SKU: 5399724097

有生之年,只想好好談場戀愛 (孤島Joe)

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有生之年,只想好好談場戀愛 (孤島Joe): Joe Joe # Joe 80 want

作者: 孤島Joe


       ★寫給所有寂寞靈魂的圖文作家,孤島Joe出道五年暖心力作!
  ★精心設計巧妙的反轉,插畫翻頁後,你將發現意想不到的結局……
  ★粉專三萬人追蹤,催淚爆文每每破萬人按鑽,紛紛敲碗出書!

  每個人來到世界時都是一座孤島,
  當你喜歡上另一個人,踏上另一座孤島,
  愛,會治癒每一顆寂寞的心。

  取之寂寞,用之寂寞,把和孤獨借來的靈感,
  寫成故事,寫給城市裡每個,有故事的靈魂。
  書中有四座孤島,每一座島都是關於愛的不同主題,寫給單身中、戀愛中、分手後的每一個你,以及一些非關愛情的暖心故事,療癒所有孤單的靈魂。
  看到「#故事未完請繼續」時要小心,插畫後的文字才是真正的完結。也許會心一笑,或者潸然淚下,這就是愛的各種滋味。
  希望你把每一座島都當成寶藏島,有人找到領悟,有人找到釋懷,有人找到勇氣,有人找到自己。

  原來,不管是誰,每個人都有過自己的幸運,自己的時代。
  原來,最深刻的感情,就是像不曾開始,也像不曾結束。


作者

孤島Joe

  80後出生的雙魚座,曾是孤獨失眠患者,現是沒時間睡覺者。

  取之寂寞,用之寂寞,把和孤獨借來的靈感,寫成故事,寫給城市裡每個,有故事的靈魂,我們,故事未完請繼續。

  有時候,是個被寫作耽誤的插畫家;有時候,是個被插畫耽誤的作詞人;有時候,是個被寫歌耽誤的廣告人;而不管什麼時候,都是一個愛喝咖啡的創意雜貨店店長。

  歌詞作品:〈錯過〉〈失眠人want睡〉〈跟著太陽走〉〈能不能你也當一天雙魚〉

  個人榮譽:〈華研國際全球華人網路詞曲創作大賽作詞組第一名〉
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SKU: 5399724097

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4.7 ★★★★★
Based on 15 reviews
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Product Reviews
J
Jiewen Wang
Dallas, 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
Massapequa, 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
Battle Creek, 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
New York, 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
Cuba, 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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