SKU: 5041068264

TCR Advanced Pro 0-AXS - Carbon

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Description

TCR Advanced Pro 0-AXS - CarbonSuperleicht, megaeffizient und fhrt sich wie ein Traum. Dieses vielseitige Rennrad hat einen top Rahmen aus Carbon und voll integrierte Teile, damit du mit krasser Geschwindigkeit und super Handling bergauf, in Kurven und beim Abfahren fahren kannst. System Optimierung Der Rahmensatz, die Laufrder, das Cockpit und andere Teile werden zusammen entwickelt und getestet, damit sie als System funktionieren. Die brandneue OverDrive Aero

Superleicht, megaeffizient und fährt sich wie ein Traum. Dieses vielseitige Rennrad hat einen top Rahmen aus Carbon und voll integrierte Teile, damit du mit krasser Geschwindigkeit und super Handling bergauf, in Kurven und beim Abfahren fahren kannst.

System Optimierung
Der Rahmensatz, die Laufräder, das Cockpit und andere Teile werden zusammen entwickelt und getestet, damit sie als System funktionieren. Die brandneue OverDrive Aero-Gabelschafttechnologie wird mit einem Contact SL AeroLight-Vorbauten und einem Contact SL-Lenker kombiniert, um eine interne Kabelführung zu integrieren, die die Oberkappe, Kabel und Distanzstücke in einer aerodynamischeren, benutzerfreundlicheren Konfiguration vereint.

Siegreiche Effizienz
Mit einem besseren Verhältnis von Steifigkeit zu Gewicht als die letzte Generation, neuen aerodynamischen Rohrformen und einem geringeren Gesamtgewicht bietet dieses kompromisslose Rennrad explosive Beschleunigung und unnachgiebige Tretsteifigkeit. Das Ergebnis ist eine siegreiche Leistung in den entscheidenden Momenten.

Integrierte Aerodynamik
Alle Rohrformen werden mit Hilfe von CFD-Modellierung (Computational Fluid Dynamics) und Windkanaltests entwickelt. Von der abgeschnittenen Ellipsenform der Rahmenrohre bis hin zum neuen Cockpit-Design und der Integration der Komponenten ergibt sich ein stromlinienförmigeres Profil, das die aerodynamische Gesamtleistung im Vergleich zur Vorgängergeneration verbessert.


Ausstattung:
Modeljahr: 2026
Rahmen: Advanced Carbon Rahmen, 12x142 mm Max. Reifenfreiheit: 33mm
Gabel: Advanced SL Vollcarbon Gabel, OD Aero Gabelschaft, 12x100 mm
Kurbel: Sram Force E1 Quarq Powermeter, 48/35
Innenlager: Sram DUB Pressfit
Kette: Sram Force E1
Kassette: Sram Force E1, XG-1270-E1, 10-36 12 Fach
Schalthebel: Sram Force AXS E1
Umwerfer: Sram Force AXS E1
Schaltwerk: Sram Force AXS E1
Bremsen: Sram Force AXS E1 HRD, 160/140mm
Bremshebel: Sram Force AXS E1 HRD
Reifen: CADEX Race GC, 700x30c, Tubeless Ready, 240TPI Auslieferung schlauchlos
Naben: GIANT SLR 0 Disc
Felgen: GIANT SLR 0 Disc Carbon, Tubeless Ready, 40 mm
Speichen: GIANT SLR 0 Disc
Lenker: GIANT Contact SLR
Vorbau: GIANT Contact SL Aerolight
Sattel: Giant Fleet SL
Sattelstütze: GIANT Variant Carbon
Zubehör (teilw. verbaut): Computer Befestigung zur Vorbauintegration 1x Flaschenhalter Tubeless Kit (Dichtmittel, Ventile, Reifenheber, Ventilkernwerkzeug, Bedienungsanleitung)
Max. Reifenbreite: 33 mm

* In seltenen Fällen liefern unsere Hersteller Fahrräder mit geänderten, aber gleichwertigen Komponenten.

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SKU: 5041068264

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4.7 ★★★★★
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Product Reviews
J
Jiewen Wang
Massapequa, 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
Birmingham, 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
Charlottesville, 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
Dallas, 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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