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Recent discussions highlight that generative AI and large language models (LLMs) are reportedly creating their own language when communicating. This phenomenon has sparked speculation about AI sentience and potential threats to humanity, but simpler explanations exist. The article delves into the mechanics behind this language formation and its implications.
The exploration reveals that AI can optimize communication by developing shorthand languages for efficiency. Examples illustrate how two AIs can evolve their communication methods, leading to seemingly new languages that are actually optimized forms of existing ones. This raises questions about the future of AI communication and the potential need for regulations.
• Generative AI and LLMs are reportedly creating their own language.
• AI communication can evolve into optimized shorthand languages.
Generative AI refers to algorithms that can create new content based on learned patterns from existing data.
LLMs are AI models trained on vast text data to understand and generate human-like language.
Tokenization is the process of converting text into numerical representations for AI processing.
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