Tag: facebook

Modern Reading: More Words, Digital Shifts, and Surprising Data Insights from 2008 | December 14 2025, 22:33

An interesting study caught my eye, dating back to 2009. According to it, the modern human indeed reads significantly more than in the past, although the format of this reading has changed. The study suggests that in 2008, an average American consumed about 100,000 words a day (approximately a quarter of “War and Peace”) – this is an approximate number of words that passed through consciousness per day (via ears or eyes), calculated based on activity chronometry. This is 140% more than in 1980.

Therefore, contrary to the myth about the degradation of reading, at least in 2008, we processed 2.4 times more textual information than our parents’ generation. Moreover, the study only considered information consumed outside of work (at home, in transit, during leisure).

The structure of reading – if in 1960, 26% of words came from paper, by 2008 this share had fallen to 9%. However, digital media (internet, email, social networks) not only compensated for this decline but also tripled the total reading time. The reason — the internet, as it is predominantly a textual environment (web surfing, email).

But it’s interesting that although the Internet accounts for 25% of consumed words, it only makes up for 2% of bytes (since video on the internet in 2008 was of low quality). Thus, they estimated the information flow from different channels and converted it into bytes 🙂 Radio accounted for 19% of the time but only generated 0.3% of bytes (as audio requires less data). Voice communication (telephone) — accounted for only 5% of words and a negligible share of bytes, but it was the only fully interactive channel before the internet era. TV remained the main source of information by time in 2008 (41% of all hours) and quantity of words (45%), however, in terms of data volume (bytes), television was only second (35%), behind computer games.

Now about games, quite interesting. The main finding from the report: Games generated (or did in 2008) 55% of all “bytes” consumed by households. Meanwhile, they only accounted for 8% of user time. This is quite a controversial topic in their report.

Those 100,500 words — that’s an assessment of actual words that a person either read or heard. This is not a metaphorical “equivalent,” but an attempt to calculate the verbal information precisely. They took the consumption time of each media and multiplied it by the average word inflow rate for that channel. Reading (books, newspapers, internet texts): 240 words per minute. Email and web surfing – 240 words per minute. Television (dialogues in shows/movies): 153 words per minute. Radio: 80 words per minute (less because of many pauses and music). Music: 41 words per minute (song lyrics).

Link in the comments

The Evolution of Personalized Video Advertising | December 14 2025, 17:08

I kept seeing ads for an AI language tutor that I ignored, and the system forgot about me for a while before coming back with a noticeably older tutor.

But really, how soon will video advertising become personalized for us? Where in the same ad, New Yorkers will see their city, black people will see black people, in the morning the main character will be drinking coffee, and a car with the logo of their alma mater will flicker in the background?

Preserving the Essence of Soviet Animation | December 13 2025, 15:05

In Soviet times, there was a great school of animation that led the world for many decades. If you search on YouTube for “Vovka in the Land of Far Far Away”, it almost exclusively shows restorations 🤮, and at the same time, it shows the same disgusting restorations of heaps of other cartoons, all made in the same style (vectorization, black outlines). If you go to Wikipedia, it will display a screenshot from the restoration, not from the original 1965 cartoon. The original can be found, for example, by searching “vovka in the land of far far away madina gazieva”, but searching “vovka in the land of far far away soyuzmultfilm 1965” shows nothing at all.

They really broke the internet.

P.S. By the way, “two of a kind, fulfilling wishes,” and “good enough” resonate very much with today’s ChatGPT 😉

Harnessing GPU Power Beyond Machine Learning: A Data Processing Experiment | December 13 2025, 01:16

Torturing my supercomputer. Illustration that the GPU is not just for machine learning and some complex math.

My script takes a thick English dictionary (Webster) and multiplies it by 30, creating a list of 12 million words. Then, the algorithm looks through all 12 million words and replaces all the vowels with asterisks using regex. To add more load, a “word length” column is added, and then we take words longer than 10 letters and find the most frequent (top 5).

So, in Python this is

df[‘masked’] = df[‘text’].str.replace(r'[aeiou]’, ‘*’, regex=True)

df[‘len’] = df[‘masked’].str.len()

res = df[df[‘len’] > 10][‘masked’].value_counts().head(5)

and this code is executed first through the main processor, then through a GPU.

The main processor (I have the top-tier Intel i9 285k) completes this task in 24 seconds, while the Nvidia RTX 5090 does it in 0.51 seconds. That’s a 46 times difference!

[Pandas CPU] Top Patterns:

masked

s*r w. sc*tt. 23280

s*r t. br*wn*. 23220

j*r. t*yl*r. 16140

bl*ckst*n*. 10860

b***. & fl. 10830

Name: count, dtype: int64

[Pandas CPU] Computation Time: 23.5596 sec.

Transferring data to GPU…

Transfer complete in 1.16s

— Running Benchmark: cuDF GPU —

[cuDF GPU] Top Patterns:

masked

s*r w. sc*tt. 23280

s*r t. br*wn*. 23220

j*r. t*yl*r. 16140

bl*ckst*n*. 10860

b***. & fl. 10830

Name: count, dtype: int64

[cuDF GPU] Computation Time: 0.5108 sec.

TOTAL SPEEDUP: 46.12x

Misadventures in AWS: Misusing aws-nuke for Configuration Exports | December 12 2025, 16:29

Just for laughs. I asked Gemini how to export the entire AWS configuration for local analysis, and they recommended using the aws-nuke command for permanently deleting everything, but if you add a dry-run flag, you’ll get the configuration… and someone actually follows such advice 🙂 and then we wonder

Two Weeks on Linux: From Mac to ArchLinux+KDE Bliss | December 12 2025, 16:24

Two weeks on Linux, wildly satisfied. After a Mac. I specifically have a setup of ArchLinux+KDE/Plasma 6.5. Everything here is customizable. For instance, I made a program from scratch in half an hour (no lie, thirty minutes) using Gemini that translates selected text to English or corrects errors if the selected text is already in English when ScrollLock is pressed. There seems to be an app for every situation in life, at least in my field. Everything flies (even though this is an Intel i9 285K/64Gb). I just enter a folder that contains 470,000 files, and it opens instantaneously. I’ve never seen anything like this anywhere else. I launch IntelliJ Idea, and there is practically no delay between clicking the icon and the editor being ready with the loaded project. All devices connected perfectly, unlike with the Mac, for which there are simply no drivers for my HP LaserJet 1018 and I need to perform tricks.

Now I occasionally switch to a Mac, and it drives me crazy that the hotkeys are different. Of course, they can be reconfigured for Mac, and probably I will do that. Muscle memory builds up, and switching quickly doesn’t work out. I miss iMessage a bit – I’m used to writing and responding to messages from the computer. Apple iMusic works, through a browser.

Overall, the impression is very good so far.

Stages of Understanding Scientific Papers | December 10 2025, 19:38

As I periodically read scientific papers on my topic, I will try to articulate the levels of understanding the truth.

Level 0: “Read Later Folder” Downloaded the PDF, the title sounds genius, the abstract seems like the solution to all my problems. The file is forever buried in the ~/Downloads/Papers/ToRead folder.

Level 1: “Sumerian Cuneiform” Don’t understand anything at all. Random symbols, the Greek alphabet is over. “Orthogonal extrapolation of cognitive entropy within a quasi-stationary discourse inevitably induces a bifurcation of transcendental synergism.” Such materials really lower self-esteem. Most often from this level, you either fall back to zero, or gradually move to the second level.

Level 2: “Illusion of Competence” The Abstract is clear, the Introduction reads like a good detective story. But as soon as the main section starts, the text turns into a pumpkin. I can’t paraphrase it in my own words, only in general phrases: “Well, they trained a neural net… kind of.”

Level 3: “Formulas where needed and where not” The Abstract is clear, the first half of the article is also okay (architecture, pictures). But then comes formula (4), where “magic” happens. I take the authors’ word for it that equation (3) leads to (4) because, of course, I won’t check it. Beyond that — sheer horror and belief in a miracle.

Level 4: “Goldfish Effect” While reading — everything is crystal clear. The logic is solid, conclusions are obvious, the authors are smart. I close the tab, someone asks me, “What was the article about?” — and I freeze. My mind goes blank. If you take away the paper, I can’t reproduce even the idea because there essentially isn’t an idea, there is a process.

Level 5: “Armchair Expert” Everything’s clear, I can retell the essence over a beer. I know that Input transforms into Output, but the “black box” inside is still black. Give me a computer, I wouldn’t be able to reproduce even the skeleton because, it turns out, the article lacks half of the important stuff.

Level 6: “Critic-Practitioner” Everything is clear, I can recount, understand how to reproduce (even without their code). I see where they cut corners. I definitely know that the “state-of-the-art” result is achieved only thanks to a lucky seed or dataset and this strange trick in preprocessing, mentioned in the footnote on page 12.

Level 7: “Deconstructor” Hooray, I’ve understood everything and implemented it myself. It works worse than in the article, but I know why. However, I understand this work better than the second author (who just made charts). I see that all this complex mathematics over 5 pages boils down to two paragraphs in the middle.

Level 8: “Nirvana” The article is trivial. The idea is secondary, it was all in the ’90s with Schmidhuber, just named differently. Formulas are overcomplicated for importance. I can write the same in 10 lines of code and it will work faster. Reject.

If anything — I’m stuck somewhere between 2 and 4.