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  • Reasoning LLMs Deliver Value Today, So AGI Hype Doesnt . . .
    Let me stop you there The fact that some people use LLMs to generate text without thought and end up with lies hallucinations bullshit outputs has little to nothing to do with the concept of AIs and LLMs providing value LLMs objectively do provide value, the value depends on how they are fed and implemented
  • Understanding Reasoning LLMs - by Sebastian Raschka, PhD
    In this section, I will outline the key techniques currently used to enhance the reasoning capabilities of LLMs and to build specialized reasoning models such as DeepSeek-R1, OpenAI's o1 o3, and others
  • Understanding Reasoning LLMs - sebastianraschka. com
    In this article, I will describe the four main approaches to building reasoning models, or how we can enhance LLMs with reasoning capabilities I hope this provides valuable insights and helps you navigate the rapidly evolving literature and hype surrounding this topic
  • LLM Reasoning: Where it is today, where its going, and its . . .
    Tim Kellogg, principal architect at Icertis, led the discussion with an insightful breakdown of where LLM reasoning stands today, where it’s heading, and the challenges it still faces Tim opened the conversation by defining AI reasoning and how it has evolved beyond simple pattern recognition
  • What Are LLM Solutions and Why They Matter in 2025
    Fine-tuned LLMs that are trained with annotated, context-rich data outperform general-purpose models by a wide margin, especially in high-risk or compliance-driven environments The Real-World Value of LLM Solutions in 2025 So how are organizations applying LLM technology today? Customer Support Automation
  • Understanding LLMs’ Reasoning Limits Today . . . - Medium
    LLMs can handle some reasoning types well, particularly those aligned with pattern recognition, yet they often struggle with more nuanced or contextually demanding reasoning In this section,
  • Reasoning LLMs, Simply Explained - aibutsimple. com
    Reasoning LLMs, Simply Explained AI, But Simple Issue #55 Reasoning large language models (LLMs) are transformer-based LLMs that appear to “think” by breaking a more complex question down into smaller steps, resulting in intermediate steps before an output





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