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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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The Best Lightweight LLMs of 2025: Efficiency Meets Performance

ODSC - Open Data Science

As AI continues to evolve, there is growing demand for lightweight large language models that balance efficiency and performance. Together in this blog, were going to explore what makes an LLM lightweight, the top models in 2025, and how to choose the right one for yourneeds.

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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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This AI Paper Introduces Agentic Reward Modeling (ARM) and REWARDAGENT: A Hybrid AI Approach Combining Human Preferences and Verifiable Correctness for Reliable LLM Training

Marktechpost

Large Language Models (LLMs) rely on reinforcement learning techniques to enhance response generation capabilities. One critical aspect of their development is reward modeling, which helps in training models to align better with human expectations.

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

ODSC - Open Data Science

Here, we look at how you can analyze a global AI research community using Gephi and ChatGPT. 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.

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Understanding the Core Limitations of Large Language Models: Insights from Gary Marcus

ODSC - Open Data Science

In a recent episode of ODSC’s Ai X Podcast , which was recorded live during ODSC West 2024 , Gary Marcus, an influential AI researcher, shared a critical perspective on the limitations of large language models (LLMs), emphasizing the need for true reasoning capabilities in AI.