دانلود کتاب اطلاعات مشترک – زندگی و کار با هوش مصنوعی

I believe the cost of getting to know AI—really getting to know AI—is at least three sleepless nights. After a few hours of using generative AI systems, there will come a moment when you realize that Large Language Models (LLMs), the new form of AI that powers services like ChatGPT, don’t act like you expect a computer to act. Instead, they act more like a person. It dawns on you that you are interacting with something new, something alien, and that things are about to change. You stay up, equal parts excited and nervous, wondering: What will my job be like? What job will my kids be able to do? Is this thing thinking? You go back to your computer in the middle of the night and make seemingly impossible requests, only to see the AI fulfill them. You realize the world has changed in fundamental ways and that nobody can really tell you what the future will look like. Though I am not a computer scientist, I am an academic studying innovation who has long been involved in work on the applications of AI, especially for learning. Over the years, AI has promised much more than it has delivered. For decades, AI research has always seemed to be on the edge of a massive breakthrough, but most practical uses, from self-driving cars to personalized tutoring, always advanced grindingly slowly. During this time, I kept experimenting with AI tools, including OpenAI’s GPT models, figuring out ways to incorporate them into my work, and assigning my students to use AI in class. So my sleepless nights came early, just after the release of ChatGPT in November 2022. After only a couple of hours, it was clear that something huge had shifted between previous iterations of GPT and this new one. Four days after the AI was launched, I decided to demonstrate this new tool to my undergraduate entrepreneurship class. Barely anyone had heard of it. In front of my students, I put on a show, demonstrating how AI can help generate ideas, write business plans, turn those business plans into poems (not that there is a lot of demand for that), and generally fill the role of company cofounder. By the end of the class, one of my students, Kirill Naumov, had created a working demo for his entrepreneurship project—a Harry Potter–inspired moving picture frame that reacted to people walking near it—using a code library he had never used before, in less than half the time it would otherwise have taken. He had venture capital scouts reaching out to him by the end of the next day. Within two days of introducing students to AI, several told me they used ChatGPT to explain confusing concepts to them “like they were ten years old.” They stopped raising their hands as much—why expose themselves in class when they could just ask the AI later? And every essay was suddenly written with perfect grammar (though references were often wrong and the final paragraph tended to start with “In conclusion”—a telltale sign of early ChatGPT writing, since fixed). But the students weren’t just excited, they were nervous. They wanted to know the future. Some of them asked me what it means for their preferred careers (“Should I become a radiologist if AI can do a lot of the work?” “Will writing marketing copy still be a good job five years from now?”). Others asked when this technological development would stop, or if it would stop. Someone even asked if Artificial General Intelligence (AGI), the hypothetical machine that would be smarter than a human, might arrive before graduation.