Industry Dynamics

Chen Yuanguang was also very happy to be able to contribute to the world. "That's good. If the prediction hadn't been accurate, we both would have been criticized.

Professor, thank you for taking a risk for me." Chen Yuanguang said sincerely.

If Levitt hadn't stood up for him, the Science paper wouldn't have been accepted so quickly, and even with MIT's endorsement, not many people would have attended the online meeting, and he wouldn't have had such a good opportunity to preach.

Chen Yuanguang continued, "Pfizer and Bayer must have confidence. Their broad-spectrum vaccine is entirely based on our virus prediction model. Our virus prediction model has performed so well, accurately predicting the mutation points of the virus strains in these two instances."

Levitt smiled and said, "That's true, Light. I should be thanking you. You've achieved such excellent results. I didn't help much, just shared some information with you.

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

Only then did Chen Yuanguang realize that he had forgotten that Levitt, as a former Nobel Prize winner, also had the qualification to recommend candidates, and there were few Nobel Prize recommenders who had a good relationship with the Gates Foundation.

"Professor, thank you. I will remember the help you've provided me." Chen Yuanguang said sincerely.

Because he knew this was his last chance, not the last chance to win the Nobel Prize, but the last chance to go to Sweden to receive the award in person.

Next year, with the broad-spectrum vaccine, the virus will be eradicated, and he will be showered with accolades. Since he is doing pure theoretical research, there's nothing wrong with going to receive the award.

If he waited until later, when he produced more influential results, such as those that could change the world, and the Nobel Prize was awarded to him again, he wouldn't dare to go and receive it.

This is the importance of timing. Missing it could mean missing it for a lifetime.

"Professor, were you just on the phone with Light?" The person standing next to Levitt waiting for him to finish his call was Steven, one of his doctoral students.

Levitt looked at Steven. "Yes."

Steven showed an envious expression. He felt that Levitt cared much more about Chen Yuanguang than about them, the doctoral students under Levitt.

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

Steven sighed, "Just the papers verifying Light's prediction model have been published in Nature, Science, and The Lancet."

Since Chen Yuanguang's research results were published, new virus strains discovered in various places, after sequencing, everyone would take them and compare them with the model.

Not all mutation points were necessarily predicted by the model, but most mutation points were included in the model, and the mutation points of the most prevalent virus strain were definitely within the model's prediction range.

Therefore, each sequencing could result in a paper. The sequencing comparison results of the Alpha strain discovered in the UK in September were preempted by Cambridge and published in The Lancet.

Academics realized that publishing papers was so simple, just sequencing and comparing was enough. Everyone started racing against time, building good relationships with virus testing centers, and it was all about who was faster.

Gradually, such results could only be published in second-tier journals, and it also depended on speed.

Some scholars summarized the sequencing results and wrote a review, which was actually published in Nature. This further increased everyone's enthusiasm.

In just half a year, Chen Yuanguang's paper was cited over two thousand times, becoming the most academically influential paper of the year.

This was something Chen Yuanguang had not anticipated.

Around a good result, everyone can make a living.

This made Steven very envious. Top-notch results, favored by bigwigs, and still young, he had all the buffs stacked.

"This is the value of top-tier researchers.

Like Euler's manuscripts, results, and thoughts fed the Russian mathematical community for three hundred years.

The more top-tier a scientist is, the richer the mine."

Chen already has that potential now."

Levitt was also deeply moved. He still remembered going to China at the end of the year before last to participate in a science fiction awards ceremony. At that time, Chen Yuanguang had approached him with a humble demeanor, making him think the other party was just trying to network.

It turned out the other party was a shark himself, and in just two years, he had already shown his sharp edge.

As a Nobel laureate, Levitt was well aware that there were differences among Nobel laureates. For some, winning the Nobel Prize was their glory, while for others, they were the glory of the Nobel Prize.

In Levitt's opinion, Chen Yuanguang, who was only in his early twenties, could completely achieve the latter.

Steven asked, "Professor, have you ever thought about recruiting Light to Stanford?

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

Speaking of this, Steven showed a strange expression. He somewhat didn't want to continue this topic because he remembered Chen Yuanguang's bizarre reason for refusing him again: because his friend was in New York.

At that time, the reason Chen Yuanguang gave him was that he preferred Bawendi's research direction.

After the two started collaborating this year, Levitt found that the other party had equally strong interest and ability in biological computing, so he asked the question again. Only then did Chen Yuanguang tell the truth, saying it was because his friend was in New York, and Boston was closer to New York.

Levitt would never forget how he felt at that moment. It was as uncomfortable as eating a can of fermented herring. So, my doctorate is not even worth seeing a friend a few more times.

After Chen Yuanguang created the prediction model, he comforted himself by saying that geniuses were just like that, individualistic. Geniuses had their extraordinary aspects, and naturally, their personalities were also very prominent.

"I invited him, but he might not like the climate in Silicon Valley," Levitt said, not even believing it himself, because the climate in California was clearly better than in Boston.

How could Boston's long, cold winters compare to California's pleasant climate?

He added, "In short, I invited him, but he didn't really want to come to Stanford."

Steven guessed inwardly that the other party probably preferred MIT, which was why the professor showed such an expression.

Steven could never guess the real reason.

"So that's how it is. It seems I won't have a chance to see Light in the short term. His achievements in biological computing are truly astonishing.

I have friends in Silicon Valley. Because of Light's results, many companies focusing on the combination of biological computing and AI have emerged in Silicon Valley recently, specifically providing AI services to pharmaceutical companies.

They've hired a bunch of computer science PhDs and biology PhDs, saying they want to provide new types of pharmaceutical outsourcing services.

Pharmaceutical companies like Pfizer, AstraZeneca, and Roche Pharmaceuticals have also started increasing their investment in AI. Pfizer alone recently placed an order for over $200 million with Nvidia."

Because he planned to go into the industry after graduation, Steven paid special attention to the cutting-edge developments in biology in Silicon Valley, as this related to his future development.

He was familiar with the latest trends in the Silicon Valley industry. After listening, Levitt said, "That's true. The advantages of AI technology in the field of biological computing are very obvious.

Traditional mathematical modeling can no longer meet the needs of the current academic community. We need new methods and new theories. Now we have new methods, but new theories are still a blank slate."