Kai-Fu Lee Quotes

In the story of AI and humans, if we get the dance between artificial intelligence and human society right, it would unquestionably be the single greatest achievement in human history.

Regardless of these theories, I believe it’s indisputable that computers simply “think” differently from our brains.

AI will do the analytical thinking, while humans will wrap that analysis in warmth and compassion.

Robotics, however, is much more difficult. It requires a delicate interplay of mechanical engineering, perception AI, and fine-motor manipulation. These are all solvable problems, but not at nearly the speed at which pure software is being built to handle white-collar cognitive tasks. Once that robot is built, it must also be tested, sold, shipped, installed, and maintained on-site. Adjustments to the robot’s underlying algorithms can sometimes be made remotely, but any mechanical hiccups require hands-on work with the machine. All these frictions will slow down the pace of robotic automation.

To the AI, such things were a matter of math, not love.

Over the years, I have learned that if each country could understand the other’s history, culture, and viewpoint, and accept that there are some issues that the two countries will “agree to disagree”, there would be tremendous progress. I have come to really like the wise Chinese proverb “yi zhong qiu tong,” which means seeking common ground while accepting differences. This is precisely the mindset that both countries need.

instead of being mission-driven, Chinese companies are first and foremost market-driven. Their ultimate goal is to make money, and they’re willing to create any product, adopt any model, or go into any business that will accomplish that objective.

Imagine, a $1,000 political assassin! And this is not a far-fetched danger for the future, but a clear and present danger.

When Sergei Brin and Larry Page founded Google in 1998, just 0.2 percent of the Chinese population was connected to the internet, compared with 30 percent in the United States.

I want to create a system that provides for all members of society, but one that also uses the wealth generated by AI to build a society that is more compassionate, loving, and ultimately human.

So, is 100-percent detection of deepfakes hopeless? In the very long term, 100-percent detection may be possible with a totally different approach — to authenticate every photo and video ever taken by every camera or phone using blockchain technology (which guarantees that an original has never been altered), at the time of capture. Then any photo loaded to a website must show its blockchain authentication. This process will eliminate deepfakes. However, this “upgrade” will not arrive by 2041, as it requires all devices to use it (like all AV receivers use Dolby Digital today), and blockchain needs to become fast enough to process this at scale.

Ray Kurzweil — the eccentric inventor, futurist, and guru-in-residence at Google — envisions a radical future in which humans and machines have fully merged. We will upload our minds to the cloud, he predicts, and constantly renew our bodies through intelligent nanobots released into our bloodstream. Kurzweil predicts that by 2029 we will have computers with intelligence comparable to that of humans (i.e., AGI), and that we will reach the singularity by 2045.

When I launched my AI career in 1983, I did so by waxing philosophic in my application to the Ph.D. program at Carnegie Mellon. I described AI as “the quantification of the human thinking process, the explication of human behavior,” and our “final step” to understanding ourselves. It was a succinct distillation of the romantic notions in the field at that time and one that inspired me as I pushed the bounds of AI capabilities and human knowledge.
Today, thirty-five years older and hopefully a bit wiser, I see things differently. The AI programs that we’ve created have proven capable of mimicking and surpassing human brains at many tasks. As a researcher and scientist, I’m proud of these accomplishments. But if the original goal was to truly understand myself and other human beings, then these decades of “progress” got me nowhere. In effect, I got my sense of anatomy mixed up. Instead of seeking to outperform the human brain, I should have sought to understand the human heart.
It’s a lesson that it took me far too long to learn. I have spent much of my adult life obsessively working to optimize my impact, to turn my brain into a finely tuned algorithm for maximizing my own influence. I bounced between countries and worked across time zones for that purpose, never realizing that something far more meaningful and far more human lay in the hearts of the family members, friends, and loved ones who surrounded me. It took a cancer diagnosis and the unselfish love of my family for me to finally connect all these dots into a clearer picture of what separates us from the machines we build.
That process changed my life, and in a roundabout way has led me back to my original goal of using AI to reveal our nature as human beings. If AI ever allows us to truly understand ourselves, it will not be because these algorithms captured the mechanical essence of the human mind. It will be because they liberated us to forget about optimizations and to instead focus on what truly makes us

China lagged years, if not decades, behind the United States in artificial intelligence. But over the past three years China has caught AI fever, experiencing a surge of excitement about the field that dwarfs even what we see in the rest of the world. Enthusiasm about AI has spilled over from the technology and business communities into government policymaking, and it has trickled all the way down to kindergarten classrooms in Beijing.

Each of the three recognized categories — care, service, and education — would encompass a wide range of activities, with different levels of compensation for full- and part-time participation. Care work could include parenting of young children, attending to an aging parent, assisting a friend or family member dealing with illness, or helping someone with mental or physical disabilities live life to the fullest. This category would create a veritable army of people — loved ones, friends, or even strangers — who could assist those in need, offering them what my entrepreneur friend’s touchscreen device for the elderly never could: human warmth. Service work would be similarly broadly defined, encompassing much of the current work of nonprofit groups as well as the kinds of volunteers I saw in Taiwan. Tasks could include performing environmental remediation, leading afterschool programs, guiding tours at national parks, or collecting oral histories from elders in our communities. Participants in these programs would register with an established group and commit to a certain number of hours of service work to meet the requirements of the stipend. Finally, education could range from professional training for the jobs of the AI age to taking classes that could transform a hobby into a career. Some recipients of the stipend will use that financial freedom to pursue a degree in machine learning and use it to find a high-paying job.