Stop me if you’ve heard this one before:

A crack team of hardware and software engineers, inspired by breakthroughs in computer science and electrical engineering, are driven to work 18-hour days, seven days a week, on a revolutionary new system. The system’s capabilities and speed will usher in a new era, one that will bring transformative computing to every workplace. The long hours are necessary: the team knows that every major computer company sees what they see on the horizon, and they too are working around the clock to take advantage of powerful new chips and innovative information architectures.

The team is almost entirely men, men whose affect and social skills cluster in a rather narrow band, although they are led by a charismatic figure who knows how to persuade both computer engineers and capitalists. This is a helpful skill. Money, big money, is flowing into the sector; soon it will overflow. Engineers are constantly poached by rival companies. Hundreds of new competitors arise to build variations on the same system, or to write software or build hardware that can take advantage of this next wave of computing power. Some just want to repackage what the computer vendors produce, or act as consultants to the companies that adopt these new machines.

The team solves one problem after the next, day and night, until the machine is complete. They focus, overfocus, block out the other concerns of the world. Their wives are ignored, as are the kids. The work is too important.

* * *

Such is the story of Data General and the group that built the computer system code-named “Eagle,” which would be successfully marketed as the Eclipse MV/8000. My summary above comes from Tracy Kidder's wonderful book The Soul of a New Machine, published in 1981. It’s about the rise of minicomputers, a now-amusing name for machines the size of double-wide refrigerators, which were considered a major advance during the 1970s, when gargantuan IBM mainframes still roamed the earth and were possessed only by the largest companies and bureaucracies. Minicomputers used new CPUs and memory that made computing accessible to a much wider range of applications and locations, and were relatively cheap. They flourished.

The Soul of a New Machine has much to recommend it — it won the Pulitzer Prize for its propulsive narrative and crisp explanations of complex technology — but I’m writing about it now, following Kidder’s recent passing, because the book helpfully dislodges you from your presentist perspective and asks, “Look what happened before — sound familiar?”

* * *

A half-century after it was published, The Soul of a New Machine does a better job challenging AI hype than most current criticism. (Also, there are probably writers working on books about AI who are shaking their fists at Kidder for beating them to that memorable title.) It's hard to read The Soul of a New Machine in 2026 without wondering whether all this AI hype is really so new. Is AI truly more revolutionary than a previous wave of computer technology that offered, for the first time, to put screens on every desk of every company? The Data General team helped to bring about a transition not from existing software and hardware to incredibly intelligent software and hardware, or from powerful computers to superpowerful computers, but literally from paper to digital files and high-speed processing. Now that is a transition. The millions of companies that could not afford an IBM mainframe could afford a Data General Eclipse or a DEC VAX system or a minicomputer from another competitor. They could, for the first time, give every employee the power of computers. Is having Microsoft Copilot help your accountants with their spreadsheets more revolutionary than moving those accountants from physical spreadsheets to electronic ones?

Amazingly, the final chapters of The Soul of a New Machine tackle exactly the same profound questions we are struggling with today regarding the impact of artificial intelligence, and Kidder records Data General engineers expressing concerns that sound straight out of the mouths of engineers working at OpenAI or Anthropic. The team’s excitement upon the completion of the Eagle leads to reflections and bigger worries than beating their competitors. What if the Pentagon wants to use the Eagle for war or other destructive purposes? Should the team object or build back doors into the machine? What will the new computer system mean for employment, since it will replace many functions of work with software, and do those tasks faster than anyone can imagine, in nanoseconds? What if their work culminates in true artificial intelligence, and the machines take over and destroy us?

Spending so much time with the team, Kidder begins to ponder these questions himself — and has his own unsettling encounter with the technology. An engineer introduces Kidder to Adventure, one of the engrossing text games of early computing. He is sucked into its digital world, playing nonstop for hours. The computer suddenly feels alive, intelligent.

But Kidder pulls back.

It was the time of night when the odd feeling of not being quite in focus comes and goes, and all things are mysterious. I resisted this feeling. It seemed worth remembering that Adventure is just a program, a series of step-by-step commands stored in electrical code inside the computer.

How can the machine perform its tricks? The general answer lies in the fact that computers can follow conditional instructions.

Kidder turns to one of the Data General engineers, Carl Alsing:

I asked Alsing how he felt about the question — twenty years old now and really unresolved — of whether or not it's theoretically possible to imbue a computer with intelligence — to create in a machine, as they say, artificial intelligence.

Alsing stepped around the question. “Artificial intelligence takes you away from your own trip. What you want to do is look at the wheels of the machine and if you like them, have fun.”

Alsing’s focus on the role of the new machine in your life or work, rather than its purported soul, instantly dispels the mythology surrounding this emerging technology. Even after an all-nighter building a revolutionary computer, Alsing is lucid about what he is making: a tool that might be helpful for some people and some purposes, but not for others.

* * *

In the 1980s, most of the minicomputer companies, launched with such excitement in the late 1970s, failed. Data General was acquired for a fraction of the billions it was once worth. The minicomputer, however, was broadly adopted, was transformative, became routine, and then was surpassed by a new new machine, the personal computer.

Later, Data General’s domain name, DG.com, was sold to a chain of discount stores, Dollar General.

For The New Yorker, Hanif Abdurraqib considers the cost of what he calls “relentless convenience,” our ability to stream content of every kind, be it movies, music, and even potential mates on dating apps, and what we lose when we live in this frictionless existence. There’s so much to learn and to savor in friction, he suggests, be it waiting for a song on the radio to complete a prized mixtape or the deep connection we can find if we go through the time and trouble to ditch electronic communication and actually meet others, face to face.

Maybe what my pal who insists on finding love the old-fashioned way is saying is that it shouldn’t be as frictionless as browsing Amazon from your couch. If you believe, as she does, that the next person you fall in love with could be the last partner you ever pursue, and the last who ever pursues you, then that pursuit should find you thrown fully into the world, eager for the beauty and discomfort of spontaneous human interaction. And I tell her that I mostly agree, though I generally just avoid dating apps because the onslaught of visual information overwhelms me. Still, I understand her desire, because so many of my own desires are detached from the reality of the times we live in. I am still inventing inconvenience in order to bolster my desire to feel alive.

Let’s imagine you have a friend who’s very good at Tetris. You’ve challenged them to a game with a twist: you get to pick which pieces they have to play. You agree that if your friend can survive 100,000 blocks then you’ll declare them the winner; but if they get game over before this, you win the challenge. So what do you do?

Tetris is a puzzle game of falling blocks that you can rotate and move as they fall. Forming complete horizontal lines clears all the squares in that line, and the aim is to prevent the blocks from stacking all the way to the top of the playfield, which results in game over.

The playfield is 10 cells wide and 20 cells tall and the game is played with seven different blocks, called one-sided tetrominoes, that are each made up of four squares. They are labelled I, J, L, O, S, T and Z because they look a bit like these letters.

There are many different versions of Tetris but, for the challenge against your friend, you will be playing a very simple version where you can pick any block you like, regardless of what has been picked previously, and the speed of the blocks falling stays the same through the whole game.

How to lose

First let’s look at the worst strategy you could go with: choosing the same block 100,000 times.

It’s easy to see that the I, J, L and O blocks fit very neatly together and can always be arranged to completely clear the playfield. The playfield will be cleared after only ten I blocks, ten J blocks, ten L blocks or five O blocks have been placed.

Ten $J$ blocks.

…or ten $L$ blocks fit together nicely then all disappear.

Ten $I$ blocks also fit together nicely
then all disappear.

For the S, T and Z blocks it’s a little less obvious. All three follow the same idea, so let’s look at how it works for the S block:

You can see that after a number of block placements it loops back to a previous step, but never back to the start. But the stack can always be kept between two cells and four cells tall, so S blocks can be played infinitely without resulting in game over, despite never clearing the playfield.

So, regardless of the block you choose, it can always be played as many times as you like without resulting in game over. Since your friend is the best Tetris player you know, this strategy will pretty certainly result in you losing the challenge.

How to win

Let’s instead consider a combination of S and Z blocks. S blocks fit nicely with other S blocks, and Z blocks fit nicely with other Z blocks; but S and Z blocks don’t fit well together.

Two $S$ blocks or two $Z$ blocks fit together nicely…

…but an $S$ block and a $Z$ block don’t.

Because of this, if you choose an alternating sequence of S and Z blocks, the best way for your friend to avoid game over is to construct columns of only S blocks and columns of only Z blocks. The playfield is 10 cells wide and each column will be two cells wide, so there will be five columns, which is odd, resulting in either three S columns and two Z columns, or two S columns and three Z columns.

Since the S and Z blocks are simply the reflection of each other, consider (without loss of generality) the scenario with three S columns and two Z columns. This will result in the Z columns growing faster than the S columns and eventually both Z columns will reach the top of the playfield. At this point, to avoid game over your friend must place a Z block in an S column, creating a one cell wide and two cell high `hole’.

Eventually, your friend is forced to play a $Z$ block in an $S$ column

Filling these holes causes issues later on in the game since there are a finite number of times they can be filled without creating new holes elsewhere. So new holes will continue to form and your friend can only create so many gaps before they reach game over.

But will this happen within 100,000 blocks?

How many blocks?

A more in-depth explanation can be found in Heidi Burgiel’s paper How to lose at Tetris (1997), but the most important parts are the following facts that were proved:

The maximum number of alternating S and Z blocks that can be placed before a hole must appear is 240 blocks.

The maximum number of times an S or Z block can be used to fill existing holes is 120 times, each time removing two holes.

The maximum number of holes the board can contain without resulting in game over is 50 holes, which is 10 holes per column.

By calculating the total number of holes that can possibly appear on the board before game over, including the ones that get filled in, and then multiplying by the number of block placements required for each hole to appear, we get an upper bound for how many blocks will force game over. The number of holes that can appear is $(120\times2)+50=290$, so game over must occur within $290\times240=69600$ alternating S and Z blocks.

Since this is well within 100,000 blocks, you now have your winning strategy. Choose only alternating S and Z blocks and even if your friend is the Tetris world champion you’ll be sure to beat them!

Infinite Tetris?

What would happen if you were to pick blocks at random instead?

In the finite game that you and your friend are playing, the probability of a sequence of 69,600 alternating S and Z blocks occurring at any point within 100,000 blocks is incredibly small, but not zero.

Despite being very unlikely to happen during your challenge, the game-ending sequence of S and Z blocks is guaranteed to occur at some point in a long enough game of Tetris. Because of this, every game of Tetris must eventually end.

Another way to think about this is in terms of the infinite monkey theorem, which states that a monkey randomly hitting keys on a typewriter for an infinite amount of time will eventually end up typing the entire works of Shakespeare. Instead, imagine that the typewriter only has the letters I, J, L, O, S, T and Z, and the monkey hitting the keys chooses the next block in the Tetris game. Given an infinite amount of time, the monkey will eventually end up typing the sequence of 69,600 alternating Ss and Zs, ending the Tetris game it was choosing blocks for.

Back to reality

In regular Tetris games, the speed at which the blocks fall steadily increases. This causes players to make more and more mistakes and, just like the holes in the S and Z columns, these mistakes will stack up until game over is inevitable. Ultimately, small mistakes due to the time constraints will likely be what causes your friend to lose the challenge, so you probably won’t have to wait 69,600 blocks to beat your friend.

But maybe next time pick someone who isn’t as good at Tetris!

The post Cheating at Tetris appeared first on Chalkdust.

One of the favorite selling points of tech industry figures when it comes to the intersection of AI and education is the capacity for the creation of an on-demand tutor that is “infinitely patient.”

This is Sal Khan’s promise in Brave New Words: How AI Will Revolutionize Education (and Why That’s a Good Thing), where he takes inspiration from the novel Ender’s Game (a famously positive story about the fates of children) and describes a world where students have “a personalized tutor in every subject.”

In his manifesto, “Why AI Will Save the World”, tech investor Marc Andreessen puts it this way:

Every child will have an AI tutor that is infinitely patient, infinitely compassionate, infinitely knowledgeable, infinitely helpful. The AI tutor will be by each child’s side every step of their development, helping them maximize their potential with the machine version of infinite love.

In my review of Khan’s book I called his views “unserious” because he does not seem to understand much of anything about teaching and learning, skipping several steps on his way to his AI-Aristotle future. This idea that somehow infinite patience is a positive quality in a teacher is perhaps the most telling sign that these people simply do not know how learning works.

Some of my most important formative educational experiences involved some teacher or authority figure losing patience with me. I will never forget the moment that my 8th grade language arts teacher Mrs. Thompson told me to “cut the shit” when I had quarter-assed a writing task. This is the same teacher who also read a short story of mine and declared that “she’d never read anything like it.” I think this was praise, or at least I took it that way, so when Mrs. Thompson said the obvious about my lackluster effort, I felt bad. I’d disappointed her.

Humans learn in communion with other humans. Maybe this was not true for Sal Khan who is quite obviously smarter and more driven than most other humans, but it is true for the vast majority of us.

In a recent article at Chalkbeat Sal Khan admits, with some mix of surprise and regret, that the very technology he said was going to revolutionize education was a “non-event” for most students. “They just didn’t use it much.”

No kidding. Back when Sal Khan was publishing Brave New Words, lots of people were saying this was going to be the case, me, , Audrey Watters, and many many others. As Watters say, “AI tutors" are not the future; they're the past.”

Please enjoy this mashup of a BBC report from 1965 on “learning machines changing education” and Khan’s demonstration of what it’s like to work with the Khanmigo chatbot.

In the Chalkbeat post mortem, Khan Academy’s chief learning officer Kristen DiCerbo suggests that the Khanmigo failure is a user problem, “Students aren’t great at asking questions well.”

My experience is that students are great at asking questions, which is not the same thing as asking questions of a tutor bot.

Back in 2024 I “debated” some dude from the American Enterprise Institute on the potential of chatbot tutors like Khanmigo. I took the skeptic’s side and argued that the number one reason this technology would not revolutionize education is because it did nothing in terms of the chief challenge of education: engagement.

I was right right, AEI dude was wrong. Sal Khan was wrong. Bill Gates, Laurene Powell Jobs, Arne Duncan, , Angela Duckworth, Tony Blair, and Francis Ford Coppola (seriously) - all of whom blurbed Brave New Words declaring it very serious indeed - were wrong.

They have always been wrong. They were wrong before they got started and yet hundreds of millions of dollars have gone towards a project that was doomed from the outset, dollars that could have - at least in theory - gone to, I don’t know, human beings who teach.

Over the years I have tried to practice good faith to these projects even as I was skeptical. I have spoken at length to people inside these projects and the granting organizations that fund them and it is clear they are well-meaning, not “grifters” out to profit at the expense of others.

But, like Mrs. Thompson telling me to cut the shit, I am out of patience. It’s time to move on from people like Sal Khan and projects like Khanmigo from sucking up so much money and oxygen when it comes to our systems of education.

Sadly, this is not happening. Not unless we make it happen.

We’re up against billionaires, world leaders, thought leaders, politicians, and one of the greatest film directors of all time, a tough set of opponents, but at least we have the benefit of being correct.

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What do you do when your AI-schools revolution fizzles? Slink off to lick your wounds and figure out something else to do with your life? Go back to the drawing board at a root level to better understand where you went wrong and return with something more deeply considered?

Not Sal Khan. You pivot to proposing a “disruption” of higher education.

Welcome to the Khan TED Institute, a joint project between Khan Academy, TED (as in talks) and ETS (Educational Testing Service). For $10,000 they are proposing to create a bachelor’s degree in “Applied AI” delivered online in two years.

I aired my doubts and grievances over this project at Inside Higher Ed in which I declare this project what it is: bullshit.

But it is bullshit backed not just by these three wealthy and powerful nonprofits, but also the institute’s “corporate thought partners” including Google, Microsoft, McKinsey, and Bain (among others).

Lest my feelings about this project be unclear, this is how I put them in the column:

These people are my enemies. I have only ill will for this project and wish them failure, because this vision for a future of postsecondary education is a recipe for mass immiseration and public disempowerment. Imagine a world where Microsoft, Google, McKinsey, et al … get to determine what and how you learn from cradle to retirement.

Anyone involved in higher education, particularly public higher education or private higher ed where your institution is not insulated by wealth and privilege, should also view this project as a direct assault on their continued existence. The higher education sector and those who have historically been responsible for it (government, voters, etc. …) should pause and reflect on how what’s happened to the sector has made it potentially vulnerable to this sort of program, but we also must set recriminations aside and deal with the threat directly.

Again, I don’t think Sal Khan is a bad person. He is not evil. I wish him nothing but health and happiness in his day-to-day existence. But we should wish him nothing but ill-will on this project because its success will mean that we have a society where individuals are essentially indentured to these corporate thought leaders. It means distorting education into a shape that pleases tech industry giants and consultants. To the extent our society already operates this way is not to our credit.

That a group of people think this is a positive direction for our collective future is mind boggling.

The good news is that Sal Khan has failed in every one of his revolutions. He gives good TED Talk, but he doesn’t seem to understand or care for anything about pedagogy. As says in his obituary for chatbot tutors, “Given that Sal Khan has tried unsuccessfully for nearly two decades to abstract humans away from human systems—first with human explanation, then with human evaluation, and most recently with human tutoring—it seems unlikely that he is the right person now to pivot edtech towards humanity.”

Still, I wouldn’t mind seeing the Khan TED Institute ethered from the get-go rather than having to engage in the same I-told-you-sos a couple of years from now.

Khan made it to 60 Minutes twice, 12 years apart, each time talking about a revolution. He was wrong both times.

How many times does someone get to be wrong before we stop listening to them?

Why do we have infinite patience for this man?

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Links

At the Chicago Tribune, I tried the LitRPG genre and while I think I get what others get, I don’t get it.

At I contrasted the end of Hampshire College with the birth of the Khan TED Institute and what that says about the world today.

At the New York Times, Colson Whitehead entertainingly puts the boot to using AI to write for you. (Gift link)

A doctor who was an early adopter of AI scribes stopped using them when he realized how it was distorting his practice.

The 2026 Guggenheim Fellows were announced, including lots of writers. I always get a little envious of these things and then I remember that you actually have to apply, which in my case is never going to happen.

Via my friends , “In Our Glorious AI Future, There Will Be No Such Thing as Money (For You)” by Andrew Singleton.

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Recommendations

1. Fintech Dystopia by Hillary J. Allen
2. The Road: Stories, Journalism, Essays by Vasily Grossman
3. Day of the Oprichnik by Vladimir Sorokin
4. The Mountain in the Sea by Ray Nayler
5. Carthage: A New History by Eve MacDonald

Sean H. - New York City

A bit of a tough one for me since I don’t know these books, so I’m falling back on my biblioracling gift and letting the spirits guide me: The Thousand Autumns of Jacob de Zoet by David Mitchell.

I’ve got a bit of a backlog, but I also have a combo work/pleasure trip next week so I may do an all recommendations newsletter to catch-up so don’t hesitate to ask.

Request a reading recommendation.

I’ll be at a conference of language arts teachers for the province of Alberta next week in Banff, which is very exciting on multiple fronts.

If anyone has Banff-related travel tips, please share them in the comments.

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See you, in some form, next week.

JW
The Biblioracle

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Why it’s good to be bored

The post Defending Our Consciousness Against the Algorithms appeared first on Nautilus.

If you have multiple computers, you'll quickly run into the problem of having data on one but needing it on the other. Because of this, people have been connecting them together since the beginning.

However, this created a classic problem: Each network used it's own addressing scheme, wire protocol, headers, etc, etc... If you wanted to get a file between two networks, you had to find a machine that was connected to both and manually forward it.

To automatically route data between networks, we had to agree on a universal numbering scheme for computers. During the 1980, people settled on the 32-bit "IPv4" address.

Here's my server's address (split into bytes):

65.109.172.162

Back then, computers were massive and extremely expensive, so 32-bits was plenty: After all, there's no way there would ever be billions of computers in the world...

There was enough margin to assign addresses roughly geographically and in power of 2 sized blocks. This allowed the internet to be scalable because each router doesn't have to know the exact details of every computer:

When your ISPs network sees my address, it doesn't have to know that what specific computer 65.109.172.162 is, just that everything starting with 65.109 should be sent to Finland.

... but does mean that we can't even have the full 32-bits of address space.

We ran out around 2011.

To keep the internet working, people started hiding multiple computers behind a single address. Odds are, every single machine on your home network has to share a single IPv4 address using a rather complex "NAT" setup.

... but even this is not enough.

Recently, ISPs have started putting multiple customers behind a single address. This obviously creates problems if you want to host services from home (a website, multiplayer games, etc), but is also a problem for normie activities: It's common to get punished by a website for something you didn't do.

If you've ever seen a "You've been blocked" message, gotten a Captcha every time on a specific site, or simply had it mysteriously refuse to load... there's a good chance this is what's happened.

Someone who had the address before you was either doing something bad — or more likely — got hacked and was used as an unwitting proxy for a criminal's traffic.

Blocking by IP address is the one effective way to deal with bad actors on the internet: It's the only way to block a particular person without requiring everyone to make an account.

The solution is quite simple:

If we've run out of addresses that fit in 32-bits... just use longer ones. This was first standardized all the way back in 1995 with IPv6 and 128-bit addresses: four times as long as IPv4. Here's how many unique addresses that allows:

340,282,366,920,938,463,463,374,607,431,768,211,456

That's quite a bit. Here's mine:

2a01:04f9:c011:841a:0000:0000:0000:0001

These larger addresses also have a lot of other benefits: There's less need for virtual hosting, the address hierarchy can be cleaner, and it's possible put MAC addresses in a /64 block for stateless autoconfiguration.

Problem solved, right?

No.

Despite being around for 30 years (almost as old as gopher!), most people still do not have access to an IPv6 capable network:

10 Users don't have IPv6 support
20 ... so websites are forced to support (ancient) IPv4.
30 ... and users don't notice they are missing anything.
40 ... and don't complain to their ISP
50 GOTO 10

Because of this, even though the solution has existed ~forever, bad decisions from 1980 continue to make your internet connection worse and more expensive.

To help break out of this cycle, I've decided to remove IPv4 support on my site. Cutting off most of my readers is a bit hash, so it'll only be disabled for one day each month:

The 6th will now be IPv6 day.

Any attempts to access my site over IPv4 will yield a message telling you that your network still doesn't support a 30 year old standard. If you really want to access my site during the sixth, use your phone. All major cell carriers have long since caught up with the times (because giving each device it's own address improves performance).

Obviously, one website going down is just a site going down. For this to work, a lot of people have to do it. If you have a website where 97% uptime is tolerable, please consider doing this.

If downtime is too much for you, how about a banner that warns about IPv4?

Related:

• /outdated.html: The message in question.
• /misc/v6day/: IPv6 only link. Avoid any suprises on May 6th.
• https://xkcd.com/865/: The one scenario where 128 bits is not enough.