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The Emergence of Self-Reflection in AI: How Large Language Models Are Using Personal Insights to Evolve

Unite.AI

Artificial intelligence has made remarkable strides in recent years, with large language models (LLMs) leading in natural language understanding, reasoning, and creative expression. Yet, despite their capabilities, these models still depend entirely on external feedback to improve.

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The Hidden Risks of DeepSeek R1: How Large Language Models Are Evolving to Reason Beyond Human Understanding

Unite.AI

Renowned for its ability to efficiently tackle complex reasoning tasks, R1 has attracted significant attention from the AI research community, Silicon Valley , Wall Street , and the media. Yet, beneath its impressive capabilities lies a concerning trend that could redefine the future of AI.

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Majority of AI Researchers Say Tech Industry Is Pouring Billions Into a Dead End

Flipboard

This, more or less, is the line being taken by AI researchers in a recent survey. In December, Google CEO Sundar Pichai went on the record as saying that easy AI gains were "over" but confidently asserted that there was no reason the industry couldn't "just keep scaling up." You can only throw so much money at a problem.

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Knowledge Fusion of Large Language Models (LLMs)

Analytics Vidhya

Introduction In Natural Language Processing (NLP), developing Large Language Models (LLMs) has proven to be a transformative and revolutionary endeavor. These models, equipped with massive parameters and trained on extensive datasets, have demonstrated unprecedented proficiency across many NLP tasks.

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5 Best Large Language Models (LLMs) (September 2024)

Unite.AI

The field of artificial intelligence is evolving at a breathtaking pace, with large language models (LLMs) leading the charge in natural language processing and understanding. As we navigate this, a new generation of LLMs has emerged, each pushing the boundaries of what's possible in AI. Visit GPT-4o → 3.

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New AI training techniques aim to overcome current challenges

AI News

Addressing unexpected delays and complications in the development of larger, more powerful language models, these fresh techniques focus on human-like behaviour to teach algorithms to ‘think. First, there is the cost of training large models, often running into tens of millions of dollars.

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The Full Story of Large Language Models and RLHF

AssemblyAI

We are going to explore these and other essential questions from the ground up , without assuming prior technical knowledge in AI and machine learning. The problem of how to mitigate the risks and misuse of these AI models has therefore become a primary concern for all companies offering access to large language models as online services.