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AI Learns from AI: The Emergence of Social Learning Among Large Language Models

Unite.AI

Since OpenAI unveiled ChatGPT in late 2022, the role of foundational large language models (LLMs) has become increasingly prominent in artificial intelligence (AI), particularly in natural language processing (NLP). This suggests a future where AI can adapt to new challenges more autonomously.

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Bigger isn’t always better: How hybrid AI pattern enables smaller language models

IBM Journey to AI blog

As large language models (LLMs) have entered the common vernacular, people have discovered how to use apps that access them. Modern AI tools can generate, create, summarize, translate, classify and even converse. However, there are smaller models that have the potential to innovate gen AI capabilities on mobile devices.

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Graph Viz with Gephi and ChatGPT, Google’s Bard AI, and Reverse Engineering Image Prompts

ODSC - Open Data Science

5 Practical Business Use Cases for Large Language Models LLMs are everywhere now. Let’s take a look at a few practical use cases for large language models and how they can shape your AI endeavors too. Check out some more highlights in the full schedule here!

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Role of LLMs like ChatGPT in Scientific Research: The Integration of Scalable AI and High-Performance Computing to Address Complex Challenges and Accelerate Discovery Across Diverse Fields

Marktechpost

This exploration of scalable AI for science underscores the necessity of integrating large-scale computational resources with vast datasets to address complex scientific challenges. Spatial decomposition can be applied in many scientific contexts where data samples are too large to fit on a single device.