SKU: 57141836721

Hudson Reed Old London 600mm Cabinet & Marble Top (1TH) - Hunter Green

Sale price$325.33 Regular price$361.48
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Description

Hudson Reed Old London 600mm Cabinet & Marble Top (1TH) - Hunter GreenThe striking finish of this Hunter green unit will add contrast and impact to your traditional bathroom. This unit has soft close doors which limits the daily wear and tear and provides a quieter closing action. Supplied rigid for easy installation and with stunning White marble top basin. Technical Specification Height: 840 mm Weight: 29. 5 kg Width: 651 mm Depth: 511 mm Material: MDF Vinyl Smooth Matt Tap Holes: 1 Waste: No Bowl Shape: Square Inner

The striking finish of this Hunter green unit will add contrast and impact to your traditional bathroom. This unit has soft-close doors which limits the daily wear and tear and provides a quieter closing action. Supplied rigid for easy installation and with stunning White marble top basin.

Technical Specification

  • Height: 840 mm
  • Weight: 29.5 kg
  • Width: 651 mm
  • Depth: 511 mm
  • Material: MDF Vinyl Smooth Matt
  • Tap Holes: 1
  • Waste: No
  • Bowl Shape: Square
  • Inner Bowl Height: 160.0000 mm
  • Mount Type: Floor
  • Handle Type: Knob
  • Construction Type: Rigid
  • Fascia Thickness: 18.0000 mm
  • Hinge Type: 95 Degree Inset Clip-On S/C
  • Number of Shelves: 1
  • Manufacture Guarantee: 5 Years
  • Guarantee Details: During installation extra care must be taken to avoid damaging the fittings. We provide Manufacture Guarantee against faulty workmanship or materials (excluding serviceable parts), providing they have been installed, cared for and used in accordance with our instructions.
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    Exchange/Return Notes
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    SKU: 57141836721

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    4.9 ★★★★★
    Based on 23 reviews
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    Product Reviews
    J
    Jiewen Wang
    Houston, US
    ★★★★★ 5
    a comprehensive guide at the intersection of generative AI and cybersecurity
    Format: Kindle
    This book blends deep theoretical foundations with practical frameworks and forward-looking strategies. From adversarial risk models to actionable guidance using OWASP Top 10 for LLMs and the NIST AI RMF, it offers both technical depth and operational clarity. What makes it stand out is its balance of academic rigor and real-world CISO insights, providing a holistic perspective on securing GenAI systems. While it leans enterprise-focused, the content remains accessible to security engineers, risk managers, and policy leaders alike. Generative AI Security is a timely and essential read for anyone working to deploy GenAI responsibly—building systems with both power and integrity in today’s fast-evolving threat landscape.
    WAS THIS REVIEW HELPFUL?YesReportShare
    Reviewed in the United States on July 2, 2025
    N
    Nader
    Fort Morgan, US
    ★★★★★ 1
    Light on substance and heavy on flaws
    Format: Paperback
    The book has a great list of topics, but fails to provide much substance any of them. Most of the provided code is just comments that avoid the actual crux of the issues being discussed. (e.g. #implement the logic to validate XYZ - while the whole point of this chapter is teach how the heck we validate XYZ!) Some parts are plain wrong, for example the part on Graph based RAG is fundamentally flawed as it assumes the text embedding and the graph embedding are in the same latent space. (This is one of many more examples). Seems like the book was rushed, and the author has limited hands on experience (if any). At least we know based on the amount of flaws that it was not written by an LLM
    WAS THIS REVIEW HELPFUL?YesReportShare
    Reviewed in the United States on December 31, 2025
    N
    noam barkay
    Dallas, US
    ★★★★★ 5
    Excellent book to truly understand LLM design patterns
    Format: Paperback
    I just finished reviewing Ken Huang's pocket book on LLM Design Patterns, and WOW what an amazing resource! This book is excellent if you want to truly understand how to create and enhance intelligent AI language models, all that in your pocket! Ken makes the difficult things seem surprisingly easy, and that's the real MAGIC. - How to prepare your data for training by making it extremely clean. Developing the brains: the practical aspects of training, optimizing, and maintaining your models. - Learn amazing prompting techniques (such as Chain-of-Thought and Tree-of-Thoughts) to improve your AI's reasoning and problem-solving abilities. Learn everything there is to know about RAGs so that your LLM can incorporate outside expertise. - It also delves into creating "agentic" AI that is capable of action and planning (not only simple plan and execute but also enhanced techniques like ReWoo!) Really, this feels like a useful toolkit, so Ken thank you for that resource Thanks, Idan Habler
    WAS THIS REVIEW HELPFUL?YesReportShare
    Reviewed in the United States on June 9, 2025
    R
    Ryan Meyer
    Lowell, US
    ★★★★★ 3
    A Broad Overview, But Light on Modern Fine-Tuning
    Format: Paperback
    I'm currently really interested in fine-tuning LLMs and recently completed my first LoRA-based fine-tuning on a quantized model. I came to this book looking for more detail on fine-tuning. While it touches on the topic, I found the content didn’t quite align with the current state of the field in 2025. Techniques like LoRA, QLoRA, and PEFT weren’t really covered, and the material leaned more toward what I think are older or lower level approaches. That made it harder to connect with what I’m actually working on. That said, when I shifted to other chapters — like the sections on prompt engineering techniques such as Chain of Thought (CoT) and Tree of Thought (ToT) — I found more value. These sections were clearer, and I picked up a few practical insights, like using few-shot examples that walk through the CoT reasoning process. That’s not something I’ve tried before, and I can see how it might help smaller models that struggle with any type of reasoning tasks. Overall, the book feels more like a broad overview of all LLM concepts. For someone exploring many topics across the LLM ecosystem, it offers a wide-ranging introduction. But for readers like me who are actively trying to learn and apply techniques like fine-tuning and quantization, it may leave you wanting up-to-date guidance.
    WAS THIS REVIEW HELPFUL?YesReportShare
    Reviewed in the United States on August 10, 2025
    V
    Vineeth Sai
    Draper, US
    ★★★★★ 5
    Great foundation read for security!
    Format: Paperback
    This book is a great read! It builds a strong foundation and I would highly recommend it for builders who are interetsed in building on LLMs and ensuring everything is secure. Security is super important and this book does it justice!
    WAS THIS REVIEW HELPFUL?YesReportShare
    Reviewed in the United States on June 27, 2025

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