Category: Mindset

Understanding the Fear of Leaving Appliances On | August 13 2026, 00:51

I recently started wondering, why are we so afraid of leaving the gas or the iron on? I’m afraid too, but I’ve been thinking about why. Because look, nothing happens on its own – the gas would burn for a month, and the iron would heat the air for the same month and use electricity. Until what? The iron theoretically could burn out as its lifespan is exhausted. Then it would just switch off. It cannot explode or burst into open flames – irons are not like that anymore. Gas – what could happen with it? The flame won’t just blow out by itself. Draughts are not typical in our enclosed spaces, but even if they were, it would take a very strong gust of wind to completely extinguish the flame.

Gas burns, producing carbon dioxide and water vapor — that is if combustion is complete. Well, let’s assume it’s not complete, but in the worst case, a small amount of carbon monoxide will accumulate. That’s not good, but remember, we left the gas on at home and went out.

The only scary scenario is if we forgot a pot of soup on the stove, which theoretically could spill over and then there would be methane release and a potential explosion (Interestingly, in Europe many gas stoves are equipped with a thermocouple flame failure device and turn off the gas if there’s no heat (i.e., spillover). That’s not yet common practice here.)

The alarm here is not an irrational failure but a perfectly rational reaction to the risk structure: the probability is low, but the outcome could be catastrophic and irreversible (fire, explosion, risking lives in neighboring apartments). When the expected damage is enormous even with a low probability, it is evolutionarily and culturally advantageous to be overcautious. But technically (ideally) leaving the iron or gas on shouldn’t result in any mishaps for those hours until you remember about them. And we worry not about the iron that’s left on, but about not being able to check whether it was turned off. The brain honestly signals no data and the stakes are high” — and with the cost of checking it taking thirty seconds versus the cost of a mistake costing an apartment, this is a mathematically flawless alarm

Engineering Zen: A Daily Dose of Science and Creativity | June 19 2026, 03:28

Due to numerous requests, I have created a Facebook group and a Telegram channel “Engineering Zen”, where I can write about all kinds of interesting things related to science and engineering every day, and guests can write too. I’ll find it interesting if we gather at least 50 people. Shall we gather? I have a ton of interesting content, enough for a year for sure.

https://www.facebook.com/groups/4344370099148010

I will also write on Telegram if we gather at least 50 members there. The channel is called @engineersdzen.

I will be happy for the shares and likes. If we don’t gather enough people, I will drop this activity with groups and channels, which I’ve been planning to do for ten years anyway 🙂

Mastering Cross-Posting: From Facebook Frustrations to Dual Blogging Excellence | May 23 2026, 14:28

I have perfected the cross-posting from Facebook to my two blog sites [which almost no one visits] – beinginamerica.com and raufaliev.com. When a new post is published on Facebook, a mechanism is triggered to translate the post into English, process attached images, generate descriptions for them, create a title based on the text of the post and descriptions of the images, generate tags from the same basis, record the post in turso db – this is a cloud database, free up to certain limits, create embeddings via openai, record in qdrant cloud – this is also a cloud database, but vector-based, and finally, upload images to wordpress via API, and publish the post in English and Russian via API.

All would be well, but of all the APIs, the silliest one is Facebook’s. Firstly, for pages like mine, transitioned to New Experience, it’s almost impossible to use most of this API. Well, it’s possible, but you have to spend a long time proving to Facebook that you really need it, by showing startup documents, demonstrating the application, etc. Obviously, they are reluctant to deal with something that takes content out of their system. In addition, the token that gives access to the latest messages is relatively short-lived (possibly a few weeks), and it needs to be obtained anew through a browser only. So, any automation requires regular attention, otherwise it breaks.

If you mess up and don’t offload the latest posts through this Facebook Graph API in time, they just disappear from the list of recent ones and that’s it, no more API access to them. The only way is to request an archive download from Facebook. This download is also rather silly – it requires a lot of transformations and removing unnecessary stuff. For example, in the file containing posts, which I process, for some reason there are links that I sent in comments without accompanying text. And the comments are in a separate file!

To assign tags, I had to solve a separate challenge. Here’s the thing: there are about 10,000 posts over all time. That’s a big chunk, and you can’t build tags from it because it doesn’t fit into the contextual window of the LLM. But you need to. So, I did this: a script takes random posts from the 10,000 in such a volume that their total size is just below the specified limit in tokens, and at the end of this block, it adds the prompt “generate the most common tags for me, 30 pieces” (I simplify the prompt used). In the end, I ran this 10 times and got 10 sets of tags with 30 pieces each, generated for different slices of the database. That made 300 tags, some of which are complete duplicates, while others are synonyms and closely related in meaning. All this is fed into the LLM, and we get a list of tags and a hierarchy of tags. Now we have a limited set of tags that reflect the 10,000 posts as closely as possible. Turns out, that in almost 20 years on Facebook, my breakdown is as follows:

Tag Posts

==================================================

#Russia 3412

#Thoughts 3146

#Tech 3105

#Culture 2765

#Hobbies 2726

#AI 1603

#Science 1367

#Software 1358

#Travel 1298

#Learning 1138

#Society 1050

#Nature 958

#Education 915

#Business 902

#Art 894

#Programming 889

#Humor 840

#History 807

#Gadgets 750

#Moscow 713

#USA 614

#Cinema 567

#Webdev 493

#Music 476

#Sports 473

#Mindset 443

#Auto 400

#Books 386

…

and so on. This list includes both tags from the limited list and tags that the LLM appointed to content simply because it didn’t find anything suitable in the limited one.

Tags from the limited list became categories on the site. The rest of the tags + these just became regular wordpress tags.

As for image search. I had two ideas on how to do it. The first – OpenCLIP. It’s pretty straightforward but requires hosting the model somewhere. Easy on my machine, but inconvenient to start it each time, plus I planned to move the migrator to a cheap server on Amazon. It’s also okay to calculate in cloud models, but you have to pay a bit, which is yet another dependency. But the main thing – it works quite well without it. I generate descriptions for images using OpenAI, which is used for translating into English anyway, and then create embeddings using a large model. So far, all search tests are a great success. Especially when there’s text on the image, and it’s a big question whether OpenCLIP would have interpreted it successfully.

In the end:

1) wordpress raufaliev.com – free

2) wordpress beinginamerica.com – free

3) turso db where all posts are stored – free

4) qdrant cloud where embeddings are stored – free

5) openai for translation and image descriptions – not free, but inexpensive (cost $30 for post processing over a year).

I attach two screenshots – how the search by images works, and by texts, as well as the migrator dashboard.

Peripheral Vision: Unveiling Optical Illusions in News Apps | April 29 2026, 17:56

I’m trying to figure out if it’s just me or do other people experience this too 🙂 if you look anywhere except at the word “Omurbekova”, the line highlighted in red in the second screenshot (which is actually white) is distinctly visible in your peripheral vision. But as soon as you shift your gaze directly to it, the line disappears. That is, it’s only visible peripherally. Share your experiences 🙂

Colorful Climbing: A Fun Indoor Adventure with Masha | April 27 2026, 15:03

Went to the mountains with Masha. Yellow paths over yellow, red over red. The organizers should put a box of candies at the top. Found out that the muscles in my fingers are non-existent, and the rest hurt the next day. Cool experience (not the first time)

Yuki’s Mysterious Bi-Annual Behavior Shifts | April 09 2026, 14:31

Yuki’s “ooooh” mode is activated again (April 7, 2026). It usually lasts a few days in April and October.

Previous occurrences were –

– October 15-20, 2025

– April 11, 2025

– April 1-4, 2024

– February 2, 2023,

– October 27, 2022,

– March 15, 2022

Behavior changes during this period include:

1) He might sing songs for hours on end. For instance, at six in the morning.

2) Suddenly, he likes to go for walks. Usually, he does not. Even though he always has access to the yard, he specifically needs to go on a walk. He might go to the door and knock on it with his paw. Usually, at the word “walk,” he rushes to the third floor.

Now, he looks into your mouth when you’re talking to him. Always seems to be waiting for something, possibly expecting the question of whether he wants to go for a walk. He knocks on the window and the front door with his paw.

And yes, he starts wanting to walk at around six in the morning, and then again soon after returning from a walk.

3) On the walk, he sticks his nose in the grass every five minutes, and it’s hard to pull him away. Usually, this is rare, but now it’s constant.

4) He might sit and watch the sunset for half an hour.

5) Unstable appetite, occasionally. You put meat on top of his food, and he doesn’t even look at it.