Tag: books

Navigating the Lexical Complexity of Nabokov’s “Lolita” | April 02 2026, 15:56

I’ve finished the first version of a dictionary-style book on Nabokov’s “Lolita”. The chart shows how the complexity of vocabulary is distributed across the pages of the book. The lower chart averages 25 sentences, displaying the number of complex words on the vertical axis, with colors indicating their complexity/rarity (purple – the most complex, red – less complex, yellow – even less so). But I have already removed two levels, and overall, for a foreigner, all five levels are challenging. In the book, level 3 is marked with a dashed line, level 4 with a simple frame, and level 5 with a double frame. Currently, there are 5794 words, of which 541 are fifth level, 1070 are fourth, 1883 are third, 1393 are second, and 54 are first (the simplest ones). Considering that the first version ended up being 1148 pages, the dictionary will need to be significantly streamlined by removing what can be dispensed with. This mainly pertains to the first and second levels, and some from the third and fourth. The rarity of words is calculated in three ways: through LLM, and through two lists of word frequencies in the English language corpus (300K words).

Not all words are complex. For instance, in the sentence “With the ebb of lust, an ashen sense of awfulness, abetted by the realistic drabness of a gray neuralgic day, crept over me and hummed within my temples.” someone well-acquainted with English might not know the words ebb, abet, drabness, while everything else is familiar, but lower the requirements for the reader, and the dictionary might not be very useful for such cases.

Or consider the sentence:

Homo pollex of science, with all its many sub-species and forms; the modest soldier, spic and span, quietly waiting, quietly conscious of khaki’s viatric appeal; the schoolboy wishing to go two blocks; the killer wishing to go two thousand miles; the mysterious, nervous, elderly gent, with brand-new suitcase and clipped mustache; a trio of optimistic Mexicans; the college student displaying the grime of vacational outdoor work as proudly as the name of the famous college arching across the front of his sweatshirt; the desperate lady whose battery has just died on her; the clean-cut, glossy-haired, shifty-eyed, white-faced young beasts in loud shirts and coats, vigorously, almost priapically thrusting out tense thumbs to tempt lone women or sadsack salesmen with fancy cravings.

My browser even highlights four words here.

I have definitions of words in English, German, French, and Russian. I’ve encountered the issue that different words from the text are considered complex in different languages, yet they are unified for me. So, I’ll have to mark, for example, French words in the English text separately, so they are not included in the French version, since there, the reader knows, for instance, what quel mot means.

Overall, this weekend I’ll be manually removing about half, and then I can make the cover and list it on Amazon.

Exploring the Multifaceted Uses of “Oblong” in English and Russian | March 17 2026, 13:50

Sometimes in English, there are very unusual words that are very difficult to translate into Russian. Here, for example, is the word oblong. As an adjective, it translates as “elongated, oblong,” but in the book, both uses are nouns. Often oblong refers to a face – that is, close to an oval, but oblong is a broader concept that describes any figure having an elongated appearance. My mom bought an oblong tablecloth for her new table.

As a noun, it is also used, and quite frequently (though less so than as an adjective). As a noun, oblong means “a rectangular object or flat figure with unequal adjacent sides.” Rulers are considered elongated items (oblongs). Laptops, tablets, and flat-screen TVs are oblongs of different sizes. A rectangle can be defined as oblong; however, not all elongated figures are rectangles. The same face, for example. Additionally, in mathematics, an oblong number is what in Russian is called a rectangular number (the product of two consecutive numbers. For example, 12). In general, it’s utterly baffling.

The word has been alive since the 15th century, by the way. So, in my book, it appears twice, and both times as nouns. In the first case, Nabokov translated it as “corner,” and in the second – “a small oblong of smooth silver” as “a little piece.”

Exploring Multilingual Vocabulary in Nabokov’s Works with Apple Books | March 15 2026, 23:20

Man, it’s really convenient. Just sitting here reading.

The usage pattern is as follows: I hold the phone in my hands. There, in apple books, this and that book. You see an unfamiliar word – it will likely be in the word list of the chapter. The definition takes into account the translation by Nabokov himself. Then you look a couple words ahead, put the phone down, continue reading. You encounter those words, and they are still in your short-term memory, and hooray, you understand. During a break, you load the next couple of words into your brain. You have to hold the phone and flip through, each page contains 4-5 definitions.

Now, every word has definitions in English (interpretation), French, and German. Consequently, I can publish four books.

Overall, my level of English matches what my app predicts about which words will be challenging. But someday I’ll need the same for French, and it will require an assessment of the difficulty level for each word because even some basic words will be unclear to me. I’m not sure that a book with basic words will be handy. With rare ones – definitely handy.

Crafting Nabokov’s Dictionary: A Multilingual Lexical Journey | March 15 2026, 18:30

I’m reading Nabokov and decided to take a break to create a convenient app “Nabokov’s Dictionary” and am considering selling it on Amazon as a book. Essentially, it looks like this (see screenshot) – definitions of complex words in English, Russian, German, and French, in the same order they appear in the original book.

Would you buy such a book?

To accurately make their definitions, I also wrote an aligner – a program that matches sentences and paragraphs in English with their translations (Nabokovian) into Russian. And when a word’s definition is created, it uses not only the knowledge of LLM but also the Russian translation by the author. It’s worth separately discussing how the algorithm works (I invented it myself because everything I found online did not work as I needed). It first finds long sentences and matches the longest sentences with their pair through cosine similarity of embedding vectors created through the multilingual e5 model. These sentences become anchors. Then, assuming that for long sentences the error is almost excluded, the longest sentence between anchors is found, and everything repeats recursively. There are many situations where a sentence in Russian has no equivalent in English and vice versa, where a sentence is split into two, or conversely two are merged into one. The algorithm handles this as best as it can. The result is quite a good quality of alignment. To such an extent, that errors in alignment can hardly be found (but they are likely still there). Either way, it is only needed for the context for translating words, even if there are rare errors, it’s not a big deal.

Would you buy such a book?

Gravitational Mastery: Semikhatov’s Cinematic Triumph | March 09 2026, 14:56

Semikhatov’s movie about gravity turned out to be really cool. Of course, it’s quite popular, but understandably so – they didn’t want to scare off the audience. It’s very cool and professionally made.

I have Semikhatov’s book on my shelf (“Everything That Moves”). It’s also popular, but it’s a bit more serious in its presentation, at times with formulas and loaded with illustrations. Later, my opinion of him slightly soured due to his specific way of conducting podcasts, constantly interrupting guests and answering his own questions in a way that outshines the guest demonstratively. But in the movie, he looks absolutely great. I recommend it.

The link is in the first comment.

The Lasting Legacy of Heaven’s Gate: A Cult’s Continuing Online Presence | February 28 2026, 04:09

Remember the American cult that had 39 members simultaneously self-extinguish in a mansion near San Diego, believing that they would be picked up by aliens? Well, their website is still up and running. The earliest version of this site from 1999 is virtually indistinguishable from what’s on the site now. The only difference is the ® symbol, which was after the name of the cult in 1999, but not now.

I Googled what’s up with their trademark registration. Just recently, in 2020, the company “The Evolutionary Level Above Human Foundation” registered (or renewed) rights to this trademark. The category is indeed listed as Lace, Ribbons, Embroidery, Fancy Goods, but the name of the company leaves no doubt that they are thinking about aliens.

I Googled some more. Turns out, this foundation, The Evolutionary Level Above Human (TELAH), acts as the “guardian of the legacy of the group ‘Heaven’s Gate'”, and has sued Stephen Havel and other defendants for copyright and trademark infringements, accusing them of illegally distributing archival materials and selling themed merchandise. The last update shows the parties are obligated to hold a meeting by the end of March 2024 to try to negotiate confidentiality and authentication of evidence without further judicial intervention.

Specifically, the foundation consists of real people from Arizona, Mark and Sara King, and the organization is registered as a corporation. They respond to emails and send out books and cassettes if you transfer them money.

Other former members are trying to challenge their “right” to use cult materials, such as recordings on tapes in court.

In short, some kind of life goes on there.

That is, the next time you think of Flat Earthers as “some pranksters pretending to be weirdos”, remember these folks, maintaining their website and selling books by their “prophets”.

My Ambitious 2026 Plan: From Galapagos Travel to Academic Achievements and Creative Pursuits | January 20 2026, 04:44

My plan for 2026:

– Travel to the Galápagos Islands, Ecuador for a week (summer)

– Finish and release a book on Information Retrieval (also summer, progressing slowly, first couple of chapters are already written. Already spent about 50-100 hours on this, the easy part)

– Release at least one scientific paper, probably on Data Mining (spring). Ideally, submit it somewhere to a journal (challenging). Already spent about 30 hours on this topic, a lot left to do.

– Make a step towards a PhD. Find professors, visit universities, understand the cost and assess my capabilities and resources.

– Continue studying fundamental mathematics and not die (linear algebra, calculus, probability theory, statistics, classical ML). In 2025, I spent about 200-400 hours on this topic.

– Continue studying Deep Learning and reach the “can teach” level. In 2025, I spent about 100-200 hours on this topic.

– Continue studying Data Mining/NLP.

– Update my book on RecSys, releasing version 2.0 with updates and corrections (autumn 2026)

– Make noticeable progress in painting and playing the piano. Specifically, learn Schubert’s serenade (Ständchen, D 889) completely and create at least one canvas that I wouldn’t be ashamed to give as a gift.

The Maddening Ambiguity of Mathematical Notation | December 02 2025, 15:30

If someone tells you that mathematics is an exact science, don’t believe them. Since I’m currently into data science as a hobby, I’m studying all sorts of things from different books and my brain is exploding at how this can happen in a science where every little detail should fit into a system, otherwise it goes by the wayside. Until it gets to notations. It’s a complete mess there. A set of dialects.

Take, for example, common logarithms. The “standard” for how to denote a logarithm depends on which room of the university you are in. In calculus and number theory, log(x) almost always means the natural logarithm ln(x) with base e. The derivative of e^x equals e^x. It’s “natural”. They’re too lazy to write ln. Yet, where decimal logarithms might appear (like in computer science), log(x) suddenly becomes decimal, and ln(x) is based on e.

The expected value E has an argument in square brackets. Meanwhile, the same square brackets in computer science are used for the step function 0/1.

Or if you see a vector – is it a column or a row? In classical mathematics, a vector is always a column. To multiply it by weights, we write T after the vector and then w for the weights. But in many papers, vectors are thought of as rows. And if you see y = xW+b, then x is not a column, because otherwise the dimensions wouldn’t match up. x here is a row. But in the next paper they write Wx+b. And there x is a column 🙂

Angle brackets . For the dot product, the symbol “⋅” is used, but it is hard to see, especially on a whiteboard, and I very often see that mathematicians use angle brackets for dot product. In general, angle brackets are used for the generalized concept of inner product, where the scalar product is a special case. signifies a certain abstract way to multiply a and b and get a number. Meanwhile, in quantum mechanics this would be written as . And for the scalar product, some use a circle with a dot or x in a circle.

And just for the sake of it, in Russia tangent is tg, while in the USA it’s tan. There’s also tan^-1 and arctan, which are the same, though x^-1 generally means 1/x

Rediscovering the 1986 “Chemical Trainer”: A Pioneer in Interactive Learning | November 23 2025, 15:55

At my home in Kolomna, I have a book called “Chemical Trainer” from 1986. I have never seen anything like it before or since.

The material of each of the 54 programs is divided into many small, very short sections, or categories. At the end of each category, one or more questions are posed. This is done to check whether the content of the category is truly understood. For each answer, there is a place in the book to jump to in order to see if the answer is correct. If the answer is wrong, it describes why and asks a new question. If correct — you move further in this quest.

These Germans in 1986 created an interactive textbook even before it became fashionable.

Data Science: The Modern Alchemy of the 21st Century | November 16 2025, 04:02

A cryptic post today. While writing a book on RecSys, I caught myself thinking that modern data science is essentially the alchemy of the 21st century. Half of the “best practices” in algorithms lack a solid mathematical framework. It’s a set of heuristics that “just work”. Much like in the 17th century where they mixed everything indiscriminately, it happens now, and if something works better, everyone else starts doing the same. There’s just no answer to the question “why”.

Take, for example, the NCF/NeuMF (Neural Collaborative Filtering) algorithm. The logic goes like this. Say, there are a million movie ratings by users. And 100 million ratings by users yet given – users can’t watch every movie in the world. But out of these 100 million, you need to choose candidates for advertising for a particular user. The algorithm, of course, has a training phase, where weights are calculated, and a prediction stage, where these weights are used on the incoming data.

(What the algorithm does. Essentially, it’s an ensemble of three sub-algorithms, two of which generate their own conclusions, and then their decisions go to a new neural network, the third algorithm, which provides the final recommendation. Smartly, it’s a hybrid of GMF (matrix factorization) and MLP (Multi-Layer Perceptron). The first of these two is based on matrix decomposition, and the second represents a neural network with multiple layers. Weights are adjusted on training data.)

For one positive example, it takes 4 negative ones. Why four? Just because it’s “not too many and not too few”. Would 8 be better? Unknown, but it would definitely take longer to learn.

Why are embedding dimensions 32? or 64? There’s no formula. It’s the “golden mean” between a “dumb” model (few k) and an “overtrained” (many k).

Now about the neural network. Why is the MLP block built as a “tower” (64 -> 32 -> 16)? Why not (50 -> 25 -> 10)? Why ReLU between them (and not tanh for example)? Pure empiricism. The number of layers in the tower is also adjusted.

Why do GMF and MLP parts have different embeddings at the input? Because the authors of the paper tried it, and it “worked out better”. No mathematical proof. Why do they go to the final layer with equal weights? Because they just do.

Why are the outputs of the two paths “concatenated” (concat), and not added or multiplied? “Experience showed that this way the result is more accurate.”

And so it is with everything, up to the choice of optimizer Adam or the “magical” learning_rate=0.001, although at least these have some mathematical basis.

That is, at least a dozen parameters of one algorithm are empirically chosen, with no clear confidence that they are independent of each other. But many of them depend on the dataset, but no one knows how 😉

In general, alchemy.