Category: Tech

Unexpected Perks: A Tale of Four Kettles and a Smart Ring | May 22 2026, 19:21

I ordered a Breville kettle. Costs a hundred bucks. Yes, I could have bought a similar one for 30, but I have all Breville products, plus a kettle is bought for several years. I come home – there’s a box up to my waist at the door. Not that surprised, because Amazon likes to put some little thing in the far corner of a huge box, it’s easier for them. But doubts increased after I couldn’t lift it with one hand. I bring it inside — and there are four kettles.

I open Amazon, check the order – everything’s correct, just one. Maybe they sell a 4-pack for 100 bucks? No, the description says one kettle. I contact support, a robot responds. I select the “brought extra items” option. The robot says “our fault, keep them”. Well, okay, now I have four kettles. Big family, one kettle for each.

Nadia has an Oura Ring 4. She says it has to be charged often. She says it used to last longer. I get in touch with support. A robot responds. I activate my own robot and ask it to draft a good letter to support. Their robot empathizes, says, “I’ll now connect to your ring and understand everything.” Connected, understood. Says, expect a new ring. Today, a plain envelope arrived with the ring inside. If it weren’t for FedEx it’d be easily lost in spam.

I love robots, almost got seven hundred bucks worth of goodies because of them. Well, good, at least the ring was a warranty case, although I expected to be dismissed with my battery complaints.

Well then, I asked the robot to make an illustration for the post.

Exploring Automated Documentation of Large Excel Datasets | May 06 2026, 22:28

I wonder if there exists an agent that takes an Excel table significantly larger than the context window and begins to document its essence. Here are several tabs. Here on tab 5, there is a table with a million rows and five columns. The columns are as follows. We take random data from the table, looks like there are numbers, and there – surnames. We assume that there are numbers everywhere – we write a code that checks this assumption and at the same time calculates min/max and a set of unique values. So, few values, only five. We record it. Now we check the surnames. Yes, these are just strings, new sampling showed that they are indeed surnames. Here’s a formula. We see where it points. And so on. And this column – unclear purpose. We look at the data – these are some numbers from 0 to 1. We measure the average and the spread. We ask the user – maybe they’ll provide some comments. They did. It turned out to be a KPI issued to this user from an external system. We record it. And so on. Documentation emerges. Later, when there is documentation, one can request to perform some operations with all this, since the LLM now more or less understands the purpose of the data and their connection, and can build some hypotheses on detecting outliers and verifying them.

The Crucial Role of Data Quality Oversight in Development Projects | May 06 2026, 16:07

Almost every development project features a dedicated functional testing automation team, yet surprisingly, a similar emphasis on Data Quality is rarely found. Regardless of whether data comes from external integrations, users, or is generated by the system itself, it often remains without proper control simply because no one seems to consider it important, and later they struggle with the consequences – they accumulate like a snowball. The longer such issues persist, the harder they are to resolve, eventually leading to a situation where people just resign themselves to the “irreparable” state of the database. It is much better to identify these problems at the moment they arise, while the technical debt has not yet become insurmountable, rather than later figuring out how to prevent them from causing everything to crash;

In essence, there needs to be a constant “supervisor” over all types of databases used by the system (relational, NoSQL, search indexes, or graph databases) — essentially, this is a layer of data quality checking over processes. Of course, there must be clear rules – specifically what to check and which flags to use to mark specific anomalies.

There must be a responsible party for the process (a human, not AI), who will integrate these reports into the development and support workflows. Many data integrity issues cannot just be resolved through an interface — they require the engineering team to develop scripts for mass correction and data cleansing.

Incidentally, this also transitions into the realm of anomaly detection (outlier detection). Machine learning and LLMs for identifying subtle “bad” patterns that traditional rule-based systems might miss.

What do you think about this? Are similar mechanisms implemented in your processes?

Disappointed by Project Hail Mary: A Missed Opportunity for Smart Sci-Fi | May 04 2026, 16:40

We went to see Project Hail Mary yesterday. Honestly, neither Nada nor I liked it at all. Maybe we’ve just grown out of the age group that likes such movies. Comic book style. The alien, in my opinion, appeared on a budget. It feels like it’s at the level of the early 2000s – when you could have made exactly the same thing. Remember the movie Arrival, where they tried to come up with something unusual? Really, was this stone monstrosity worth 200M? The whole plot is full of cliches and banalities. In one minute, they made it so that the human and the alien began to understand each other perfectly via some program that a science teacher created in a day. As if the astronaut and a piece of rock just start chatting like buddies… 5 kilometers of iron chain the thickness of an index finger is about 10 tons of metal… did they have that much on the ship?

The directors became successful in the realm of Lego movies and Cloudy with a Chance of Meatballs, along with a couple of comedy series and 21 Jump Street. I was expecting a movie in the spirit of Interstellar or The Martian, smart adult sci-fi that is not afraid of scientific details, and instead I got a children’s fairy tale with an ugly alien.

I googled it, and it turns out that a ton of people are thrilled with it and it’s making a lot of money.. Probably, people are nostalgic for such amidst post-irony, satires, various narratives, Lanthimos, and “Battle after Battle”. As children, everyone watched “Flight of the Navigator” and “Short Circuit”, so adults are nostalgizing over simple goodness. Perhaps it’s just a family movie for watching with the kids. Then it might be okay.

okay, going back to watching the second season of Succession. It’s considerably better.

Repurposing Components from a Broken Air Purifier | May 03 2026, 15:00

The air purifier broke down, so I bought a used one with a new cartridge for the price of a replacement cartridge plus $40. I completely disassembled the old one, extracted the reusable components, and figured out how it works. Just like in school 🙂

Inside, it comprises:

– an ESP32-WROOM-32D controller. But a part of the board responsible for voltage burned out, so it’s trash now.

– a CO sensor MQ-7 (unfortunately soldered to the board, but can be desoldered). Though, it needs a heating cycle for correct operation. First 5V (60 sec) for sensor cleaning, then 1.5V (90 sec) for measurement. But, it can also be used elsewhere.

– Plantower PMS9103M — a high-precision laser sensor for measuring airborne particulate matter concentrations (PM1.0, PM2.5, PM10). Can be connected to Arduino, specification available.

– a microwave motion sensor (radar), model RCWL-0516. Can be connected to Arduino, very simple interface. Detects motion up to 5-7 meters around within 360 degrees.

– 200W Snowfan YY225H310B motor. Also quite simple to connect, but it requires 310V DC plus 15V for speed control. But that’s all.

– a Hall sensor (magnet)

The motor is the most valuable part. It’s priced at $100 on eBay. Though, it should probably be tested first to see if it hasn’t burned out.

Harnessing Chat Data for Semantic Q&A Search | April 30 2026, 04:05

In one evening, I created a simple utility that extracts the Natural Language Processing chat for a year and a half – there are 65,000 messages, and converts it into question-answer pairs with semantic search available. Clicking on a search result (on the left) opens the dialogue in the chat. The messages that are responses to the question are highlighted. And at the top, the original phrasing of the question is highlighted as well.

How it works: the system assumes that people mainly reply to messages that are relatively close in the past. If several replies are made to one message, then it is likely useful and caught the interest of others in the chat. The system takes messages starting from the one many have replied to, ending with the last in the reply-to chain – and among such messages, it selects those that have at least 3 reply-tos to the original question. In essence, it cuts a piece from the chat starting with a popular question so that after the bottom cut, most likely, irrelevant content follows. Such blocks can overlap each other – for example, if someone asked a question while others were replying to something else.

So, if user A asked what the weather was like, and they received answers like “good,” “bad,” “rain,” and there were five messages without a reply-to, and then someone replied to “rain” with the question “why rain”, and five more people replied to this question, then the first question about the weather makes it into the system – the piece ends with 13 messages.

Afterwards, these pieces are summarized into question-answer pairs.

It turns out quite cool.

P.S. In the screenshot, the search query has nothing to do with the search result because I foolishly took the screenshot after I changed the query but before I hit send.

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 🙂

Misadventures in Keyboard Layouts: Searching for Gremlin, Finding Surprises | April 28 2026, 20:33

This is me typing the word gremlin, without switching the keyboard layout. Wanted to read about the query language for graph databases, need it for work. Google surprises, it does surprise