Another problem was the dominance and profitability of rice farming and its hold over the political establishment. Agricultural subsidies kept the economic value of growing paddy and wheat artificially high, which prevented a natural
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“so many people were shocked and upset when, in 1997, IBM’s Deep Blue chess-playing system defeated the world chess champion Garry Kasparov. This event so stunned Kasparov that he accused the IBM team of cheating; he assumed that for the machine to play so well, it must have received help from human experts.2 (In a nice bit of irony, during the 2006 World Chess Championship matches the tables were turned, with one player accusing the other of cheating by receiving help from a computer chess program.3) Our collective human angst over Deep Blue quickly receded. We accepted that chess could yield to brute-force machinery; playing chess well, we allowed, didn’t require general intelligence after all. This seems to be a common response when computers surpass humans on a particular task; we conclude that the task doesn’t actually require intelligence. As John McCarthy lamented, ‘As soon as it works, no one calls it AI any more.’4”
― Artificial Intelligence: A Guide for Thinking Humans
― Artificial Intelligence: A Guide for Thinking Humans
“Should my Modern Turing Test for the twenty-first century be met, the implications for the global economy are profound. Many of the ingredients are in place. Image generation is well advanced, and the ability to write and work with the kinds of APIs that banks and websites and manufacturers would demand is in process. That an AI can write messages or run marketing campaigns, all activities that happen within the confines of a browser, seems pretty clear. Already the most sophisticated services can do elements of this. Think of them as proto–to-do lists that do themselves, enabling the automation of a wide range of tasks. We’ll come to robots later, but the truth is that for a vast range of tasks in the world economy today all you need is access to a computer; most of global GDP is mediated in some way through screen-based interfaces amenable to an AI. The challenge is in advancing what AI developers call hierarchical planning, stitching multiple goals and subgoals and capabilities into a seamless process toward a singular end. Once this is achieved, it adds up to a highly capable AI, plugged into a business or organization and all its local history and needs, that can lobby, sell, manufacture, hire, plan—everything a company can do, only with a small team of human AI managers who oversee, double-check, implement, and co-CEO with the AI.”
― The Coming Wave
― The Coming Wave
“I was an ordinary person who studied hard. There are no miracle people. It happens they get interested in this thing and they learn all this stuff, but they’re just people.”
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“Just consider how terrible the day of your death will be. Others will go on speaking, and you will not be able to argue back.”
― The Argumentative Indian: Writings on Indian History, Culture and Identity
― The Argumentative Indian: Writings on Indian History, Culture and Identity
“In a paper published in 1950, the computer scientist Alan Turing suggested a legendary test for whether an AI exhibited human-level intelligence. When AI could display humanlike conversational abilities for a lengthy period of time, such that a human interlocutor couldn’t tell they were speaking to a machine, the test would be passed: the AI, conversationally akin to a human, deemed intelligent. For more than seven decades this simple test has been an inspiration for many young researchers entering the field of AI. Today, as the LaMDA-sentience saga illustrates, systems are already close to passing the Turing test. But, as many have pointed out, intelligence is about so much more than just language (or indeed any other single facet of intelligence taken in isolation). One particularly important dimension is in the ability to take actions. We don’t just care about what a machine can say; we also care about what it can do. What we would really like to know is, can I give an AI an ambiguous, open-ended, complex goal that requires interpretation, judgment, creativity, decision-making, and acting across multiple domains, over an extended time period, and then see the AI accomplish that goal? Put simply, passing a Modern Turing Test would involve something like the following: an AI being able to successfully act on the instruction “Go make $1 million on Amazon in a few months with just a $100,000 investment.” It might research the web to look at what’s trending, finding what’s hot and what’s not on Amazon Marketplace; generate a range of images and blueprints of possible products; send them to a drop-ship manufacturer it found on Alibaba; email back and forth to refine the requirements and agree on the contract; design a seller’s listing; and continually update marketing materials and product designs based on buyer feedback. Aside from the legal requirements of registering as a business on the marketplace and getting a bank account, all of this seems to me eminently doable. I think it will be done35 with a few minor human interventions within the next year, and probably fully autonomously within three to five years.”
― The Coming Wave
― The Coming Wave
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