SKU: 2473329874

Bardo Pond - Melt Away (2xLP, Comp)

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Description

Bardo Pond - Melt Away (2xLP, Comp)Media Condition: Mint (M) Sleeve Condition: Near Mint (NM or M ) Comments: SEALED, brand new copy General notes about this release (please note: our version may differ a little. see the comments above): The Bandcamp release page notes "Melt Away, the new double LP compilation, catalogues late 90s rarities and outtakes from a creative apex in Bardo Pond's career" and "shipping out on or around October 25, 2024". From rear of sleeve: Tracks A1 A3 & B1

Media Condition: Mint (M)
Sleeve Condition: Near Mint (NM or M-)

Comments:
SEALED, brand new copy

General notes about this release (please note: our version may differ a little. see the comments above):
The Bandcamp release page notes "Melt Away, the new double LP compilation, catalogues late-’90s rarities and outtakes from a creative apex in Bardo Pond's career" and "shipping out on or around October 25, 2024". From rear of sleeve: Tracks A1-A3 & B1-B3 "Recorded at Studio Red, Philadelphia PA and Cycle Sounds Philadelphia, PA, '96-'98"". Tracks C1-C2 & D1-D2 "Recorded in the Lemur House Philadelphia, PA '97-'99 by MG". Track C1: "(from What's Up Matador Comp)". Track C2: "(from Everything is Nice Comp)". Track D1: "(from Bardo Pond/Mogwai split 10")". Track D2: "(from Bardo Pond/Mogwai split 10")". Rear photo taken "@ The Cooler NYC 12/8/94".

 

A1. Olive Skin
A2. Tapir Dub
A3. Son Of Dispersion
B1. Anadamide (Complete)
B2. Shadow Puppet
B3. The Division Of Nature
C1. The Trail
C2. Long Ride
D1. Despite The Roar (In Spite Of Themselves)
D2. Highlands

 

Barcode and Other Identifiers:

Barcode 191401177917
Matrix / Runout OLE1779LP 283558E1/B
Matrix / Runout OLE1779LP 283558E2/A
Matrix / Runout OLE1779LP 283558E3/A
Matrix / Runout OLE1779LP 283558E4/C

 

Recorded At Studio Red (2)
Recorded At Cycle Sounds
Recorded At Lemur House
Copyright (c) Bardo Pond
Pressed By GZ Media

Data provided by Discogs
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SKU: 2473329874

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4.1 ★★★★★
Based on 26 reviews
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Product Reviews
J
Jiewen Wang
Natrona Heights, 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
West Palm Beach, 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
Draper, 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
Phoenix, 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
V
Vineeth Sai
Draper, US
★★★★★ 5
Great foundation read for security!
Format: Paperback
This book is a great read! It builds a strong foundation and I would highly recommend it for builders who are interetsed in building on LLMs and ensuring everything is secure. Security is super important and this book does it justice!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 27, 2025

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