Digital Yacht JB1 NMEA0183 & Power Junction Box
SKU: 50175051418

Digital Yacht JB1 NMEA0183 & Power Junction Box

$36.90 $41.00
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Description

Digital Yacht JB1 NMEA0183 & Power Junction BoxEasy solution for NMEA 0183 and 12 24V DC power connectivity Compact waterproof junction box measures just 105 x 70 x 35mm Three inlet glands you can add more glands if you require. Supplied with two x 3 way Wago junction blocks (recommended for positive and negative power connections) and six x 2 way (recommended for NMEA) Simply lift lever and insert cables into the block and snap shut for reliable connections Accepts cable from 0. 25mm to 4mm you

  • Easy solution for NMEA 0183 and 12/24V DC power connectivity
  • Compact waterproof junction box- measures just 105 x 70 x 35mm
  • Three inlet glands- you can add more glands if you require.
  • Supplied with two x 3-way Wago junction blocks (recommended for positive and negative power connections) and six x 2-way (recommended for NMEA)
  • Simply lift lever and insert cables into the block and snap shut for reliable connections
  • Accepts cable from 0.25mm to 4mm- you can also twist smaller cables together
  • Wago connectors mount onto internal base using supplied velcro pads allowing connections to be easily completed and then fixed in place before assembly of the case
  • Can make the device waterproof to IPX6
  • Includes 1m power input cable (5A)

Lots of systems still use NMEA 0183 for connectivity. It's a simple two wire system but there's no standard colour codes or connector type. This means installers need to design their own solution. NMEA devices that transmit data are called talkers and they connect to devices that receive data- listeners. In other words NMEA OUT goes to NMEA IN. With a plus and minus polarity for NMEA data it involves two wires and while a talker can broadcast to multiple listeners (typically up to 5 devices) two talkers can't connect together without using a specialist multiplexer.

A typical installation would be connecting an AIS transponder to a plotter. The NMEA out from the AIS would connect to the NMEA input on the plotter. If you need to add wifi connectivity for an iPad or tablet then our WLN10SM could also connect to the NMEA output of the AIS. Some devices may have multiple NMEA outputs. One at 4800 baud for traditional instruments and one at 38400 baud for AIS. These both require their own dedicated wiring.

The new JB1 junction box from Digital Yacht is a simple easy to install solution for NMEA 0183 and power connections. It uses a patented spring lock terminal system from Wago. This allows various sized cables to be connected and joined in seconds.

The internal connections use a patented Wago system. The two way joining blocks measure just 12 x 18mm and this can be removed to aid inserting thin and fiddly cables. Open the lever insert the cable and snap shut for a reliable insulated connection.

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SKU: 50175051418

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4.1 ★★★★★
Based on 364 reviews
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O
Om S
Louisville, 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
Charlottesville, 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
Houston, 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
Lexington, 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
Lexington, 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.
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Reviewed in the United States on August 10, 2025

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