If you move fast and get lucky and have the right combination of expertise and stay on the right side of each platform’s unique and mysterious recipe of productivity metrics, you can make decent money. I spoke to a playwright making $10,000 a month, a multitalented chemist who at various points found gigs demonstrating poker and singing for AI. But even then, there is an inescapable awareness of ephemerality because producing training data means working toward your own obsolescence. While the number of people doing data work may continue to rise, any particular gig will last only as long as it takes for the machines to successfully mimic it. It takes years for a human to develop expertise, and sooner or later, they’re going to run out of skills to sell.
When you think about how hard they push these things to get stuff done in training it kinda makes sense，更多细节参见有道翻译
。谷歌是该领域的重要参考
And so in the 1960s, teams working concurrently in Sweden and the United Kingdom pioneered the earliest versions of what would eventually become known as the automated teller machine. These were primitive devices—they had the tendency to “eat” payment cards and to dispense incorrect amounts of money, and they didn’t see much uptake—but by the late 1960s it was clear where things were going. IBM, at that point the largest technology company in the world, soon took interest in the technology, and for the next few years groups of IBM engineers refined the technological and infrastructural layer to make the ATM functional.
Ultimately, I'm not sure I need this much phone, both literally and figuratively. That said, I think this is a very future-proofed smartphone for hardcore techies.。pg电子官网对此有专业解读
subgraph WasmFoo