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Solidsteel Accessories Hyperspike PadsSolidsteel Accessories Hyperspike Pads The S Series Kits & Accessories allows the customization and completion of what offered by the S Series. WE CONSIDER AS KITS & SPARE PARTS: S Series Starter Kit: its a basilar kit only made of frame & hardware parts able to create a complete two level rack. The clearance between the shelves vary between 165 mm (6,49 in) and 345 mm (13,58 in) for the standardized custom lenghts (for other special measures we
Solidsteel Accessories Hyperspike Pads
The S Series Kits & Accessories allows the customization and completion of what offered by the S Series.WE CONSIDER AS KITS & SPARE PARTS:
- S Series Starter Kit: it’s a basilar kit only made of frame & hardware parts able to create a complete two-level rack. The clearance between the shelves vary between 165 mm (6,49 in) and 345 mm (13,58 in) for the standardized custom lenghts (for other special measures we invite you to contact us by e-mail). Included in this kit there are: A) n. 4 top caps; B) n. 4 bottom feet; C) n. 4 top screws; D) n. 4 bottom screws; E) n. 4 aluminium poles (of the desired dimensions); F) n. 4 S Series Pads; G) n. 4 S Series Spikes; H) n. 8 plastic fittings.
- S Series Add Kits: it’s an additional kit only made of frame & hardware parts able to create a suppletive level on a rack. The clearance between the shelves vary between 145 mm (5,7 in) and 345 mm (13,58 in) for the standardized custom lenghts (for other special measures we invite you to contact us by e-mail). Included in this kit there are: A) n. 4 inner screws; B) n. 4 aluminium poles (of the desired dimensions); C) n. 8 plastic fittings.
- for the S3 Series: A) S3 Set Shelves (S3-2 Set Shelves, S3-3 Set Shelves, S3-4 Set Shelves and S3-5 Set Shelves); B) S3 Top Shelf; C) S3 Inner Shelf.
- for the S4 Series: A) S4 Set Shelves (S4-2 Set Shelves, S4-3 Set Shelves, S4-4 Set Shelves); B) S4 Top Shelf; C) S4 Inner Shelf.
- for the S5 Series: A) S5 Set Shelves (S5-2 Set Shelves, S5-3 Set Shelves, S5-4 Set Shelves and S5-5 Set Shelves); B) S5 Top XShelf; C) S5 Inner XShelf.
- If you need to create an S5-4 in black with the following clearance (mm from the bottom) 325/265/145, then you will need to order: A) S5-4 black Set Shelves; B) S5 StarterKit 325, black; C) S5 AddKit 265, black ; D) S5 AddKit 145, black.
- If you already have a standard S3-2 in black and need to add an extra level, then you should order: A) S3 inner shelf; B) S3 AddKit (of the desired measure).
- The S Series Pads, which are our stainless steel discs of 25 mm (0,98 inch) of diameter, designed to support all the S Series spikes. They are sold separately as accessories, exception made for the S3-A&B and S5 Series products, on which are always included as standard. We strictly recommend the purchasing of these parts;
- The S Series Spikes, which are our traditional S Series spikes made of stainless steel for an high efficiency against component’s vibrations;
- The S5 Series Cones, which are the technical stainless steel cones adopted for the S5 Series products;
Technical Specifications
Please, for the technical specifications check the other products from this Series.
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- We offer a 30-day return/exchange service after receiving.
- Final sale items are not eligible for returns or exchanges.
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4.8 ★★★★★
Based on 9 reviews
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Product Reviews
★★★★★ 4
Title: Really Good Book for Learning LLMs
Format: Paperback, Format: Paperback
I picked up this book after struggling with LLM implementation at work. Ken Huang explains things clearly without too much technical jargon.
The book covers everything from data preparation to building AI agents. I especially liked the chapters on RAG and prompting techniques - they helped me improve my current projects. The code examples actually work, which is nice.
Some parts are pretty advanced, so you need basic Python knowledge. I had to read a few chapters twice to fully get it. The fairness and bias detection section was eye-opening.
Good practical advice throughout. Not just theory - real solutions you can use. Worth the money if you're serious about LLM development.
Recommended for anyone building AI systems professionally.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 25, 2025
★★★★★ 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
★★★★★ 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
★★★★★ 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
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Reviewed in the United States on June 9, 2025
★★★★★ 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.
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Reviewed in the United States on August 10, 2025
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