SKU: 30738936501

Primitivo ソファ120

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Description

Primitivo ソファ120Primitivo Primitivo Primitivo Item 120 Sizecm W120 D97 H6236 Specification Option Primitivo 120 ML L Product Status Delivery Delivery fee <3> [] (2F)

Primitivo

　人間が人間らしくいるためには「考えること」「自らの手でものを作ること」が大切だと言われています。近年は目まぐるしい科学技術の進歩により暮らしは便利で効率良くなりましたが、「考えること」は減り「手を動かすこと」も少なくなり人間が本来備えている感性は衰退しているように感じます。

　本シリーズ「Primitivo（プリミティーヴォ）」は人智を活かした明快な構造を探り、またその知恵を理解しながら組み立てる楽しさを感じてもらいたいという思いで開発されました。組み立て式であることはその楽しさだけではなく、梱包が小さくなることで輸送にかかるエネルギー負荷を抑えられたり、パーツがシンプルなので、単一パーツ単一素材になり、メンテナンス性の向上や素材の分別のし易さにもつながっています。

　木材は国産のナラ材を使用し、シンプルで必要最小限の加工とすることで、材料調達にかかるエネルギー、さらには加工にかかるエネルギー負荷も抑えられています。こうした「人間的で愛情と愉しさにあふれた家具」シリーズが「Primitivo（プリミティーヴォ）」です。




●Item
　プリミティーヴォ　ソファ120

●Size（cm）
　W120　D97　H62（座面高：36）
　※天然木の特性上、表記寸法と多少の誤差が生じる場合がございます。

●Specification
　フレーム
　材種：ナラ　無垢材
　塗装：ソープ仕上げ ／ オイル仕上げ（ナチュラル）／オイル仕上げ（アカネ）

　座面（カバーリング）
　張地：ピエトラシリーズ

　組立て式

●Option
　・【替カバー】Primitivo ソファ120
　・レザーポケット
　・フレックス バッククッション
　・クッションM／L
　・カーポ　ヘッドレスト
　・【替カバー】フレックス バッククッション
　・【替カバー】クッションL
　・【替カバー】カーポ　ヘッドレスト

　※木の紹介はこちら
　※仕上げについてはこちら
　※張り地についてはこちら
　※メンテナンスについてはこちら


●Product Status
　受注生産品：ご納品までに製作期間をいただきます。
　※納期についての詳細はこちら


●Delivery
　「開梱・設置・梱包材引下げ」の配送となります。

　・Delivery fee
　　配送料金は、商品のサイズやお届けの地域によって異なります。
　　当商品の配送区分：<家具の大きさ3>
　　※ソファ単体毎に配送料金が必要となります。
　　※配送料金はこちら

　[特記事項]
　　・ご注文前に、必ず搬入経路のご確認をお願いいたします。
　　・付帯作業(2F吊上げなど)が発生した場合は、別途ご請求させていただきます。
　　・搬入経路などのご相談は、お気軽にご連絡ください。
　　・離島、一部特定地域は、別途追加料金が発生いたします。その際は、ご連絡いたします。


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SKU: 30738936501

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4.8 ★★★★★
Based on 21 reviews
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Product Reviews
P
Paul Pollock
Natrona Heights, US
★★★★★ 5
Your Blueprint for Building Smarter AI!
Format: Paperback
If you're building AI and sometimes feel a bit lost, "LLM Design Patterns" by Ken Huang is like finding the secret map you've been searching for. Ken Huang, who clearly knows his stuff (he's a renowned AI expert and works with big names like OWASP and NIST), writes in a way that just clicks, without getting bogged down in super-dense tech talk. The author even acknowledges using AI to make the language clearer for a smooth reading experience! This book covers everything you need, from getting your data squeaky clean to making AI agents that can actually think and act autonomously. For me, the parts on Retrieval-Augmented Generation (RAG) and advanced ways to 'talk' to your AI (prompting) were particularly eye-opening and immediately useful for my projects. Plus, it has handy code snippets that really help you grasp the ideas. While they're not ready for direct production copy-pasting, they illustrate the concepts perfectly for learning. It's not for absolute beginners – you'll want some basic Python and machine learning smarts to get the most out of it – but the effort is totally worth it. It even delves into making sure your AI is fair and unbiased, which was a real lightbulb moment for me. This book is crammed with actionable advice; it's less about abstract theory and more about real-world solutions you can actually use. If you're serious about building impressive AI systems professionally, this is a must-read.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 7, 2025
A
Allen Wyma
Massapequa, US
★★★★★ 5
Great Resource when Integrating AI
Format: Kindle
This is a great resource when building systems that integrate with AI. It manages to cover the entire lifecycle and even tips for corporate environments!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 26, 2025
O
Om S
Cuba, US
★★★★★ 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
J
Jiewen Wang
Lake Worth, 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
Alexandria, 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

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