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Description
15″ 7mm Glass Beaker BongThe 15 7mm Glass Beaker Bong is built for performance and durability, offering smooth, powerful hits with a solid and reliable design. Featuring thick 7mm borosilicate glass, a wide 135mm beaker base, and a 5. 5 downstem, this bong is engineered for serious smokers who demand strength and smooth diffusion. Features: Height: inches Tube Thickness: 7mm heavy duty glass Base Diameter: 135mm wide beaker base Bowl: Thick glass bowl for 14mm female joint
The 15″ 7mm Glass Beaker Bong is built for performance and durability, offering smooth, powerful hits with a solid and reliable design. Featuring thick 7mm borosilicate glass, a wide 135mm beaker base, and a 5.5″ downstem, this bong is engineered for serious smokers who demand strength and smooth diffusion.
Features:
Height: inches
Tube Thickness: 7mm heavy-duty glass
Base Diameter: 135mm wide beaker base
Bowl: Thick glass bowl for 14mm female joint
Downstem: 5.5-inch removable downstem
Material: High-quality borosilicate glass
Available Colours: Green, Black, Amber, Teal and Blue
It Includes: 1× 15″ 7mm Glass Beaker Bong
1× Bowl
1× Downstem
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4.1 ★★★★★
Based on 798 reviews
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Product Reviews
★★★★★ 5
Hilarious and Informative
Format: Kindle
This book was a major hit with me - it had me in hysterics at several points while teaching me a lot about machine learning and neural networks on a deep level.
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Reviewed in the United States on April 5, 2026
★★★★★ 5
An adorable book
Format: Paperback
This is an adorable book. I bought it because I needed to know more about AI, and this exemplar seemed perfect to me. And it was.
I had already read several books on AI, dozens in fact, and let's say this is one of the best. First: the tone (the author is very nice); secondly, the drawings (always adding clarity), and thirdly, the scope (it covers all the main topics, including ethical and technological issues).
The problem with books on AI is that some authors begin to talk on AI in a very effective manner, but then, before you realize, they start pontificating on all the evils that it brings with it, and the perverse people behind the scene trying to kidnap your soul (or your money). Believe me, I tremble every time I read on AI because I know what possibly is going to happen after the first fifty pages. This is not the case. Janelle Shane goes to the point, shows you the magic, and the limits of this pervasive science, without painting the horror movie some others make you watch.
Highly recommended for all those interested in passing a couple of days of good reading on AI topics, learning on them, and enjoying a very entertaining author.
Five brilliant stars.
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Reviewed in the United States on October 13, 2023
★★★★★ 5
A fun, accessible introduction to how AI works...and how it sometimes doesn't!
Format: Hardcover
Still relevant despite recent advances in AI-generated imagery and text, because the new systems still work on the same principles as the ones that were around three years ago. They just have a lot more data and processing power. This also means they have the same limitations and blind spots. What was it trained on? *How* was it trained? (This is the most obvious way human bias can leak into an AI model.) How well is the goal specified? And of course, did the AI actually latch onto relevant details, or did it notice that all the training pictures labeled sheep had green fields and blue skies, and completely ignore the actual sheep?
These are things to keep in mind as we enter the landscape of generative AI tools like ChatGPT: You can train an LLM to write a book review, and it'll give you a great piece of text that *reads* like a book review -- but it's not going to have actually evaluated the book. For that, you'd have to train *another* AI to categorize books as good, bad, interesting, dull, and so on. But even that can only be as good as its training data. (I don't remember whether the classic phrase "garbage in, garbage out" is used anywhere in the book, but it still applies today!)
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Reviewed in the United States on April 1, 2023
★★★★★ 4
If you want a book on the details of AI without math and statistics, this is it
Format: Paperback
I had this book a year or two back and then sold a lot of books as they piled up. After that I read a good number of books on AI. Of those, Ethan Mollick's book Co-Intelligence is best for the user end. But then there was still the issue of how do they do it?
If you want to understand the process how AI works, there are a few books like this. Melanie Mitchell tends to focus on pictures. When you read ANY of these book, you will come to a page where you think "this makes no sense." You get there because the way AI chops up information and stores it in "cells" and then processes in stages (deep learining, hidden layers) is not how we think. They are not brains, though the neural network has some similarity to ours. You will simply need to finish the book. This one or the one you bought. Then read another one, if needed. It will make a lot of sense if you finish the book. Then you just generalize where you are at. I am never going to write Python or get deeply involved in tha manner. I am quite familiar with the free vesrions and I am able to check what summaries I get from AI. I will also keep up with the language part of it. AI does not study grammar the way we do. It looks for patterns in millions of examples.
I have since 2023 gone through most of the 20 dollar range books. This one is the best.
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Reviewed in the United States on April 1, 2026
★★★★★ 5
Great, funny intro to AI
Format: Hardcover
This is a wonderful, humorous introduction to AI that is a fast read packed full of examples. It makes a great gift for friends or family who don’t know much about the field, and I imagine it would be especially interesting to teens. I loved the way she used running jokes to make connections between themes. Shane is clearly on a mission to make AI more accessible.
It’s funny, someone else said they didn’t like this book because it wasn’t enough like Shane’s tear-inducingly-hilarious blog. But here’s the thing: I can read the blog for free! I was actually nervous that I was going to be getting a repeat of the blog in book form, but it was super different. If you’re a computer science scholar, maybe skip this one, but I don’t think that was the audience Shane was trying to reach.
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Reviewed in the United States on November 19, 2019