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Description
Golden Severum Cichlid Heros Efasciatus 5cmGolden Severum Cichlid Heros Efasciatus Overview Synonyms Chromys appendiculata, C. fasciata, Cichlasoma severum perpunctatum, Heros appendiculatus, Uarus centrarchoides Distribution Brazil and Peru. Maximum Size 20cm (7. 9") Temperature 23 29C Water Parameters Captive bred fish will acclimatise to a wide range of conditions. Wild caught fish should be provided with soft, acidic water. Compatibility Community with no small fish Lighting No special
Golden Severum Cichlid Heros EfasciatusOverview
| Synonyms | Chromys appendiculata, C. fasciata, Cichlasoma severum perpunctatum, Heros appendiculatus, Uarus centrarchoides |
| Distribution | Brazil and Peru. |
| Maximum Size | 20cm (7.9") |
| Temperature | 23-29°C |
| Water Parameters | Captive-bred fish will acclimatise to a wide range of conditions. Wild-caught fish should be provided with soft, acidic water. |
| Compatibility | Community with no small fish |
| Lighting | No special requirements |
| Sexual Dimorphism | Mature males usually have more pointed dorsal and anal fins. |
| Feeding | Flake, granules, cichlid pellets and frozen foods |
Description
Care
The Green Severum is a peaceful species, suitable for communities of non-aggressive medium-large sized fish. In the wild, the gentle Green Severum can be found in slow-moving waters packed with heavy with vegetation. Therefore the aquarium should include plenty of robust plant species along with numerous rocky caves and bogwood pieces. Green Severums can be kept in groups or pairs, but should a pair choose to spawn in a community setting, they will become much more aggressive towards the other fish. Ideally the tank will be at least 4ft long with lots of visual barriers for the other fish to escape the Green Severums attentions. Male fish can be sexed by the presence of cheek markings lacking in the smaller females. If the male seems to overly harass the female, many aquarists find that adding a couple more females will help to spread the brunt of the aggression. After a time, these fish learn to recognise their owner and often come to the glass to greet them or wait for food. A gold variety of this species is also available.
Feeding
Slow-sinking cichlid pellets, flake, lettuce, spinach, frozen foods such as mosquito larvae, brineshrimp, Mysis shrimp, Krill etc. Will avidly consume soft-leaved plants.
Breeding
A breeding aquarium should be set up with soft, acidic water and the pair acclimatised across. The temperature should be carefully raised to 30 °C. Some flat pieces of slate should be provided, which the fish will clean prior to laying the eggs on them. The female usually deposits between 200 and 1000 eggs onto the rocks, and these are then vigorously defended by both parents. The eggs should hatch after 48-72 hours, and once free-swimming the parents will be seen herding them to different areas or pits dug in the substrate. The young can be offered finely powdered flake foods and microworms. It is not unusual for parental care to last up to 6 weeks.
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4.1 ★★★★★
Based on 2348 reviews
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Product Reviews
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 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
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Reviewed in the United States on June 9, 2025
★★★★★ 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