Chapter 142: The True Trump Card Of The Cold War
“Hello everyone, in 1951, Professor Turing proposed in his BBC radio lecture and article ‘Intelligent Machines’ that machines might eventually surpass human intelligence.
Professor Gude believed computers would experience an intelligence explosion, feeling that a machine far surpassing all human intellectual activities would emerge.
In my view, this is indeed possible.
Whether America or the Soviet Union ultimately wins the Cold War does not depend on the space race, but on who invents such a machine first.
When an artificial intelligence machine far surpasses any smartest human in all intellectual activities, machine design and manufacturing are themselves part of these intellectual activities.
Then this machine will design better machines itself, and human wisdom will be far left behind.
Even without waiting until that time, if artificial intelligence can assist human scientists in research and development, our technological development will usher in an era of big explosion.
IBM’s chess program is living proof. It can defeat most humans in chess.
However, this is just the beginning.
Imagine such a world: this intelligence applied to medicine, curing previously incurable diseases; applied to engineering, solving problems humans cannot reach; applied to education, unlocking knowledge for everyone; applied to national security, protecting our way of life.
The possibilities of artificial intelligence are infinite.
In my view, the development of artificial intelligence is not just a scientific endeavor; it is a competition that determines a country’s fate.
The key to true victory does not lie in who steps on the moon first, but in who first unlocks the full power of artificial intelligence and ushers in the technological singularity.
The country that first reaches this singularity will master the dominance of the future.”
After Lin Ran finished speaking, discussions erupted in the audience.
To put it bluntly, Lin Ran’s viewpoint is actually Professor Gude’s future viewpoint.
First, Gude was just a professor in England, and his views were only noticed by science fiction novel writers.
Second, because artificial intelligence lacked a sufficient discussion window, it was not fully recognized by the public for its importance.
At this time, Lin Ran, relying on IBM’s Deep Blue and the future IBM exhibition hall in Times Square, provided such a window.
Defining who wins the Cold War, coming from Lin Ran’s mouth, has a completely different level of importance.
Why did Lin Ran give Korolev that paper converting the non-convex optimization problem into a convex optimization problem? This paper is one of the cornerstones for SpaceX to achieve the reusable rocket.
Precisely to let Korolev, with the help of this paper, achieve manned moon landing ahead of time.
Lin Ran’s words were already extremely weighty, and after the Soviet Union takes the lead in manned moon landing, America’s media, in order to redefine winning studies, will naturally pick up his words again.
Losing manned moon landing is fine; our true decisive battle will come with the technological singularity brought by artificial intelligence.
And if the Soviet side can keep up in the semiconductor field and go all-in, with the unique technological aesthetics of the Russians, it is highly probable to develop a completely different semiconductor technology route for you.
Thoroughly unleashing the potential in the semiconductor field in the 1960s is one of Lin Ran’s real purposes.
What Lin Ran didn’t expect was that the reporters in the audience burst out with unprecedented enthusiasm.
“Professor, can you talk more about the technological singularity?”
“Professor, when do you think we can build such a machine?”
“Professor, does the White House’s viewpoint align with yours?”
The reporters’ questions were about to completely ignite the entire venue.
Lin Ran pressed his hands down, “Quiet, let’s finish watching the next two games first.”
The second player was Harvey Cohen.
He walked onto the stage full of confidence, sitting next to him was his student, while Chen Jingrun frantically mobilized his brain, memorizing everything Lin Ran had just said, to pass these words back home.
Chen Jingrun felt like he was turning into a memory master.
When Harvey Cohen began playing against Deep Blue, the focus in the venue finally returned to the stage, not on Lin Ran.
Lin Ran squeezed Jenny’s hand, and the two sneaked out through the side door.
“Professor, you should save the time for your exclusive interview for me, right?” Jenny’s eyes sparkled as she hurriedly asked.
Lin Ran nodded: “Of course.”
The chess match in the hotel was still continuing.
Harvey Cohen didn’t persist much longer than Fox.
By the time Harvey Cohen was defeated, the reporters realized Lin Ran had already disappeared.
Everyone had no choice but to focus on Alex Bernstein and Thomas Watson; your news value is not as good as Lin Ran’s, but something is better than nothing.
Who is Thomas Watson? IBM’s CEO, he is also the son of IBM’s founder, and his ability to control the scene is not low either.
“Everyone calm down, Mr. Bernstein and I will fully accept interviews from everyone; let’s first complete the last chess game, we still have time,” Watson said.
Under the joint recommendation of many mathematicians, the last player to take the stage was Stephen Smale.
Indeed, the mathematicians really couldn’t accept it: in the evening there were only three human-machine chess matches in total, and the mathematician group lost all of them.
Although they were not chess champions or any chess experts, they also couldn’t accept a complete defeat.
And Stephen Smale was the strongest chess player among the mathematicians present, publicly recognized by everyone.
Unfortunately, in the end, he still fell short by one move.
Stephen Smulders sat in front of the chessboard, this time there was no Lin Ran to comfort him, and he was reluctant to step down for a long time.
Bernstein walked up to him: “Professor.”
Trying to remind Stephen to come back to his senses in this way.
Stephen Smulders was still savoring the previous chess game, “Mister, can you let me play one more game with him?
I was too hasty just now, I was so close, I could have won!”
Bernstein
Stephen Smale looked annoyed, grabbing his hair with his hand as he walked off the stage. Smale’s hair was quite thick.
(Stephen Smale 2008 photo)
“Stephen, you’re no good either!” Seeing Stephen lose, the happiest was Professor Fox.
“Don’t shout! I couldn’t beat Deep Blue, but can’t I beat you?!” Stephen Smulders was already annoyed, and seeing his defeated subordinate shouting made him even more annoyed.
Fox said: “Come on, come on, let’s play a game. Who’s afraid of whom!”
Stephen Smale said: “Come on then.”
Professor Fox added: “But you have to let me have a car.”
Stephen Smale was speechless: “I even give you two stones in Go, and you want a rook in chess?”
However, they obviously have no opportunity to play against each other tonight.
Because the reporters’ interviewees included not only Bernstein and Watson, but also these mathematicians who had played against Deep Blue.
“Professor Fox, why did you lose to Deep Blue?”
Quick-reacting reporters had already gathered around.
Ralph Fox said: “It’s mainly due to lack of experience. The first time playing against a machine, it’s easy to get nervous.”
Even Stephen Smale, who was listening nearby, couldn’t help but roll his eyes.
“Professor Fox, if there is a next time, do you think you can beat Deep Blue?” the reporter continued.
Fox was very confident: “Of course.”
What he was actually thinking in his heart was that I would never play against Deep Blue again.
“Professor Fox, how did it feel to play against Deep Blue?” the reporter asked next.
Fox thought for a moment: “You will have a very obvious feeling that you are playing against a machine.
The computation time for each step is almost constant, and then you can’t see the person, only the pieces moving on their own. This feeling is very peculiar, something that has never happened before.”
It’s just that current technology can’t achieve it. Lin Ran initially wanted to make a mechanical arm, which would have a better effect.
However, IBM has tried many times, but technically it really cannot achieve this precision.
At present, for a mechanical arm to accurately pick up a pawn and place it in the corresponding position on the chessboard, it not only requires sufficiently high sensitivity from the sensor, but also visual recognition capability.
That’s a bit too advanced.
And the reporters gathered around Bernstein and Watson, everyone’s questions were all focused on the technological singularity that Lin Ran mentioned.
“Mister Watson, do you agree with the professor’s viewpoint?”
“Yes, I strongly agree. From the abacus to the calculator and then to today’s computer, the help that machines can provide to human scientific research has greatly improved.
If it continues to develop at this rate, machines that can provide greater help will eventually appear someday.
When such a machine appears, the side possessing such a machine will gain an unprecedented leading advantage.
Can you imagine how terrifying it would be if every researcher was equipped with similar machines, allowing them all to perform at the same level as the professor?
“If NASA has over ten thousand engineers, and each engineer’s ability is similar to that of a professor, then our goal would probably not just be the Moon, but the entire Solar System.”
Watson was animated, the reporters taking notes in their notebooks while listening with eyes gleaming.
Some reporters have even come up with the front-page headline title for tomorrow, called:
“Technological singularity, everyone is Randolph”
“Watson, who do you think will invent a similar machine first? Is it IBM, Texas Instruments, General Electric, Bell Communications, or some other company?”
“Of course it’s IBM. We have already led all other companies in the Artificial Intelligence field.
We also have a trump card; we have a close cooperative relationship with the smartest brain on Earth right now.
“Why did the professor choose to cooperate with IBM instead of other companies? Isn’t it precisely because we have the best engineer team, with the deepest technological accumulation and reserves in the artificial intelligence and computer field?”
Watson spoke eloquently, convincing even himself.
He was already looking forward to IBM’s surge after the US Stock Market opened.
IBM was listed on the New York Stock Exchange as early as 1916, but at that time its name was not IBM; it was called Computing-Tabulating-Recording Company, and it was not renamed International Business Machines Corporation, or IBM, until 1924.
Thanks to the booming development of computers, IBM’s stock price is now very high. Calculated at that time’s price, it exceeds 400 US dollars per share.
It is also precisely because of such a high price that IBM’s stocks have undergone more than one split.
“Mister Watson, will you invite the professor to join IBM?”
“Of course, if the professor is willing, I’m even ready to offer him the CEO position,” Watson said.
He knew how much of a boon this would be for a technology company, and what kind of help it would provide.
Bell could help Bell Telephone become a colossus, Edison could lay the foundation for Edison Electrical to become General Electric, and Lin Ran’s value was no less than theirs—only higher.
“Mr. Watson, regarding the Deep Blue exhibition hall, will IBM consider selling Deep Blue as a product in the future?” the reporter continued to ask.
“We will consider it. We will make a judgment based on market demand.
But what can be said for sure is that once it is put on the market for sale, its price will not be affordable for ordinary consumers.”
The questions thrown at Bernstein focused on Deep Blue itself:
“Mr. Bernstein, since Deep Blue didn’t lose a single game today, can it defeat all human players?”
“Not yet. It still has limitations. After all, the professors are just amateur chess enthusiasts, and Deep Blue’s level is roughly equivalent to an expert among amateur enthusiasts.” Bernstein remained very low-key.
“So, when do you think it can defeat all humans?”
“I’m not certain, but I think five years should be enough,” Bernstein said.
“Mr. Bernstein, do you agree with the professor’s view on the technological singularity of artificial intelligence technology?”
“Of course. I hope to find that technological singularity.”
If the interview in the high-end Manhattan hotel seemed chaotic, then the exclusive interview Jenny conducted with Lin Ran was filled with an ambiguous atmosphere.
Last time, Lin Ran had sent Jenny to the Clarendon Building in Manhattan’s Upper West Side owned by the Hearst family, where the Hearst family had connected the top five floors into an aerial villa. He had never been up there.
This time, Lin Ran went to Jenny’s own private residence, a super-large apartment on the edge of Central Park with a view overlooking the entire New York Central Park.
They leaned on the sofa. Jenny had already changed into silk pajamas, the heating was turned up high, with a notebook on her lap and red wine on the table in front of them.
Lin Ran felt the atmosphere was very ambiguous, but the conversation was extremely serious.
“Professor, congratulations on Deep Blue defeating a human player. Does this victory mean that machines have surpassed humans?”
“Of course not. This is just proof to the public that computers have infinite potential—they are the future.”
In this interview, Lin Ran hoped to express his true ideas as much as possible.
He knew that what he said would surely cross the ocean and land on the desks of every relevant person in Yanjing.
He didn’t expect the artificial intelligence competition he initiated to make China the winner.
Because there was no possibility of a winner at all.
Neither America nor the Soviet Union could win.
Especially since Lin Ran also planned to guide them as much as possible toward technological paths that did not exist in the spacetime of the 20th century.
This made it even more impossible for there to be a winner.
What he hoped for was that China would take it seriously, with external pressure bringing internal unity.
Laying a sufficiently complete foundation for his return to China.
It didn’t need to be very advanced—just complete.
Just like China’s industrial system in the future: completeness means infinite potential.
“Professor, how did you come up with the idea to create a chess artificial intelligence program?” Jenny asked.
“I’ve always believed computers have enormous potential. I saw in a magazine that IBM had once made a chess program, so I thought of cooperating with them.
To try creating a more powerful chess artificial intelligence program. I’m glad we succeeded.
We need to awaken the public’s awareness and expectation of artificial intelligence. This relates to whether the free world can win the Cold War!” Lin Ran looked serious, his tone firm.
This version of Lin Ran surprised Jenny somewhat.
Because in her impression, Lin Ran had always been a calm and rational scientist with limited aversion to the Soviet Union, and she had hardly heard his views on the free world or ideological matters.
As a quasi-philosopher, this was actually very rare.
Jenny had even once suspected that he had a favorable view of the Soviet Union.
Now hearing Lin Ran mention victory for the free world.
She was very surprised.
It felt out of place, like Musk suddenly getting involved in politics.
Jenny asked seriously, “Professor, do you really think the ultimate victory in the Cold War will be decided by artificial intelligence?”
Lin Ran nodded and said, “Of course, and we don’t even need to wait for artificial intelligence.
We don’t yet have sufficient understanding of the power of computers.
Our understanding of how computers can help the Soviet Union is even more insufficient.
Put it this way: as a colossal command-type planned economy, the Soviet Union’s economy is entirely formulated by Moscow’s bureaucrats.
We would accuse this allocation mechanism of being rigid and unrealistic.
That’s because their computational power is insufficient; they can’t build models that fit the real world closely enough.
But computers can help them make up for this shortcoming. Can you imagine computers precisely calculating the materials needed by every Soviet person, the materials they consume, and then statistically allocating them precisely to every factory responsible for production.
Humanity cannot achieve this, but computers can.
It does not even require computers and artificial intelligence at the level of the technological singularity. As long as the Soviet Union can build computers capable of precisely handling domestic materials allocation, it would be a huge threat to the free world.
By that time, while we are talking about trade flows in the free world, they can respond with efficient and precise resource application.
This is not good news at all.
Don’t wait for Reagan to start Star Wars; Lin Ran will first give you a Star Wars in the computer field.
It is still Nikita now, not Leonid yet.
To be precise, in the early days of Leonid, the Soviet Union was not yet rigid to the point of being unable to move.
So Lin Ran needs to turn up the intensity for them.
If the Soviet Union really builds a massive commodity allocation network through computers, it will be an entirely new social form.
cybernetic socialism
It is not that no one in the Soviet Union has thought of this.
Whether it was Viktor Glushkov proposing OGAS in the 1960s, aiming to establish a national computer network to collect data in real time and optimize resource allocation, simulating economic activity through networked computers to reduce inefficient allocation patterns.
Or later Leonid Kantorovich developing linear programming theory, attempting to optimize resource allocation mathematically, and applying it in some factories.
The Soviet Union has made no shortage of similar attempts.
It is just that the internal resistance was too great; by the time they realized they could do this, it was already too late.
And the external pressure was not enough.
After Lin Ran proposes it, with the White House fanning the flames and the media amplifying it.
Coupled with Lin Ran’s status, ability, and vision, it is possible to leverage the Soviet Union into attempting to build a union-wide computer allocation network.
Even if it ultimately fails, the Soviet Union will definitely increase its investment in computers, lighting up a tech tree different from that of the Western free world.
“Professor, do you think America can win this technological singularity race?” Jenny became tense after hearing this.
As a former Geneva international news reporter, she knows the Soviet Union very well.
As an old family, the rejection of the Soviet Union is instinctive.
If the Soviet Union really wins, would the Hearst family still have so much wealth now?
People like Engels are too rare.
“I don’t know, but I believe America can win,” Lin Ran said.
“Professor, could you elaborate more on your viewpoint about the technological singularity?” Jenny asked next.
What Lin Ran said at the Christmas party was very brief.
“Of course.
Computers have powerful computing ability and have already demonstrated their strong capabilities in many aspects in the past.
Currently, it is mainly focused on solving mathematical equations.
From the abacus that could only do addition and subtraction, to the calculator that could do addition, subtraction, multiplication, and division, to today’s computers that can solve complex equation systems, calculus, and even linear equations.
The development of tools is rapid, and the help it provides to human scientific research is enormous.
And today at the party, we can see Deep Blue’s ability boundary expanding from mathematical calculation to chess games.
Its ability will expand.
So in the future, can it do more things?
When physical phenomena can be explained by mathematical models, similarly, when real-world problems can be broken down into numbers understood by computers, computers will certainly be able to help provide solutions to real-world problems.
When sufficiently powerful computers appear, everyone can become an expert scholar through computers, so whoever builds such computers first will see explosive growth in their technology.
And this growth speed may be so terrifying that latecomers can never catch up.
Our current research and development of manned moon landing takes at least ten years; if someone develops such sufficiently powerful computers and corresponding artificial intelligence first, it might take only one year.
More importantly, this technological explosion will also feed back into the research and development of computers and artificial intelligence; the essence of the technological singularity is snowball rolling.
The first mover will roll the snowball bigger and bigger, and the gap between the two sides will never narrow but only widen.
And whoever achieves the technological breakthrough first can start snowball rolling first.
Just like what I said in my hotel speech, this is the true winning move in the Cold War showdown.”
After the interview ended, Lin Ran stood up to return to his apartment.
Jenny called out to him: “Professor, aren’t you forgetting something?”
“What?” Lin Ran did not dare to turn back.
“Last Christmas Eve, you gave me an apple and said it was a tradition among Chinese people. I later asked people of Chinese descent, and other people of Chinese descent don’t have this tradition?
And why didn’t you give me an apple on this Christmas Eve to wish me peace in the new year?”
A total of 10,000 words offered!
