Duracell Coppertop AA Battery with POWER BOOST?, 4 Pack Long-Lasting Batteries
SKU: 69263397700

Duracell Coppertop AA Battery with POWER BOOST?, 4 Pack Long-Lasting Batteries

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Duracell Coppertop AA Battery with POWER BOOST?, 4 Pack Long-Lasting BatteriesAt Duracell, we provide trusted power to those who depend on us to keep their lives charged. Duracell Coppertop batteries with POWER BOOST Ingredients deliver dependable power to your everyday devices throughout the home, like toys, remote controls, flashlights, calculators, clocks and radios, wireless mice, keyboards, and more. The pack of high performance 1. 5 volt batteries will last in storage for up to 12 years, so you can rest assured they will

At Duracell, we provide trusted power to those who depend on us to keep their lives charged.
Duracell Coppertop batteries with POWER BOOST™ Ingredients deliver dependable power to your everyday devices throughout the home, like toys, remote controls, flashlights, calculators, clocks and radios, wireless mice, keyboards, and more. The pack of high performance 1.5 volt batteries will last in storage for up to 12 years, so you can rest assured they will be ready when you need them. We're proud to offer you Duracell 1.5 Volt Coppertop Alkaline AA Batteries as part of our trusted lineup of batteries - from storm season to holiday needs, Duracell is the #1 trusted battery brand for the moments that matter most.

Duracell Coppertop AA Batteries with POWER BOOST™, 4 Pack
Alkaline Batteries with POWER BOOST™ technology to deliver lasting performance in your devices
#1 trusted brand of pharmacists and medical professionals
Guaranteed up to 12 years in storage (5 years for 9V batteries)
Recommended for medical devices, remote controls, calculators, toys, games, and smoke detectors
Duracell Coppertop batteries are available in AA, AAA, C, D and 9V battery sizes
Duracell batteries also available in the Duracell Optimum battery, Hearing Aid battery, and lithium coin button battery
Tips for Battery Care and Use:
Duracell batteries are a reliable and important source of daily portable power. To ensure you get the most from your Duracell batteries, follow these general "DO" and "DON'T" tips for proper battery use and storage:

DO - Keep all batteries in a safe place away from children and pets, particularly the smaller sized batteries.

DON'T - Remove the battery label, or attempt to take the battery apart, or dispose of in a fire as this may lead to rupture and/or chemical burns.

DO - Store batteries, in their original packaging, in a dry place and at normal room temperature until ready to use.

DON'T - Attempt to recharge non-rechargeable batteries. This can cause your batteries to overheat or leak.

DO - Use the correct size and type of battery specified by the manufacturer of your device.

DON'T - Carry batteries loose in your pocket or purse as they may create a safety risk. They can be shorted by contact with metal objects and may leak, overheat or rupture.

DO - Replace all used batteries in your device at the same time. Insert batteries properly, with the plus (+) and minus (-) terminals aligned correctly. CAUTION: Some equipment using more than three batteries may appear to work properly even if one battery is inserted incorrectly.

DON'T - Mix old and new batteries, batteries of different brands, or batteries of different types (for example heavy duty zinc chloride batteries and alkaline batteries) in the same device as this may cause the batteries to leak.

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SKU: 69263397700

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4.0 ★★★★★
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O
Om S
New York, 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
Lake Worth, 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
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
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 31, 2025
N
noam barkay
Chelsea, 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
Waukegan, 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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