in 2024, showcasing advancements in both large and smaller models. Smaller language models are gaining traction due to their efficiency and ability to perform specialized tasks, while larger models continue to push the boundaries of generative AI. The interplay between these models is crucial for developing hybrid systems that can operate on more accessible hardware.
The increased accessibility of language models has raised concerns about their potential misuse, especially during election periods. Instances of AI-generated disinformation highlight the need for regulatory frameworks to govern AI use in sensitive contexts. As AI agents emerge, organizations are beginning to adopt new frameworks that enhance the capabilities and autonomy of these systems.
• Smaller language models are becoming more efficient and specialized for tasks.
• AI misuse during elections raises concerns about disinformation and regulation.
LLMs are trained on vast text data to generate human-like language, crucial for AI applications.
AI hallucination refers to the generation of false or misleading information by AI models.
AI agents are advanced chatbots with tools and autonomy to perform tasks independently.
OpenAI develops advanced AI models and has intervened against misuse of its technology during elections.
Microsoft is involved in creating smaller language models like Phi-3 and Phi-4, enhancing AI capabilities.
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