EPISODE · Aug 23, 2025 · 24 MIN
Designing Large Language Model Applications: A Holistic Approach to LLMs
from CyberSecurity Summary · host CyberSecurity Summary
A comprehensive overview of designing large language model applications, praised for its synthesis of advanced AI methods and practical applications. It explores fundamental concepts like prompting, fine-tuning, and reasoning, emphasizing how LLMs behave in practice through hands-on exercises and numerous research paper references. The text examines the ingredients of LLMs, including pre-training data, vocabulary, and tokenization, and details their architecture and learning objectives. It further investigates advanced techniques for fine-tuning, mitigating hallucinations, improving reasoning, and optimizing LLM inference, while also covering interfacing LLMs with external tools and the retrieval-augmented generation (RAG) pipeline. The book concludes by discussing LLM application paradigms, aiming to equip readers with the intuition and tools for building production-grade LLM solutions.You can listen and download our episodes for free on more than 10 different platforms:https://linktr.ee/cyber_security_summaryGet the Book now from Amazon:https://www.amazon.com/Designing-Large-Language-Model-Applications/dp/1098150503?&linkCode=ll1&tag=cvthunderx-20&linkId=f35a8451c3f08e12beb4f3b1b1ea9bcc&language=en_US&ref_=as_li_ss_tlDiscover our free courses in tech and cybersecurity, Start learning today:https://linktr.ee/cybercode_academy
What this episode covers
A comprehensive overview of designing large language model applications, praised for its synthesis of advanced AI methods and practical applications. It explores fundamental concepts like prompting, fine-tuning, and reasoning, emphasizing how LLMs behave in practice through hands-on exercises and numerous research paper references. The text examines the ingredients of LLMs, including pre-training data, vocabulary, and tokenization, and details their architecture and learning objectives. It further investigates advanced techniques for fine-tuning, mitigating hallucinations, improving reasoning, and optimizing LLM inference, while also covering interfacing LLMs with external tools and the retrieval-augmented generation (RAG) pipeline. The book concludes by discussing LLM application paradigms, aiming to equip readers with the intuition and tools for building production-grade LLM solutions.You can listen and download our episodes for free on more than 10 different platforms:https://linktr.ee/cyber_security_summaryGet the Book now from Amazon:https://www.amazon.com/Designing-Large-Language-Model-Applications/dp/1098150503?&linkCode=ll1&tag=cvthunderx-20&linkId=f35a8451c3f08e12beb4f3b1b1ea9bcc&language=en_US&ref_=as_li_ss_tlDiscover our free courses in tech and cybersecurity, Start learning today:https://linktr.ee/cybercode_academy
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Designing Large Language Model Applications: A Holistic Approach to LLMs
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