Industry Developments

Chen Yuanguang was equally delighted to be able to contribute something to the world. "That's good. If the prediction hadn't been accurate, both of us would have been criticized.

Professor, thank you for taking this risk for me." Chen Yuanguang spoke with great sincerity.

If Levitt had not backed him, Science would not have accepted the paper so quickly. Even with MIT's endorsement, not so many people would have attended the online conference, and he would not have had such a good opportunity to spread his ideas.

Chen Yuanguang continued, "Pfizer and Bayer must be confident. Their Broad-spectrum Vaccine was built entirely on our virus prediction model. Our model performed so well that it accurately predicted the mutation sites of these two strains."

Levitt smiled. "That's true. Light, I should be the one thanking you. You produced such outstanding results, while I did not contribute much beyond sharing some information with you.

The virus prediction model is entirely your achievement. I will recommend you for next year's Nobel Prize in Biology."

Only then did Chen Yuanguang realize that he had forgotten Levitt, as a former Nobel Prize winner, was also qualified to nominate candidates. There were very few Nobel Prize nominators with close ties to the Gates Foundation.

"Professor, thank you. I'll remember the help you've given me." Chen Yuanguang spoke earnestly.

Because he knew this was his last chance—not his last chance to win a Nobel Prize, but his last chance to travel to Sweden and receive one in person.

Next year, with the Broad-spectrum Vaccine bringing the virus to an end, he would be surrounded by glory. Since he was doing purely theoretical research, there would be no issue with going to accept the award.

But if he waited until later, until he produced even more influential results—results capable of changing the world—and the Nobel Prize was awarded to him then, he would not dare attend the ceremony.

That was the importance of timing. Miss it, and it might be gone for a lifetime.

"Professor, were you just speaking with Light on the phone?" The person who had been standing beside Levitt waiting for him to finish was his doctoral student, Steven.

Levitt looked at Steven. "Yes."

Steven wore an envious expression. He felt that Levitt cared far more about Chen Yuanguang than he did about the doctoral students under his own supervision.

The difference was like that between a personal disciple and an outer disciple.

Steve sighed. "Several papers just verifying Light's prediction model have already been published in Nature, Science, and The Lancet."

Since Chen Yuanguang's findings had been released, whenever new strains were discovered around the world and sequenced, researchers would compare them against the model.

The model did not necessarily predict every mutation site, but it covered most of them. Moreover, the mutation sites of the strain that ultimately became the most prevalent would always fall within the model's predicted range.

As a result, every sequencing effort could produce a paper. Cambridge had beaten everyone to the sequencing comparison results for the Alpha strain discovered in Britain in September and published them in The Lancet.

Researchers soon realized that publishing papers could be this easy: sequence, compare, and it was done. Everyone began racing against time and building good relationships with virus testing centers. It all came down to who was faster.

Gradually, such results could only be published in second-tier journals, and even then, it depended on how quick one was.

One scholar compiled the sequencing results into a review paper and actually got it published in Nature. That made everyone even more enthusiastic.

In just half a year, Chen Yuanguang's paper had been cited more than two thousand times, becoming the year's most academically influential paper.

Chen Yuanguang had not expected that.

With one good result, everyone could make a living around it.

Steven found that deeply enviable. Top-tier achievements, favored by leading figures, and still young—his buffs had been stacked to the max.

"That is the value of a top-tier researcher.

Euler's manuscripts, achievements, and ideas fed Russia's mathematical community for three hundred years.

The more elite the scientist, the richer the mine.

Chen already has that kind of potential."

Levitt was also moved. He still remembered going to China at the end of the year before last to serve as a judge for a science fiction award. Chen Yuanguang had approached him with such humility that Levitt had assumed he was merely trying to make connections.

But it turned out Chen Yuanguang was a shark himself. In just two years, he had already revealed his sharp edge.

As a Nobel Prize winner, Levitt knew very well that not all Nobel laureates were the same. For some, winning the Nobel Prize was the prize's honor; for others, the Nobel Prize was honored by them.

In Levitt's view, Chen Yuanguang, only in his early twenties, was entirely capable of becoming the latter.

Steven asked, "Professor, have you never considered recruiting Light to Stanford?

Stanford should be able to give him a faculty position easily enough."

At that, Steven showed a strange expression. He did not really want to continue the subject, because he remembered Chen Yuanguang's bizarre reason for refusing him: his friend was in New York.

At the time, Chen Yuanguang's explanation had been that he preferred Bawendi's research direction.

After the two began collaborating this year, Levitt discovered that Chen Yuanguang had equally strong interest and ability in computational biology, so he asked again. Only then did Chen Yuanguang tell the truth: his friend was in New York, and Boston was closer to New York.

Levitt would never forget how he had felt then. It had been as unpleasant as eating canned herring. So his doctoral program was worth less than seeing a friend a few more times.

After Chen Yuanguang created the prediction model, Levitt consoled himself by saying that geniuses were simply like that. Geniuses possessed extraordinary qualities, so naturally their personalities stood out as well.

"I invited him. He may not like Silicon Valley's climate very much." Levitt did not believe that himself after saying it, because California's climate was obviously better than Boston's.

How could Boston's long, bitter winter compare to California's pleasant climate?

He added, "In any case, I invited him, but he doesn't really want to come to Stanford."

Steven guessed inwardly that Chen Yuanguang probably preferred MIT, which was why his professor looked that way.

Steven could never have guessed the real reason.

"So that's how it is. It seems I won't have a chance to meet Light anytime soon. His accomplishments in computational biology are truly astonishing.

I have friends in Silicon Valley. Because of Light's results, many companies focused on combining computational biology and artificial intelligence have emerged there recently, specializing in providing AI services to pharmaceutical companies.

They have hired a group of PhDs in computer science and biology, claiming they will provide a new kind of pharmaceutical outsourcing service.

Pharmaceutical companies like Pfizer, AstraZeneca, and Roche Pharmaceuticals have also begun increasing their investment in AI. Pfizer alone recently placed orders with Nvidia worth more than two hundred million dollars."

Since he planned to enter industry after graduation, Steven paid particular attention to cutting-edge developments in Silicon Valley's biotech sector. They concerned his future career.

He knew the latest developments in Silicon Valley's industrial world like the back of his hand. After listening, Levitt said, "That is indeed the case. Artificial intelligence has obvious advantages in computational biology.

Traditional mathematical modeling can no longer meet the needs of today's academic community. We need new methods and new theories. We now have new methods, but new theories remain a complete blank."