Month: January 2025

Reading an article in Wired, the link will be in the comments. It’s fascinating to see how people from the past envisioned 2024.

In 2002, Kevin Kelly, one of the founders of Wired, attended a small party organized by Google, which at that time had not yet gone public and was solely engaged in search technologies. At this event, he struck up a conversation with Larry Page, Google’s co-founder, who later, in 2011, became the CEO of the company (and left the position in 2015).

Kelly asked Page a question that seemed sensible at the time:

— Larry, I still don’t understand. There are so many companies doing search. Free web search? Where is this going?

At that time, Google had not yet implemented its advertising sales scheme through auctions and had not made major acquisitions like YouTube. Many, including Kelly, doubted that Google would last long.

Page then replied:

— Oh, actually, we are making AI!

Years later, when Google had acquired 14 companies working in the fields of AI and robotics, Kelly often reflected back on that conversation. At first glance, it might seem that Google uses its AI resources to improve search, because search then generated 80% of the company’s revenue. However, Kelly wrote in his 2014 article that the opposite is true: Google uses search to enhance its AI.

Every time a user enters a query, clicks on a link or creates a link on the internet, they train Google’s AI. For example, by searching for “Easter bunny images and selecting the most appropriate one, a person teaches the system what an Easter bunny looks like. As of 10 years ago, when the article was written, 1.2 billion users made 12.1 billion queries daily, continuously training AI.

Interestingly, in that 2914 article Kelly was confident that by 2024, Google would create AI and it would gradually become the main product.

Well, here we are in 2024, and as of today 82% still comes from the same advertising. But still, 2024 became the year of AI and Google is among the key players (along with a dozen others).

Interestingly, the Larry-predicted formula from the article – add AI to everything indiscriminately and you get a new startup – worked out

“…In fact, the business plans of the next 10,000 startups are easy to forecast: Take X and add AI…”

He writes in 2024 that for AI, progress in three areas is critical:

1) GPU/parallel computation for training models

2) Big Data for training models

3) Algorithms that we have yet to conceive

“… This perfect storm of parallel computation, bigger data, and deeper algorithms generated the 60-years-in-the-making overnight success of AI.”

Discovered a plethora of interesting facts about SQLite. For those unaware — it is likely the most widespread database in the world. It’s utilized everywhere: from smartphones to cars and rockets. The scale of deployment — over _a trillion_ instances, billions of active copies worldwide. In your phone, dozens of applications use it.

Initially, SQLite emerged from the need to ensure reliable database operations on the USS Oscar Austin destroyer.

It is supported by _three people_. They do not admit external contributors. You can’t just send a pull request and hope the patch will be approved. SQLite’s development is backed by the company Hwaci. Interestingly, they seem to be involved in music too. Their website is extremely succinct. Office in a private house.

For each line of SQLite code, there are over 600 lines of test code. Tests cover 100% of branches (and 100% MC/DC) of the library. The test suite is highly diverse, including fuzzing tests, boundary value tests, regression tests, and tests simulating operating system crashes, power failures, I/O errors, and out-of-memory errors. Originally, SQLite was an extension of Tcl, and its main test suite is written in Tcl.

Interestingly, some SQLite tests are proprietary. The TH3 (Test Harness 3) test suite, which provides one hundred percent code branch coverage, is proprietary, and access to it is restricted.

I know of no other project that is open-source yet has paid tests.

To gain access, one must join the SQLite Consortium with an annual membership fee of 120 thousand dollars.

This is an interesting business model. Developers generate profit through licenses, paid support, service maintenance, consortium membership, and commercial extensions.

SQLite does not have a Code of Conduct (CoC); instead, they use a Code of Ethics derived from the “kinds of good deeds” from chapter 4 of the Rule of Saint Benedict. Google SQLite Code of Ethics, it’s a very intriguing document.

At the beginning of all source files, instead of legal notices, there is a blessing: “In place of a legal notice, here is a blessing: May you do good and not evil…”

SQLite creator Richard Hipp (D. Richard Hipp, DRH) couldn’t find any version control system that suited him, so he created his own called Fossil. Of course, Fossil is based on SQLite.

It reminded me of how Linus wrote Git.

DRH also wrote his own parser generator called Lemon.

All the above is described in more interesting details (and expanded) in an article on Habr, which is a translation into Russian of an article by Avinash Sajjanshetty. For originals — check the comments

Some novelties for me. Sharing, as they’re likely new for you too. About bulbous bows on ships, about how the body of water under the Paris Opera from “The Phantom of the Opera” actually exists, about how 70% of all global internet traffic passes by my house, and about how no one really knows how general anesthesia or paracetamol works.

= First Discovery =. Large ships may have this thing in front, called a bulbous bow. I didn’t understand what it was for, it seems to disrupt hydrodynamics. Turns out, it’s quite the opposite. It improves it. It creates a counter wave that partially offsets the main bow wave occurring when the ship is moving — especially at high speeds and for large vessels. Each ship’s bulb is designed individually.

= Second Discovery =. Remember “The Phantom of the Opera”? There was a body of water under the Paris Opera where Erik and Christine sailed. Well, it’s not fictional. There really is a body of water beneath the Paris Opera House.

The opera house required a much deeper basement space beneath the stage than other types of buildings, but the groundwater level turned out to be unexpectedly high. In February 1862, wells were drilled and in March eight steam pumps were installed, which operated around the clock, yet the site remained damp. To solve this problem, Garnier designed a double foundation to protect the structure from moisture. The design included waterways and a huge concrete tank (cuve), meant to reduce the pressure of the external groundwater on the basement walls and to serve as a reservoir in case of fire. The construction contract was signed on June 20. Soon, a persistent legend arose that the opera house was built over an underground lake, inspiring Gaston Leroux to include this idea in his novel “The Phantom of the Opera”.

= Third Discovery = Of course I knew it was a lot, but today I saw the number — 70% of internet traffic passes through a place just about 10 minutes from where I live. Around me, more than 130 data centers have been built covering an area of three million square meters. Quite a thrilling neighborhood. I hope no ill-wishers will mark this place on the map with a cross. This cluster specifically consumes about 150 TWh, which by my estimates is like ___THREE MOSCOWS___.

= Fourth Discovery = It turns out that no one really knows how general anesthesia works. There are theories in Wikipedia on how anesthesia functions. But though they exist, none of them is completely convincing. In 2019, it was found that human-like anesthesia even works on plants, like on a mimosa and on a venus flytrap—they stop responding to touch under it. Not to mention, as everyone knows, plants don’t have a central nervous system at all. Not a brain, not even neurons. There’s also xenon anesthesia. Meaning, it’s fundamentally an inert substance, doesn’t react with anything, but somehow works. They recently figured out how aspirin works, but there’s still no full understanding of paracetamol.