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  • React
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Fine-Tuning LLMs for Domain-Specific Support

Transform generic AI models into specialized tools for customer support through fine-tuning, enhancing accuracy, efficiency, and compliance.
Image of Author zaoyang
zaoyang
Owner of \newline and previously co-creator of Farmville (200M users, $3B revenue) and Kaspa ($3B market cap). Self-taught in gaming, crypto, deep learning, now generative AI. Newline is used by 250,000+ professionals from Salesforce, Adobe, Disney, Amazon, and more. Newline has built editorial tools using LLMs, article generation using reinforcement learning and LLMs, instructor outreach tools. Newline is currently building generative AI products that will be announced soon.
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Layer-Wise Fine-Tuning vs Full Model Tuning

Explore the differences between layer-wise fine-tuning and full model tuning for large language models, including their benefits and drawbacks.
Image of Author zaoyang
zaoyang
Owner of \newline and previously co-creator of Farmville (200M users, $3B revenue) and Kaspa ($3B market cap). Self-taught in gaming, crypto, deep learning, now generative AI. Newline is used by 250,000+ professionals from Salesforce, Adobe, Disney, Amazon, and more. Newline has built editorial tools using LLMs, article generation using reinforcement learning and LLMs, instructor outreach tools. Newline is currently building generative AI products that will be announced soon.
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Horizontal Scaling for LLMs: Best Practices

Learn how horizontal scaling optimizes large language model deployments by improving efficiency, cost management, and fault tolerance.
Image of Author zaoyang
zaoyang
Owner of \newline and previously co-creator of Farmville (200M users, $3B revenue) and Kaspa ($3B market cap). Self-taught in gaming, crypto, deep learning, now generative AI. Newline is used by 250,000+ professionals from Salesforce, Adobe, Disney, Amazon, and more. Newline has built editorial tools using LLMs, article generation using reinforcement learning and LLMs, instructor outreach tools. Newline is currently building generative AI products that will be announced soon.
•Last Updated:
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How Layer Dropping Speeds Up LLM Inference

Layer dropping enhances LLM performance by reducing computation and memory load, achieving speed boosts without significant accuracy loss.
Image of Author zaoyang
zaoyang
Owner of \newline and previously co-creator of Farmville (200M users, $3B revenue) and Kaspa ($3B market cap). Self-taught in gaming, crypto, deep learning, now generative AI. Newline is used by 250,000+ professionals from Salesforce, Adobe, Disney, Amazon, and more. Newline has built editorial tools using LLMs, article generation using reinforcement learning and LLMs, instructor outreach tools. Newline is currently building generative AI products that will be announced soon.
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Retrieval-Augmented Feedback Loops: How They Work

Explore how retrieval-augmented feedback loops enhance AI performance by integrating real-time data and adaptive learning for improved accuracy.
Image of Author zaoyang
zaoyang
Owner of \newline and previously co-creator of Farmville (200M users, $3B revenue) and Kaspa ($3B market cap). Self-taught in gaming, crypto, deep learning, now generative AI. Newline is used by 250,000+ professionals from Salesforce, Adobe, Disney, Amazon, and more. Newline has built editorial tools using LLMs, article generation using reinforcement learning and LLMs, instructor outreach tools. Newline is currently building generative AI products that will be announced soon.
•Last Updated:
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