I've been asked about this a lot, so let me provide a quick FAQ.
Q: What's the nature of the issue?
A: Anyone who has bought my book from Amazon in the past few month hasn't bought a genuine copy, but a lower-quality counterfeit copy printed by various fraudulent sellers.
A: Amazon lets any seller claim that they have inventory for a given book, and then proceeds to route orders (from the book's page) to that seller's inventory. In this case, Amazon even hosts the inventory and takes care of the shipping. (cont.)
(cont.) This has given rise to a cottage industry of fraudsters who "clone" books (which is easy when the PDF is readily available: you just need to contract a printer) and then claim to be selling real copies.
This is endemic for all popular textbooks on Amazon.
Q: How do I know if I'm about to buy a counterfeit copy?
A: Look for the name of the seller. If it's a 3rd party seller (i.e. not Amazon's own inventory) and it isn't a well-known bookstore, then it's a scammer. (cont.)
(cont.) They tend to have names like "Sacred Gamez", "Your Toy Mart", etc. That's because they started out with counterfeit toys, video games, etc. and eventually pivoted to technical books (higher-margin).
They've been in activity for years -- it's a highly lucrative model.
Q: How do I know if my copy is counterfeit?
A: The surest way to check is to try to register it with Manning at: manning.com/freebook
Other than that, the fakes have much lower print/make quality.
A: Nothing. We've notified them multiple times, nothing happened. The fraudulent sellers have been in activity for years.
The issue affects ~100% of Amazon sales of the book since March or April. That's because, amazingly, since fraudsters are claiming to have inventory, Amazon has stopped carrying its own inventory for the book (i.e. it has stopped ordering new copies from the publisher).
Q: Does this affect any other book?
A: Absolutely. It affects nearly all high sale volume technical books on Amazon. If you've bought a technical book on Amazon recently there's a >50% chance it's a fake.
E.g. @aureliengeron's book is also heavily affected, etc.
Besides books, it also affects a vast number of items across every product category -- vitamins, toys, video games, brand name electronics, brand name clothes, etc. But that's another story.
Q: What should I do if I already bought a counterfeit copy?
A: Ask for a refund. Maybe this will put pressure on Amazon to look into the issue?
An update: this thread has caused more of a stir than I expected. A positive side effect is that the issue has been escalated and resolved by Amazon (at least in the case of my book). Thanks to all those involved!
Specifically, the default buying option for the 2nd edition of my book is now Amazon itself, rather than any third party seller.
For the 1st edition, the default option is still a counterfeit seller, though. Perhaps this widespread problem needs more than a special-case fix.
If it's impossible for Amazon to ensure the trustworthiness of 3rd party sellers, then perhaps there should be an option for publishers/authors to prevent any 3rd party seller from being listed as selling their book (esp. as the default option for people landing on the page).
It may not be entirely obvious at first that a given seller is selling exclusively counterfeit items, because that seller may appear to have thousands of ratings, 99% positive.
An important reason why is that Amazon takes down negative reviews related to counterfeits.
I spoke way too soon when I said the problem was resolved for my book -- 24 hours later a fraudulent seller is now back as the default buying option for both editions of my book. Sigh...
This goes far beyond "a 3rd party seller on Amazon is selling counterfeit copies."
The gist of the issue is for many bestselling books, Amazon is routing people towards counterfeits *by default*. Which is a big deal because Amazon is the default online bookstore for most people.
If someone wants to buy my book or @aureliengeron's book (etc.), they will search for it on Amazon, find the book's official page, and click "buy".
And Amazon will be routing this purchase intent *by default* towards a seller of counterfeits.
This is hijacking a large fraction of total book sales -- for some books, a majority. This is theft of purchase intent (and that purchase intent typically originates outside of Amazon).
For authors and publishers, this represents a massive loss of revenue.
To use a metaphor -- it's not as if some guy on the street were selling bootleg items next to a massive supermarket that sold genuine ones.
It's as if this guy were empowered by the supermarket to systematically replace the genuine items on the shelves with his own fakes.
An update -- it has been nearly 5 days (and over 2M views) since I posted this thread. I regret to say that both editions of my book are *still* being sold by fraudulent sellers by default (new ones, though).
Do NOT buy my books on Amazon. Buy from the publisher directly.
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I'm joining forces with @mikeknoop to start Ndea (@ndeainc), a new AI lab.
Our focus: deep learning-guided program synthesis. We're betting on a different path to build AI capable of true invention, adaptation, and innovation.
We're really excited about our current research direction. We believe we have a small but real chance of achieving a breakthrough -- creating AI that can learn at least as efficiently as people, and that can keep improving over time with no bottlenecks in sight.
People scaled LLMs by ~10,000x from 2019 to 2024, and their scores on ARC stayed near 0 (e.g. GPT-4o at ~5%). Meanwhile a very crude program search approach could score >20% with hardly any compute.
Then OpenAI started adding test-time CoT search. ARC scores immediately shot up.
It's not about scale. It's about working on the right ideas.
Like deep-learning guided CoT synthesis or program synthesis. Via search.
Today OpenAI announced o3, its next-gen reasoning model. We've worked with OpenAI to test it on ARC-AGI, and we believe it represents a significant breakthrough in getting AI to adapt to novel tasks.
It scores 75.7% on the semi-private eval in low-compute mode (for $20 per task in compute ) and 87.5% in high-compute mode (thousands of $ per task). It's very expensive, but it's not just brute -- these capabilities are new territory and they demand serious scientific attention.
While the new model is very impressive and represents a big milestone on the way towards AGI, I don't believe this is AGI -- there's still a fair number of very easy ARC-AGI-1 tasks that o3 can't solve, and we have early indications that ARC-AGI-2 will remain extremely challenging for o3.
This shows that it's still feasible to create unsaturated, interesting benchmarks that are easy for humans, yet impossible for AI -- without involving specialist knowledge. We will have AGI when creating such evals becomes outright impossible.
When we develop AI systems that can actually reason, they will involve deep learning (as one of two major components, the other one being discrete search), and some people will say that this "proves" that DL can reason.
No, it will have proven the thesis that DL is not enough, and that we need to combine DL with discrete search.
From my DL textbook (1st edition), published in 2017. Seven years later, there is now overwhelming momentum towards this exact approach.
I find it especially obtuse when people point to progress on math benchmark as evidence of LLMs being AGI, given that all of this progress has been driven by methods that leverage discrete search. The empirical data is completely vindicating that DL in general, and LLMs in particular, can't do math on their own, and that we need discrete search.
In the last Trump administration, legal, high-skilled immigration was cut by ~30% before Covid, then by 100% after Covid (which was definitely a choice: a number of countries kept issuing residency permits and visas). However illegal immigrant inflows did not go down (they've been stable since the mid-2000s).
If you're a scientist or engineer applying for a green card, you're probably keenly aware that your chances of eventually obtaining it are highly dependent on the election. What you may not know is that, if you're a naturalized citizen, your US passport is also at stake
The last Trump administration launched a "denaturalization task force" aiming at taking away US citizenship from as many naturalized citizens as possible, with an eventual target of 7M (about one third of all naturalized citizens). Thankfully, they ran into a little problem: the courts.
When we say deep learning models operate via memorization, the claim isn't that they work like literal lookup tables, only being able to make sense of points that are exactly part of their training data. No one has claimed that -- it wouldn't even be true of linear regression.
Of course deep learning models can generalize to unseen data points -- they would be entirely useless if they couldn't. The claim is that they perform *local generalization*: generalization to known unknowns, to degrees of variability for which you can provide a dense sampling at training time.
If you take a problem that is known to be solvable by expert humans via pure pattern recognition (say, spotting the top move on a chess board) and that has been known to be solvable via convnets as far back as 2016, and you train a model on ~5B chess positions across ~10M games, and you find that the model can solve the problem at the level of a human expert, that isn't an example of out-of-distribution generalization. That is an example of local generalization -- precisely the thing you expect deep learning to be able to do.