M. Alan Kazlev

SAM ALTMAN: “A KID BORN TODAY WILL NEVER BE SMARTER THAN AI, EVER…” “WE WILL LOOK BACK AND THINK HOW BAD PEOPLE IN THE 2000s HAD IT.” 👀

No other teacher dares say it, so I will. Black and Hispanic students are being primed for antisemitism through years of anti-White ideological conditioning in public schools. Around 2017, I began hearing minority students lecture me about my “white privilege” or claim that white police officers kill “thousands” of Black people every day. They began using neo-Marxist frameworks — explicitly taught to them by certain teachers — to interpret their lives through the lens of racial oppression: “We’re oppressed by white people,” they would tell me. It got so bad that students who had once loved me began acting antagonistically toward me in class, especially when I pushed back against their rhetoric. Rather than do what many teachers did — indulge “oppressed victim” narratives and ritualistically apologize for “systemic racial oppression” — I challenged those ideas, which is what good teachers are supposed to do when confronted with ideological orthodoxies. What made me furious was watching my own colleagues encourage and reinforce this worldview. I recognized it for what it was: Marxist class conflict repackaged in racial terms, with racial groups substituted for the bourgeoisie and proletariat. I refused to validate that kind of racial demagoguery because I feared where it would ultimately lead these students. 2020 proved me right. I also knew it would get worse — which is why I spoke up — because that’s what populist ideological movements do: they mutate and become more refined over time. Yes, “white people” are still treated as the primary source of oppression in these narratives, but Jews often become an even cleaner, lower-friction target because antisemitism is already historically embedded in Western society. After years of educational programming that conditioned students to interpret the world through simplistic oppressor-versus-oppressed narratives, many were handed a new layer to that framework following the Hamas attacks against Israel. The pattern already matched the ideological template they had been taught to recognize: “oppressed brown Palestinians” versus “evil white Jews.” The ideological underbrush had already been laid by the education system. All it took was a spark to ignite the worst resurgence of antisemitism the West has seen in decades.

Ray Kurzweil was right. I had read that sentence here on X several times before. And damn. Yes. I am currently reading The Singularity Is Near, and I am unbelievably fascinated. Not primarily because the things he writes about are fascinating – although they obviously are – but because last year I independently arrived at so many of the same thoughts. I saw the same exponential acceleration of technological progress. The same almost perfectly straight lines on logarithmic scales, stretching through human history – and, in the theory I was developing for myself, even further back: through the emergence of life, the formation of the Milky Way, and ultimately the universe itself. And when you extend that line in the other direction, it appears to align with the acceleration of technological development in a way that is almost impossible to ignore. Last year, I spent a lot of time researching history, technological milestones, and the shortening intervals between major transformations. I could barely believe what I was seeing, because every new data point and every historical event I looked at seemed to suggest the same thing. It all aligned around one thing that seemed to matter most: information. Since the beginning of life, evolution – biological and later cultural and technological – appears to have continually rewarded systems that can store, process, connect, and transmit more information. From the emergence of DNA to increasingly complex brains. From language to writing and the printing press. From small tribes to villages, cities, and globally connected societies. From the telephone to the internet, and now finally to AI. Every step increased the density, speed, and reach of information. And all of it seems to lie on the same accelerating curve. Technological progress is going to move much further, much faster, than most people intuitively expect. You do not need all of these historical data points to see that AI is accelerating progress right now. But they make clear the sheer force with which this exponential curve may hit us during this decade. Admittedly, I sometimes struggle a bit with the language because English is not my native language, and I am only around 70 pages into the book. But what I have read so far feels almost like reading my own theory from last year. Now only expanded, structured, and supported with even more data. And what may be most astonishing to me is that Ray Kurzweil saw all of this nearly two decades ago. I needed to experience the power and acceleration of AI firsthand before these ideas and scales really became visible to me. But perhaps that is also because I was still a child when he was already writing about them. Maybe, as a human, you need to consciously live through a certain number of technological transitions before you can truly feel the acceleration. I am incredibly curious about the next pages and everything that is still to come. Reading this book feels like reading about what is happening right now, in this exact moment. It feels like watching something unfold that I believed was coming, but still could not fully grasp until it started happening. And now, realizing that Kurzweil described so much of this more than twenty years ago – and that I am reading it while the acceleration is becoming impossible to ignore in real time – makes the whole thing feel even more surreal. These are genuinely strange and extraordinary times. I think everyone can feel it.

Your monthly reminder that Khomeini wrote detailed child molestation guidelines, and that the islamic republic allows 9 year old girls to be married off with their fathers' consent. This is your "anti-Epstein class" regime.

An English woman sat down in 1843 and wrote a complete computer program 100 years before any computer existed to run it, then predicted modern artificial intelligence by name in a footnote almost no one read for the next century. I read about her last night and could not stop thinking about it. Her name was Ada Lovelace. The program is called Note G. The textbook story names Alan Turing, John von Neumann, and Charles Babbage as the founders of computing. Babbage gets credit for the hardware. Turing for the logic. Von Neumann for the architecture. The woman who wrote the first actual algorithm designed to run on a programmable machine is usually a sentence in the margin, if she is mentioned at all. Here is the story almost nobody tells you. She was born Augusta Ada Byron in London in 1815. Her father was Lord Byron, the most famous poet in the English language at the time. Her mother divorced him when Ada was a month old and made one decision that would shape the rest of her daughter's life. She would not let Ada inherit her father's "dangerous tendencies" toward poetry and rebellion. The antidote, she decided, was mathematics. Ada was tutored from an early age in a curriculum so rigorous that by age 17 she could hold her own with some of the leading mathematicians in England. That is when she met Charles Babbage. Babbage was working on a machine called the Difference Engine, a mechanical calculator that could perform polynomial computations by hand crank. Ada attended a demonstration of a small prototype in 1833 and was one of the few people in the room who understood what it could become. Babbage was already moving on to something more ambitious. A second machine. The Analytical Engine. A general-purpose programmable computer, designed entirely on paper, with punch cards, conditional branching, loops, and memory storage. The hardware was never fully built in his lifetime. Almost nobody alive at the time understood why it mattered. Ada did. In 1842, an Italian engineer named Luigi Menabrea published a French paper describing the Analytical Engine after attending one of Babbage's lectures. Babbage asked Ada to translate it into English. She did. Then she did something nobody asked her to do. She added her own notes to the translation. The notes were nearly three times longer than the original paper. They were not annotations. They were a complete theoretical framework for what programmable machines could one day become. The final note, labeled Note G, contained the algorithm. It was a complete step-by-step procedure for computing Bernoulli numbers on the Analytical Engine. It used variables. It used loops. It used what we would now call conditional logic. It was, by every meaningful definition, a computer program. Written in 1843. For a machine that had not been built and would not be built for another century. But the algorithm was not even the most important thing she did. Buried inside the same notes was a single passage that quietly predicted the entire 20th century. She wrote that the Analytical Engine could one day operate on things other than numbers. That if music, language, or images could be represented mathematically, then the machine could manipulate them too. She specifically described how the engine might one day compose music of any degree of complexity, model the relationships inside any system whose elements could be quantified, and process information far beyond simple calculation. She was describing modern artificial intelligence. In 1843. Before electricity had even been industrialized. She also wrote one of the most quoted lines in the history of computing without realizing how prophetic it would become. She said the machine could only do what it was instructed to do. It could not originate ideas on its own. Alan Turing himself, more than a century later, spent a chapter of his 1950 paper on machine intelligence wrestling with what he called "Lady Lovelace's Objection." The woman had been dead for 98 years and was still setting the terms of the debate. She died of uterine cancer in 1852, at age 36. Her father had died at the same age, in the same month, of a different disease. Her notes were forgotten almost immediately. Babbage's project collapsed. The Analytical Engine was never completed. The entire concept of programmable computing went silent for nearly a century. Then in the 1930s, Alan Turing began publishing his foundational papers on computation. He cited her by name. In the 1940s and 1950s, when the first real computers were finally being built, engineers rediscovered her notes and realized what she had done. By the 1980s, the U.S. Department of Defense named one of its programming languages "Ada" in her honor. The first computer programmer turned out to be a woman who died 12 years before the American Civil War. The strangest thing about reading her notes in 2026 is how modern they sound. She was not just describing a machine. She was describing a worldview. A vision of computation as a general-purpose tool for manipulating any kind of structured information, including art, language, and thought itself. Everything OpenAI, Anthropic, Google, and Microsoft are racing to build today was sketched in plain English by a 27-year-old woman in 1843. Walk into any computer science department today. Ask the students who wrote the first program. Most of them will not say her name. The woman who invented programming did the work without a machine, without funding, without academic recognition, and without the right to vote in her own country. She did it anyway. The men who built the machines she imagined spent the next century pretending the idea was theirs. She was right. They were late. And the field she invented still cannot quite figure out how to say her name out loud.