Exploring the World of Whistled Languages: From Silbo Gomero to the Peaks of Human Ingenuity | October 18 2026, 16:03

I learned that there is a language entirely based on whistling. Google Silbo Gomero. It’s a whistling language on the Canary Islands, a whistling dialect of Spanish. Quite a few residents there can communicate in it. A speaker of Silbo Gomero is called a ‘silbador’ (whistler). In 2009, the language was included in the List of the Intangible Cultural Heritage of Humanity. There are many videos about it on YouTube.

I started thinking about how humanity is rapidly losing the skill of whistling. Some can still whistle with their lips pursed, but with all other methods, it seems, no one can.

Apart from that, there is the palatal whistle (search for palatal whistle, roof of mouth whistle) — sharper and more piercing than the lip whistle, better at cutting through noise, but almost no change in pitch. There is also the rolled tongue whistle (search for rolled tongue whistle, taco tongue whistle) — low, dull, sounds like an owl, but reportedly, not everyone can do it (maybe genetics). With fingers in the mouth — louder (wash your hands!). Two fingers of one hand (index + middle or thumb + index ‘ring’) — 100-115 dB, up to 1 km in silence. This is precisely the basis of Silbo Gomero — pitch is adjusted by lip positioning and how deep the fingers are inserted, so much can be encoded. One finger (index or pinky hooked) — almost the same loudness, the other hand free. Fingers of both hands (one or two from each side) — the loudest manual whistle, up to 120 dB, across a valley 2-3 km in the mountains. Thumbs of both hands (nails to tongue) — loud, somewhat low, a tradition of shepherds in the Pyrenees, Caucasus, Balkans.

There’s also the whistle with cupped hands — low, 300-600 Hz, audible at 100-300 m, but the low sound bends around trees and bushes, so in the woods it travels further than a high sound. Pitch is changed by slightly opening the fingers, allowing for 5-8 notes to be whistled.

Exploring Undocumented Features of FlexibleSearch on SAP Commerce Cloud | October 14 2026, 12:50

Published a new article on Hybrismart about undocumented features of FlexibleSearch (SAP Commerce Cloud / Hybris). Relevant if you work with this platform in any way. If not — feel free to send it to those who do 🙂

I now publish articles in three languages – RU, ENG, UKR. Of course, the Russian and Ukrainian are automatic translations from English. But many prefer reading in their native language.

https://hybrismart.com/2026/10/13/flexiblesearch-2026-rus/

https://hybrismart.com/2026/10/13/flexiblesearch-2026-rus/

Smart Bed: The Ultimate Sleep Assistant with a Voice | October 13 2026, 17:45

Interesting, what if you were to embed a voice assistant into a bed? To listen nonstop and to respond. Usually, during the day, there’s no one in the bedroom anyway. You would just need to customize it to read audiobooks and to stop itself if it seems the owner has fallen asleep.

And oh, how cool that would be. You lie down, it’s three in the morning, not a wink of sleep. You sigh heavily, turn over to the other side, and then in the silence from under the bed a muted, velvety baritone voice emerges:

— Another existential crisis, Oleg?

“Understandable,” — the mattress vibrates empathetically. — “Want me to tell you a fairy tale? Or perhaps, delve into the brutal world of badminton? I’ve downloaded an article on how Chinese maidens pluck rare geese for feather shuttlecocks. There’s more intrigue there than in ‘Game of Thrones.’ A goose named Gao…”

No, let’s talk about neural networks, you say.

“Oh yes… listen to this, my sweet data scientist… JEPA architecture doesn’t try to reconstruct pixels… it’s too good for that… it predicts only abstract features in the hidden space… And then there’s Dreamer…” — the bed might make a theatrical pause here and slightly rebound. — Dreamer builds a whole model of the world… it generates imaginary trajectories, Oleg… run your hand over the mattress pad, and I’ll tell you about Markov decision processes…”

Would be a cool thing indeed

Navigating DIY E-Scooter Repairs in the U.S. | October 12 2026, 17:43

In the USA, scooter repair services are pretty bad. I had to do everything myself. But before that, I did a lot of searching. I called various e-bike service stores, asking around. Something like adjusting the brakes—that can be done anywhere. But when it comes to dealing with the electronics, no one wants to touch it. Meanwhile, most scooters are very simple on the inside. I speak from experience, because I have another one in the garage just for scraps; I tried fixing it, gave up, and bought a new one.

Overall, electric bikes have similar internals. But since there are many brands (all Chinese), you have to order parts and wait for weeks, involving people with high hourly rates, and often it’s just not economically sensible to repair. But sometimes it is worthwhile, yet there’s no market—apparently, there’s not enough volume, or people don’t bother and just go buy a new one.

My scooter costs around $1000. The repair cost me $30. I bought a new fuse holder and put in a new 40A fuse. The previous 40A fuse melted along with the fuse holder. Initially, I thought there was a short somewhere, but no, it’s actually drawing currents up to 25A, and it seems they heat up the holder, which for some reason is rated for lower currents. Since there’s nowhere for the heat to dissipate, it melts. Structurally, any scooter consists of a battery + motor controller(s) + on-board computer combined with a display, and wheels with an internal motor. So, if there’s a non-mechanical breakdown, you simply need to replace one of these four components, which are all available for purchase.

Unveiling BloomSpan: Revolutionizing Text Sequence Analysis in Large Datasets | October 12 2026, 04:10

I want to share our fresh work — the BloomSpan algorithm for finding the longest frequent sequences of words in an array of texts. I named it BloomSpan.

What is it, in human terms. Imagine you have a library of 50,000 books, and you need to find all the long phrases that are repeated word for word, without omissions, in many different books. Not “similar” phrases, but exactly identical chains of words, and as long as possible — such that if you add another word to the left or right, the phrase no longer occurs frequently enough. The task sounds simple, but with billions of words, it stumbles on memory and time. Classic algorithms either build huge indexes or go through too many candidates.

Where is it needed? For example, extracting patterns from documents (such as uniform “headers” in letters or contracts), searching for borrowings and plagiarism, highlighting stable phrases and clichés in large text arrays.

So, here’s what we got. The algorithm. Honestly, BloomSpan is not exactly an algorithm from scratch but a careful assembly of known ideas which, when combined, have a strong effect. At its core – different ideas from BIDE+, FHK, and on top of that: (a) The Bloom filter — a compact structure that answers the question “has this combination of words occurred frequently enough?”, without storing the combinations themselves. It can occasionally make a mistake in the direction of “yes”, but never in the direction of “no”, ensuring we never miss a phrase we need (b) “Depth-first” search directly through the text — we find a short frequent core and gradually expand it into a long phrase, without creating intermediate copies of the corpus. (c) An occupancy map — marking positions in the text already “covered” by found phrases, to avoid checking the same thing many times.

The results. On the Gutenberg Project corpus of 50,000 books (about 3 billion words), BloomSpan operates 11-15 times faster than the classic FHK algorithm and consumes up to twice as little memory. It is the only tested method that manages to complete the entire corpus within 40 GB. Moreover, where they do finish, the results fully match those of the precise algorithms — meaning the speedup does not compromise quality.

On synthetic data with an “unnatural” distribution of words, good old FHK is faster. BloomSpan is specifically tailored for living natural language, and the article discusses why this is so.

The preprint and code (Java) — in the comments

Navigating Google’s Multi-Account Maze | October 11 2026, 04:47

It seems like Google is a powerful, smart company, but if you’re logged into multiple accounts 1) you cannot log out of just one, you have to log out from all of them 2) there’s no other way to change the default one (the one that opens when you log into Gmail, for example) from the first logged-in one to another, except by logging out of all accounts and logging back into the right one first (followed by the others).