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AI Is Replacing Programmers and Mathematicians—Fast Eric Schmidt predicts that within one year, the majority of programmers will be replaced by AI agents, and graduate-level mathematicians will be rivaled by models trained on mathematical reasoning. Why? Because both code and math follow structured languages, which AI can learn to...

31,686 Aufrufe • vor 1 Jahr •via X (Twitter)

11 Kommentare

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Wes Rothvor 1 Jahr

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The Rundown AIvor 2 Jahren

AI won't replace you, but a person using AI will. Join 500,000+ readers and learn how to use AI in just 5 minutes a day (for free).

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Eddie Hovor 1 Jahr

Let's see how it develops. I don’t doubt AI will outperform on some coding and math tasks - but saying 'it will replace most programmers' skips over all the ambiguity, creativity, and human problem-solving that code and math require, imo.

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Rediminds, Incvor 1 Jahr

It’s not just about replacement, but redefinition. Let AI tackle routine algorithms and verifications, while human experts focus on creativity, system design, and ethical guardrails. Those who design the workflows around these ‘math‑and‑code specialists’ will lead the next wave.

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Markus Odenthalvor 1 Jahr

Interesting. I agree with him that information and math is precise. But the problem is that language isn’t. I would even say it’s the total opposite 😅

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Mickvor 1 Jahr

Let's see what happens. I don't think devs will disappear, they will simply all become prompt engineers. You still need someone to tell the machine what to do.

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Vertexvor 1 Jahr

The “consensus” is fucking STUPID and driven by greed, not science.

Profilbild von 🇯🇲🇧🇧 Eagles really the champs forever.
🇯🇲🇧🇧 Eagles really the champs forever.vor 1 Jahr

just another old man in the way. Glad im diving deep, the human race has no use to counterintuitive ai. We don't have to live in the negative timeline of this

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AHMADvor 1 Jahr

I think at some point AI will be limited to the fact of how today's computing works digitally and start to self improve to work in analog world, (analog-to-analog) with a new form of processing principals Simpler than quantum computing, more power efficient than current computing

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Tom Bennetvor 1 Jahr

One year? Please. The hype cycle's a beast 🚀. It’ll *feel* like replacement, but it’s really just… evolution. Like upgrading from abacus to calculator.

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Permianvor 1 Jahr

"All watched over By machines of loving grace"

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Eric Schmidt, former CEO of Google, offers a sobering view: The biggest technological shift in human history is happening, and almost no one is talking about it. Schmidt opens with a startling industry prediction: "We believe as an industry that in the next one year the vast majority of programmers will be replaced by AI programmers. We also believe that within one year you will have graduate level mathematicians that are at the tippy top of graduate math programs." He explains why this matters so much. Programming and math aren't just two fields among many: "Programming plus math are the basis of sort of our whole digital world." And the AI labs are already using AI to build better AI: "The research groups in OpenAI and anthropic and so forth… around 10 or 20% of the code that they're developing in their research programs is being generated by the computer. That's called recursive self-improvement." Eric Schmidt then lays out the timeline most people haven't grasped: "Within 3 to 5 years we'll have what is called general intelligence AGI which can be defined as a system that is as smart as the smartest mathematician physicist artist writer thinker politician." He gives this belief system a name: "I call this by the way the San Francisco consensus because everyone who believes this is in San Francisco it may be the water." But the truly unsettling part comes next. Once AI starts improving itself, humans become optional to the process: "The computers are now doing self-improvement… they don't have to listen to us anymore. We call that super intelligence or ASI… computers that are smarter than the sum of humans. The San Francisco consensus is this occurs within six years." And here's where Schmidt sounds the alarm. The conversation isn't keeping pace with the technology: "This path is not understood in our society. There's no language for what happens with the arrival of this. This is happening faster than our human that our society, our democracy, our laws will address." His closing thought captures why this matters: "That's why it's underhyped. People do not understand what happens when you have intelligence at this level which is largely free."

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Eric Schmidt, former Google CEO, on why top programmers won't be replaced by AI, they'll be amplified by it: He starts with an observation about the existing hierarchy in software: "The very top programmers were worth 10 times more than the ones right below. There's something special about the mathematical reasoning skills of programmers." Rather than flattening that gap, he argues AI will widen it: "Those people will become more valuable, not less valuable, because these systems need to be controlled by humans at the moment. Those people will be capable of grasping the parallelization and the activities of this." To show what this amplification actually looks like in practice, Eric shares a story from a startup he's involved with. He was talking to one of the programmers there, who works on UIs, about his daily workflow: "He said, 'I write the spec of what I want and then I write a test function, an evaluation function. And then I turn it on.' I said, 'What time?' And he goes, '7:00 in the evening.' And I go, 'Okay. What do you then do?' Well, he has dinner with his wife and he goes to sleep." Eric continues: "I said, 'Do you wake up?' Said, 'No, I sleep very well.' 'When does it finish?' 'Oh, 4:00 in the morning.' And then he gets up, has breakfast, you know, does whatever he does, and then he sees what's been good." Eric Schmidt calls the whole thing "mindboggling." The story captures what amplification really means. The programmer isn't writing less code. He's producing a night's worth of work while asleep, because the machine is running on his spec, his tests, his judgment of what "good" looks like. The leverage belongs to those who can define the problem precisely, write the tests that matter, and recognize good output when they see it.

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