Preparing a book for publication on Solr&Lucene. What do you think about publishing such a translation on Amazon? 🙂
The book is about algorithms and under-the-hood engineering. I haven’t seen books from this angle yet, maybe someone will find it interesting.
Microsoft has one very nasty thing with Outlook for MacOS, which for some reason nobody tries to fix. If you have a meeting in 30 minutes, Outlook reminds you with a popup showing the upcoming meetings, where it “highlights” these meetings. Well, in my case, there’s no secret here, I could even share my screen during that time. But it would be nice if such notifications didn’t appear while screen sharing, especially while recording, because screen sharing goes through Teams, which is part of the same package as Outlook.
But what’s worse is something else. If you try to CLOSE this notification window while screen sharing on MacOS (especially if the recording is on), it causes the whole Outlook with all the emails there to pop up. And there might be things there that the viewers shouldn’t see. That is, by _closing_ the window, you suddenly reveal the titles of email messages. Which is completely unexpected (well, until you step on these rakes, then it’s not unexpected anymore).
Today I learned how scientific achievements fly under a pig’s tail when faced with reality.
There’s this thing called precision feeding in pig farming. The gist is: a pig has an RFID chip attached to its tag (actually to its ear), and when it wants to eat, it sticks the tag into the feeder – and a special sensor reads its data and dispenses exactly as much feed from the machine as it should, also recording in a database how much and when it was given. If the pig sticks its tag in too early, the feed machine won’t dispense any. The idea is to reduce feed costs, improve growth and health of the animals, and lessen environmental pollution (less uneaten feed).
It seems like a great idea. However, such a system doesn’t work where there are large populations – it only works in specialized productions with few pigs, where almost all are known by name.
Why doesn’t it work on a large scale?
Because pigs are very cunning and quickly adapt. One pig inserts a tag, and then the one higher in the hierarchy chases it away and eats what isn’t meant for it.
Whole classes of oppressed arise, whose role is to insert the tag so that the authorities can gorge themselves. In the end, chaos ensues and no precision is achieved.
This is how pigs oppose technological progress.
I read something interesting today. About fractals. If you take any three points that form a triangle, and then a fourth point anywhere, and subsequently throw a dice, the faces of which are assigned to the first three points. Next, you move from the current point towards the point corresponding to the result on the dice and place a new point halfway; this becomes the new current point. After many iterations, the points start to form the Sierpinski triangle – the one shown in the attached picture. Intuitively, you would think the triangle should be fully filled because it involves random movements in three directions from a randomly chosen point, but no. Moreover, it works even if the starting point is inside the future empty triangle (yes, a few points will disrupt the picture, but that’s it). If you start our experiment with five or six points instead of three, different shapes will form – see the attached picture. This graphical method is called the Chaos Game.
By the way, it may seem obvious, but in case you wondered — all the presented figures have zero area.
If you take two triangles and with a probability p move towards random vertices of the first, and with (1-p) towards random vertices of the second, you end up forming a Barnsley fern (picture №2).
I love such things because they seem like magic at first glance 🙂
(It’s a kind of problem from the same class as the synchronization of metronomes)
Bought myself an AI microphone that listens to everything around and provides summaries. Decided to test it once. With it, you can’t even watch reels with the mic turned off on your computer, because it tries to merge and summarize everything it hears 😉
“..The team methodically moved through complex comparisons, but unexpected phrases like ‘Watch the video back if you didn’t notice’ and ‘Don’t be a sucker’ created a quiet, almost poetic dissonance—as if the universe whispered ‘Let it be’ amid spreadsheets and sprint tickets….”
While working on a book, I realized what kind of product I’m missing. It’s an AI diagram generator based on textual descriptions.
The idea is that the master document for the diagram is text. This textual description can be (and should be) quite detailed, so the generated diagram exactly matches the author’s vision. The diagram itself is not edited. That is, it can be edited – moving circles around, but ideally, after making changes, the system should update the text, generating from which will result in what the user adjusted.
The result — the diagram — should correspond as closely as possible to the description. If it does not match the description because, for example, it’s impossible to make a triangle with three obtuse angles, the system should do its best and provide a verbal response about what didn’t work. The user can then modify the task so that the system complies and produces the diagram correctly.
But then we understand that the author might have randomly achieved something that they liked with their flawed text. And if regenerated, it might turn out differently, and not necessarily better. Therefore —
You could ask the system to generate a diagram description from the diagram, which, if inputted back into the diagram generator, would result exactly in what the description was generated from. Yes, this description would be more verbose and complex, but it would more reliably describe the result.
So, from this point, you are no longer working with the diagram. You are working with text. If a diagram is needed — you simply compile the text into a diagram and it turns out as needed. But you don’t even work directly with the text. You work with this diagram-description text through an LLM, asking it to add some block, and the text changes, but changes in a way that everything doesn’t suddenly shift.
The final diagram should be in an object form, from which raster (PNG) or vector (SVG, EPS) images can be created.
It would also be great if such a system could take existing diagrams or diagram templates so that it could borrow styles and existing conventions on how to display what.
So, these are my fantasies. If anyone has ideas on how to implement this — let’s discuss 🙂
With the purchase of a Tesla, there’s sudden interest like a fuel nozzle understanding that the tank is full. And a couple of other interesting findings on the topic.
There used to be an awkward problem at gas stations. Customers didn’t know when their tank was full and gasoline often spilled over. Engineers came up with a genius solution.
Inside the fueling nozzle, there’s a thin tube that pulls air from the car’s tank into a special membrane chamber (if you look at the “nozzle,” there will be two holes) When you press the trigger, fuel flows until the tube is submerged in gasoline (which means a full tank) and the air flow stops.
This creates a vacuum, which pulls three little steel flaps into the center of the mechanism, instantly releasing the trigger and cutting off the fuel supply.
By the way, approaching the diaphragm valve in the channel there is a compartment with a small ball inside. If for some reason the fuel nozzle falls out of the tank, the ball will block the vacuum channel, provoking a sharp increase in vacuum – and triggering the process described above.
It also turned out that the diesel nozzle is larger in size so it cannot be mistakenly inserted into a gasoline tank. But the opposite mistake can happen. Although they could have invented a different design that would work both ways from the start.
When a tanker refills an underground reservoir, the valve automatically closes when the tank is nearly full, and the gasoline vapors are sucked back into the tanker through another hose, where it condenses back into liquid fuel.
And it also turned out that if you drive away with the hose still in your car, there will be no fireballs, spilled fuel, or toppled gas pump. The hose connecting the nozzle to the pump is designed to disconnect into two parts when a certain force is applied. Next time you are at the gas station, pay attention to the metal connector on the hose. That is the break point. When the hose disconnects and you drive away, the area of the hose breaks, built-in valves in the hose cut off the fuel, but, of course, the pump will not operate for some time until everything is put back to normal again. Interestingly, this risk is considered and damage is minimized.
Oh, and here’s something for those who haven’t driven in New Jersey. By law, it’s prohibited to refuel your own vehicle. At all gas stations, there are attendants who do it for you.
An interesting trick. To color the circle dark purple, you simply need to look at it and it will instantly change color. However, to revert it back, you just need to stop looking at it, and it will return to its original appearance (though you’re likely to look at another circle instead)
I decided a while ago to write a book on recommendation algorithms. With mathematics, code examples, a repository, etc. English, of course.
Accordingly, I am looking for volunteer reviewers who are knowledgeable in the field. Also those who have experience with print-on-demand on Amazon.
There’s already about 200 pages of content. About three months of work left. Working title Recommender Algorithms in 2026: A Practitioner’s Guide. Roughly half of it is still in draft form, with the first 80 pages about 80% complete.
I’ve built a mechanism to publish in HTML and PDF simultaneously. The HTML version is fully functional, with navigation. The navigation block reflects the current section, and as you scroll, it shifts to the one in front of the reader. Clicking on a section, of course, teleports you to what you clicked on. It’s all completely automatic.
So far, I have only one car model and brand that can deploy airbags not at the moment of impact, but a moment earlier, so that by the time of the impact, it’s not too late to do so. We’ll see what the news shows, but tests indicate that this thing works better than the traditional method. Reality might turn out to be harsher, but we’ll keep an eye on it.
It’s also interesting that the car started to receive new exciting features after purchase. I never had this experience before. What you bought it with, you lived with, and sometimes you could go to the dealership for something new, and it usually involved replacing something physical.
The previous update (not very useful to me, but maybe to someone) was about automatic detection of children and animals in the cabin. And if it turns out they were left inside while the owner left, the car does not turn off the climate control. And of course, it screams into the app that this is not a good thing to do.
Hi, I'm Rauf Aliev. 