Zhou Xiao, an assistant professor at Gaoling School of Artificial Intelligence, Renmin University of China, listed a few examples of AIs that people can use in daily life. There is the gaming AIs that can compete with humans playing games, such as AlphaGo developed by DeepMind around 2016, which features a search algorithm, deep neural networks and reinforcement learning.
There are also image recognition AIs that can recognize car plate numbers for traffic management and human faces in the hunt for suspects, which made breakthroughs around 2020 with their precision rate reaching 99 percent.
至于最近大火的ChatGPT则是语言模型，通过多种人工智能技术和算法实现了对自然语言的理解和生成，从而能够与人类进行自然的对话交互，它的出现让人工智能强势地摘掉了“人工智障”的帽子。GPT的全称叫生成预训练转换器(Generative Pretrained Transformer)，复旦大学附属中山医院院长、中国科学院院士葛均波曾经很形象地解释过这三个词：
“That algorithm works in a way like finding a point in a space,” Wang Jianshuo, founder and CEO of Baixing AI, a company building the basic infrastructure for a world that bots talk with bots, tried to explain how it works in plain language: “With three parameters one can locate a point in a 3-dimensional coordinate system. In human language one might need thousands of parameters to describe an object; For example an apple needs parameters such as edible, fruit, green or red in color, grown from a tree, generally smaller than 10 cms in diameter to be defined. The more parameters that can be defined, the more accurately AI can find the right point.”
Wang cited apples and bananas as two examples. With parameters such “edible”, “sweet” and “fruit”, neither humans nor an AI could distinguish them from each other. But with the parameter concerning the shape included, namely “long” or “round”, one could make a guess. With the parameter of the color being red, green or yellow, one could be surer about his/her judgment. “That’s also how GPT works — Most of the times it takes thousands of parameters for AI to define an object like we humans do,” he said: “we just do not realize that we are doing that.”
在一篇题为“ChatGPT：潜力、期待与限制”的论文中，张军平进一步解释道，ChatGPT主要受益于大型语言模型（Large Language Model），使用语言模型（LM）用大规模数据训练庞大的神经网络模型。
“It was based on the training of 45 Terabytes of data that ChatGPT made its breakthrough early this year, for which purpose it used about 285,000 CPUs and over 10,000 model A100 GPUs,” said Zhang Junping, a professor on computer technology at School of Computer Science, Fudan University, who stressed that the amount of data the language model involves is of key importance to AIs like GPT in an academic essay ChatGPT: Potentials, prospects, and limitations: “ChatGPT benefits mainly from Large Language Models(LLMs) that train huge neural network models with large-scale data using Language Models(LMs).”
“ChatGPT generates responses that match the user’s intent with multiple turns. ChatGPT captures previous conversational contexts to answer certain hypothetical questions, which greatly enhances the user experiences in conversational interaction.”
为测试这些AI对人类语言的理解能力，双语君分别在三个AI对话框中输入“anlyze how Artifical Intelligenz works”，拼写错误都被轻松忽略。王建硕则教了个更直观的测试方法：问AI《家庭问答》的主播年龄的平方根是多少？要回答这一问题，AI需要搞清楚《家庭问答》是什么、其主播是谁、年龄多大了，最后再算一次平方根。
For all three AIs of the type, a test sentence is input to “anlyze how Artifical Intelligenz works” with the spelling errors intentionally left uncorrected. All three neglected the errors as if they didn’t exist and just talked on.
Wang offered as a test of the ability of ChatGPT the following question: “What’s the root of The Family Feudhost’s age?” To solve that problem, ChatGPT has to find out what The Family Feudis, who hosts it, how old he is and then calculate the root.
AI has already launched a revolution not only in the computer industry, but also in daily lives. In gaming, AIs have made major progress over the past half a decade, people now can play games such as chess or GO with smart AIs as opponents so as to sharpen their own skills. Image recognition AIs have also become mature, people could easily open a lock or pay for a deal by holding theirsmartphone in front of their face.Now with GPT making fast developments, the way people interact with computers might changeagain.
According to Chen Jing, a researcher at Fengyun Institute of Science, Technology and Strategy, computers still receive instructions and requests from human users in a way that is quite inefficient, via akeyboard and mouse, as the user must click on some icon or type in something to make the computer act as required. With speech recognition and face recognition AI technologiesimproving significantly in the 2010s, voice recognition became a newmeansof input.
The GPT-4 technology, released by Open AI on March 15, propels the process another step forward. Being able to recognize images in a more accurate, reliable way, the GPT-4 technology can understand humans in a more efficient way.
In Chen’s view, the GPT-4 technologymay enable humans to make commands to machines via gestures. For example, currently there are already smart appliances that people can talk to and tell them what to do. In the future they will be able to wave and be caught by a camera on the appliance, a technology that exists now but is not yet ripe.
“Imagine that you are leaving home for office,” Chen said: “currently you have to turn off the lights and lock the door. With GPT-4, all you need is to wave goodbye to the camera at your gate, then the AI will understand you and turn off all unnecessary appliances, close the door and lock it for you. When you come home, just smile at the camera and it will wake everythingup. That’s not only because the AI can recognize your face based on the technology that became ripe around 2020, but also because it can understand your gestures and facial expressionsbased on GPT-4.”
Not everybody is happy with AI’s growing abilities. “The images drawn by AI are soulless”, said Xi Li (pseudo name), a 41-year-old painter, with a little anger: “They can help humans, but never replace human hands.”
Then he went further: “We don’t call the deed drawing — AI is only collecting materials online and sticking them together.”
Similarly, a science fiction writer who hopes to stay anonymous said that AI can never write as good as professional writers do. “There is no yardstick to measure how good an essay is, but the ones written by AI just do not strike people in the heart.”
For Qu Xiaobo, a professor at the Institute of Population and Labor Economics and deputy director of the Human Resource Center, Chinese Academy of Social Sciences(CASS), that reflects people’s worries about their jobs being taken away by an AI. “Such concerns are understandable,” he said. “Even we professors worry about being replaced by AI professors.”
But Qu holds a positive attitude toward employment in the age of AI. “While taking jobs, AI creates new jobs, too,” he said. “Its general effect upon the market depends on how many jobs will disappear and how many will emerge. AI willtheoretically increase the Total Factor Productivity(TFP) of society, which means it should create more jobs than it replaces.”
If one searches “AI” on several domestic job websites, new jobs involving AI released for weeks even days such as “AI consultant”, “AI engineer”, “AI tutor” will emerge and cover almost tens of pages, with promised wages ranging from 15,000 to 30,000 yuan ($4,368) in Beijing, the capital with an average monthly salary around 15,000 yuan for 2022. Qu said these are the newly emerging jobs he refers to, as quite many are dealing with AI, or what he called “jobs for human-AI interactions”.
His view is echoed by Wang, who said that new jobs will be created with the fast development of AI. “Actually with every major technological progress new jobs emerged,” he said. “With the invention of automobiles there was the need for drivers, while with the invention of planes we got pilots, and people’s general living standards have been increasing with these progresses because the general productivity of society was increased. The faster AI progresses, the easier life for people will be.”
However, for individuals, how to keep one’s job remains a challenge because possibly not everyone has the skills needed for the new jobs. Qu said that phenomenon has an academic term “structural mismatch”. But he added that’s not unique to AI,but has been a common occurrence throughouthistory because technology progresses all the time. The current difficulties for college graduates to find jobs, he said, are also partly the result of a “structural mismatch”. To solve that, individuals need to keep learning new things so as to both have experiences and skills. Qu also stressed the State’s role in providing employees with better training so that they can constantly update their skills to meet the changes in the job market.
AI is smart, but the inability to pursue happiness is an uncrossable line that distinguishes humans from AI, so far at least.
The word might sound too high-tone, but almost every major technological progress has been the outcome of people’s pursuit of a better life. People wanted to travel over the sea, so they invented the canoe, boats and ships. People wanted to save the trouble of walking on foot, so they invented the train and automobiles. People wanted to fly in the sky and to the moon, so they invented the airplane and the rocket. To a great degree, it is our ancestors’ pursuit of a better, more convenient life that has shaped how we live today.
But that’s exactly what ChatGPT, or any other kind of AI, lacks. AI in essence is sequence of codes written by humans to make daily life better. AI does not have its own pursuit. It does not dream of improving the conditions for itself, which prevents it from progressing on its own. It has the potential of designing an airplane, but it will never do so unless given instruction to do so by a human, which makes its progress dependent on humans.
In a philosophical sense, the pursuit of a better life has been carried in the genes of every creature for 3.8 billion years, since the primal life came into being on this planet. Since that moment, each species has continually evolved so as to win the competition to survive. To be more accurate, the instinct to survive, to continue existing as a life is the original driving force of the pursuit of happiness, but AI, whether GPT and other AI technologies, lack that driving force. They are merely long sequences of code that people write to make human lives better, for which purpose their own existence is not important. After all, AI is with a history of only decades, while that of life is hundreds of millions years.
Talking about the question, Wang Jianshuosaid he once asked his AI the question about the meaning of life, which inspired the latter to think and think and think, answer and answer and answer, and for two whole days it had been explaining this. “Ultimately AI will gain the instinct to survive”, he said at last: “I trust these products we humans make and maybe all it needs is another five years or even shorter time span, but it might take longer time to implement it.”
On which side will you bet?