Remove Hybrid AI Remove Large Language Models Remove Natural Language Processing
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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).

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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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A Guide to Mastering Large Language Models

Unite.AI

Large language models (LLMs) have exploded in popularity over the last few years, revolutionizing natural language processing and AI. What are Large Language Models and Why are They Important? In Summary Large language models represent a new era in AI capabilities.

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Unbundling the Graph in GraphRAG

O'Reilly Media

One popular term encountered in generative AI practice is retrieval-augmented generation (RAG). Reasons for using RAG are clear: large language models (LLMs), which are effectively syntax engines, tend to “hallucinate” by inventing answers from pieces of their training data. Do LLMs Really Adapt to Domains?

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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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