SKU: 81202663489

77Mm Variable Neutral Density (77Mm Variable Nd) Filter Hoya

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Description

77Mm Variable Neutral Density (77Mm Variable Nd) Filter HoyaVariable 0. 45 2. 7 Neutral Density Filter Reduce Exposure by 1. 5 9 Stops Darkens Entire Image Allows Reduced Shutter Speed Allows Wider Aperture Threadless Front Filter Ring The Hoya ND Variable Filter provides a convenient way to maintain exposure control by being able to vary the amount of light entering the camera by 1. 5 to 9 stops (0. 45 to 2. 7 density for Cine use). The precision built in double ring design allows the outer ring rotates to

  • Variable 0.45-2.7 Neutral Density Filter
  • Reduce Exposure by 1.5-9 Stops
  • Darkens Entire Image
  • Allows Reduced Shutter Speed
  • Allows Wider Aperture
  • Threadless Front Filter Ring

 

The Hoya ND Variable Filter provides a convenient way to maintain exposure control by being able to vary the amount of light entering the camera by 1.5 to 9 stops (0.45 to 2.7 density for Cine use). The precision built-in double ring design allows the outer ring rotates to control amount of neutral density effect anywhere within the 1.5 – 9 stop range. This double-ring design is also thin to reduce the likelihood of vignetting with wide-angle lenses. This control allows for many special effects such as being able to control depth of field by using a wider aperture or create or control motion blur by being able to choose just the right slower shutter speeds for perfect blurring.

The Hoya Variable Neutral Density filter can take the place of a range of graded ND filters which saves money by only needing to buy one filter and saves time on location or on set by not needing to change filters constantly to change the effect, just turn the right to get the effect you want. The HOYA Variable Neutral Density filter puts you in control.

Variable Neutral Density filters, and ND filters in general have these main uses:

  • Slow down shutter speed for motion blurring effects like waterfalls, cars or blurred panning movement to make the subject stand out from the background.
  • Allow wider apertures to be used to decrease depth-of-field, literally focusing more attention on the subject.
  • Allow higher ISO films to be used in brighter lighting conditions.
  • Allow cine/video cameras, which have a fixed shutter-speed range, to film on brighter lighting conditions such as the beach or in snow on a sunny day. 

The Hoya Variable Density filter uses high-quality optical glass from Hoya Corporation, the worlds largest optical glass manufacturer and is available in sizes 52mm to 82mm.

For best results Hoya recommends using a tripod when photographing with slow shutter speeds.

Notes:
The practical exposure range and light transmittance will vary depending on the situation. When using the filter near or at MIN a cross-like dark pattern will appear across the image and cannot be eliminated. This is a property of the filter and all variable ND filters.
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SKU: 81202663489

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Paul Pollock
Port Orchard, 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
Whiting, 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
Dallas, 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.
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Reviewed in the United States on July 25, 2025
J
Jiewen Wang
San Leandro, 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.
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Reviewed in the United States on July 2, 2025
N
Nader
Whiting, 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
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Reviewed in the United States on December 31, 2025

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