SKU: 9151581671

Krypto Kunst "Take the orange Pill"

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Description

Krypto Kunst "Take the orange Pill"In der Matrix whlt Neo die rote Pille, um die Wahrheit zu sehen. In der Bitcoin Welt ist sie orange. Take the orange Pill" ist die Einladung, das Geldsystem zu hinterfragen, und dieses 3D Bild macht aus dem Insider Spruch ein Stck Wand Kunst: eine fein gravierte Acrylplatte vor leuchtend orangem Hintergrund, gerahmt und bereit zum Aufstellen oder Aufhngen. Fr wen ist das Bild? Fr alle, die den Spruch kennen und beim Lesen genickt haben. Es

In der Matrix wählt Neo die rote Pille, um die Wahrheit zu sehen. In der Bitcoin-Welt ist sie orange. „Take the orange Pill" ist die Einladung, das Geldsystem zu hinterfragen, und dieses 3D-Bild macht aus dem Insider-Spruch ein Stück Wand-Kunst: eine fein gravierte Acrylplatte vor leuchtend orangem Hintergrund, gerahmt und bereit zum Aufstellen oder Aufhängen.

Für wen ist das Bild?

Für alle, die den Spruch kennen und beim Lesen genickt haben. Es funktioniert im Home-Office als Statement hinter dem Schreibtisch, im Flur als Gesprächsstarter und im Regal angelehnt als Teil eines Krypto-Setups. Wer die Referenz nicht kennt, sieht einfach ein grafisch starkes Bild in Orange.

Als Geschenk

Das richtige Geschenk für den Bitcoin-Maximalisten, der Münzen schon hat. Kunst verschenkt im Krypto-Bereich fast niemand, genau deshalb bleibt dieses Bild hängen, im Kopf und an der Wand. Anlässe: Einzug, neues Büro, Geburtstag oder als Dankeschön für die beste Orange-Pill-Überzeugungsarbeit.

Lieferumfang

  • Gerahmtes 3D-Bild „Take the orange Pill" mit gravierter Acrylplatte
  • Schutzscheibe aus Kunststoff statt Glas: leichter, bruchsicher, genauso klar

Maße & Material

Rahmen außen 23,5 × 32,5 cm
Bild ohne Passepartout 21 × 30 cm
Bildausschnitt mit Passepartout 13 × 18 cm
Materialien Rahmen aus Hartfaserplatte, Passepartout aus Papier, Hintergrund Fotopapier, 3D-Motiv aus graviertem Acryl
Pflege einfach mit dem Staubwedel reinigen

Versand & Rückgabe

Bruchsicher verpackt, kostenloser Versand innerhalb Deutschlands, meist innerhalb von 24 Stunden. 30 Tage Rückgaberecht. EU-Kunden finden ausgewählte Produkte bei Etsy und eBay.

Häufige Fragen

Was bedeutet „Take the orange Pill"?
Eine Anspielung auf die Matrix-Szene mit der roten Pille: Wer die „orange Pille" nimmt, beginnt, Bitcoin und das Geldsystem zu verstehen. Orange ist die Markenfarbe von Bitcoin.

Aufstellen oder aufhängen?
Beides möglich. Mit 23,5 × 32,5 cm passt das Bild auf Regal und Sideboard, an der Wand wirkt es in Augenhöhe am stärksten.

Warum Kunststoff statt Glas?
Leichter und bruchsicher beim Versand und beim Aufhängen, ohne sichtbaren Unterschied in der Klarheit.

Shipping Notes
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Exchange/Return Notes
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SKU: 9151581671

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4.3 ★★★★★
Based on 19 reviews
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Product Reviews
O
Om S
Alexandria, 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
Omaha, 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
N
noam barkay
Draper, 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
Los Angeles, 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

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