SKU: 43807093588

Sony BRAVIA 7 65" QLED XR Mini LED 4K HDR Smart TV

$764.55 $849.50
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Description

Sony BRAVIA 7 65" QLED XR Mini LED 4K HDR Smart TVSony BRAVIA 7 65" QLED XR Mini LED HDR 4K Smart TV (K65XR70U) Sonys BRAVIA 7 TV combines their powerful XR Processor with the precise light control of Mini LED screen technology to deliver a bright, contrast rich image with natural colours and superb detail. It's no surprise that a company with so much experience in the film industry can also craft cinema like displays for home use. Premium processing power with XR Processor The BRAVIA 7s XR Processor

Sony BRAVIA 7 65" QLED XR Mini LED HDR 4K Smart TV (K65XR70U)

Sony’s BRAVIA 7 TV combines their powerful XR Processor™ with the precise light control of Mini LED screen technology to deliver a bright, contrast rich image with natural colours and superb detail.  It's no surprise that a company with so much experience in the film industry can also craft cinema-like displays for home use.

Premium processing power with XR Processor™

The BRAVIA 7’s XR Processor™ cross-analyses individual picture elements and quickly identifies the human focal point, so that it can immediately enhance each detail of that area. Instead of applying generic changes to the entire frame, it recognises how individual parts of the whole interact with each other and makes precise adjustments to create a more natural picture.

The XR Processor™ contributes to a richer sound experience, too. With two powerful side-mounted speakers reproducing clear sound from the screen, your family and friends will feel like they’re at the cinema.

XR Backlight Master Drive

XR Backlight Master Drive uses a unique local dimming algorithm that controls the thousands of LEDs with absolute precision to deliver impressively deep blacks and stunning highlights that feel real. It's the same technology used in Sony’s master monitors that professional creators use when making a movie, so you know it can be trusted to convey their original intent.

Stunning design with 4-way multi-position stand

Bravia 7 has been designed with an almost invisible bezel, minimising distractions so that you can focus on the action on-screen. An ingenious stand design provides maximum flexibility with a choice of 4 settings including an outside position, an inside position for smaller shelves or two soundbar positions to accommodate selected soundbars.

Google TV built-in

Discover movies, TV shows, games and much more from Google Play™. Enjoy a huge and ever-growing choice of apps on your Sony Smart TV. Browse 700,000+ movies and TV episodes from across your streaming services, all in one place and organized into topics and genres based on what interests you.

And if you're feeling really lazy, you can simply ask the remote's built-in Google Assistant to pull up a show or movie. You can also adjust the volume, change channels or inputs, and control other basic TV functions using your voice.

More streaming options

The BRAVIA 7 65 has Chromecast built-in and Apple AirPlay® 2 support so you can easily stream a wide range of content from your mobile device or compatible computer.  This TV also includes the Apple TV streaming app, so you can rent, buy, and watch titles from Apple's video library, and subscribe to Apple TV channels, without having to connect a separate device.

Great for gaming

The Bravia 7 65 is an excellent match for your PC or next-gen games console, with support for Auto Low Latency Mode (ALLM), 4K at 120Hz and Variable Refresh Rate (VRR) for smooth graphics without frame tearing or stuttering. And if you've got a PS5, you'll benefit from Auto HDR Tone Mapping for more accurate detail and colour.

Why Buy from Weybridge Audio?

  • Expert advice from real AV specialists
  • In-store demos available
  • Professional delivery & installation options
  • Local service, ongoing support

Available Sizes:

55" | 65" | 75" | 85"

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SKU: 43807093588

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4.2 ★★★★★
Based on 26 reviews
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Product Reviews
O
Om S
Charlottesville, 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
Boise, 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
Carnegie, 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
Massapequa, 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
Battle Creek, 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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