Li Miaomiao continued, "Being a beggar? Being a homeless person is also a life experience, why don't you try it?"
Zheng Li explained, "What you're describing can all be logically categorized as a scarcity of resources, differing only in degree."
"Besides, how do you know I haven't experienced it?"
When Zheng Li first graduated from the mage academy, he only received a salary of a dozen or so magic stones. Most of that money was spent on basic research materials, not to mention materials for magical experiments.
Fortunately, the Mage Alliance provides basic living allowances for all registered mages, which enabled Zheng Li to accumulate knowledge in his early years.
Li Miaomiao asked, "You received an investment of 50 million before you even graduated, and your net worth is already over 100 million. You earned tens of thousands while teaching others in college. You are basically among the richest people in your age group."
"If this is what you call resource scarcity, then it really is a bit like Versailles."
Zheng Li looked nostalgic. "That was a long time ago."
In fact, your sense of accomplishment and satisfaction will be stronger in the initial stage of capital accumulation than in the later snowballing stage. When 1 becomes 2, the growth rate is 100%, but when 100 becomes 110, the growth rate is only 10%.
It's like how time seems to pass faster as you get older. When you're a child, each year you grow up is a fraction of your lifespan, but when you're older, each year you grow up is a fraction of your lifespan.
Li Miaomiao couldn't understand Zheng Li's feigned profundity: "You didn't suffer when you were young, did you? Your parents are civil servants and you're an only child, so they certainly wouldn't mistreat you."
“I visited your home last Chinese New Year to extend my greetings to your parents on behalf of the company,” Li Miaomiao quickly explained.
Zheng Li changed the subject, asking, "How many days do you plan to stay in Singapore this time?"
Li Miaomiao: "I plan to stay until the end of the year and then properly reorganize the company's structure."
Zheng Li: "Okay, you can consider whether to locate our AI R&D center in England or Singapore. At least initially, we need to have an office in England. Since we can't acquire them, we'll poach their talent."
Li Miaomiao nodded: "I feel that our acquisition has been leaked."
"Although the company's valuation and profits are high, the composition of its members is still too complex. Only now do we truly realize what true strength is. Our talent source is heavily reliant on rice (a type of rice) and external recruitment."
"I initially thought the leak was related to rice, but the fact that IDG and Goldman Sachs hold stakes in SecondMind dispelled my doubts."
“In the next few years, we need to cultivate a group of talents who have grown from campus recruitment to gradually replace the previous middle-level managers and even senior managers.”
"This incident made me realize that we need to be as discreet as possible in our actions. We should then use a multi-layered structure to set up a separate company to poach talent, instead of directly using the name of Kechuang Biotechnology."
Zheng Li nodded: "I trust you. Go ahead and do the job of training campus recruits. Besides, it's not easy for a startup to poach talent. High-end talent looks at the company's background, and it's very difficult for a startup to find high-end talent."
Li Miaomiao: "Then we'll offer high salaries to poach talent from universities, and we can appropriately reveal the company's background when we're poaching them."
“My dad has been a teacher for so many years, so he has some connections. I can use him to find some trustworthy people. The office in England is made up entirely of new people.”
"I didn't want to involve my dad's connections in this matter before, since it's your company. But now it seems that I have no choice but to use my dad's connections to recruit talent for the mid-term transition."
Zheng Li didn't care. To him, science and technology innovation was just a tool to mobilize social resources, not his wealth: "Okay, you can give it a try."
Li Miaomiao asked, "When are you going back to China?"
Zheng Li: "It will probably take some time, about a year."
The distance between Kuala Lumpur and China is too far. If one wants to control a physical body in Suzhou, there will be a delay. Even a delay of only tens of milliseconds will look very strange to the naked eye.
Li Miaomiao's tone lowered: "Okay."
......
In a building in faraway California, jubilation reigned. Besides assisting Pfizer with the screening of effective drugs, Simmons had been working on optimizing the Haiber algorithm.
The "Magic Brain" system optimized Simmons' logical thinking and the associative abilities of his underlying neurons.
The most important thing in mathematical research is the ability to make associations in your subconscious mind. Can you connect the methods you have seen in your subconscious mind and form new methods to solve mathematical problems?
(The mathematical problems here refer to those in the basic mathematics field at the doctoral level. High school and university mathematics can be solved entirely through practice by developing a set of methods in one's mind.)
It can be said that Simons alone could claim to have led his team to solve the Haber algorithm (here, "solved" refers to optimization).
"Professor, you're as charismatic as ever. I can almost see how you used to handle every question with ease back at Stony Brook." The researcher next to Simmons was one of his students when he taught at Stony Brook.
Simmons didn't mince words: "I'm getting old. If I had had a magic brain when I was younger, this question wouldn't have stumped me for almost a year."
"If it were back then, it would have taken at most six months."
The researcher showered him with praise: "Actually, it only took ten months. You have to understand that you've been working in the financial world doing quantitative investment for so many years. To pick up cutting-edge mathematical research again is like starting all over again. This time is already amazing!"
"You should know that people like Terence Tao and Weiteng are not progressing as fast as you."
Simmons works for the government, so their information network is the best.
Simmons said smugly, "After all, I'm their senior. The body may grow old, but the mind can't."
"We've done what we can. The rest is up to the astronomers and computer scientists. They need to find the right galaxies and develop the right algorithms to perform the calculations."
The optimized Haber algorithm is equivalent to only needing to observe galaxies that may harbor life, then substituting the galaxies into the optimized Haber algorithm for calculation, and judging from the results whether the galaxy has a cosmic coordinate system that meets the conditions.
In other words, each planetary system is regarded as a mine, and the optimized Haber algorithm determines whether gold can be found in the mine.
If the galaxy meets the criteria, then the stars in the galaxy can be calculated one by one to find the specific coordinates that satisfy the Hayfir algorithm.
Whether or not the exact coordinates of a planet can be determined depends on astronomical observation capabilities and the distance of the galaxy from Earth.
In other words, the countries that develop the optimized Haber algorithm first are the ones that can mine resources closer to Earth, while the countries that develop the Haber algorithm later can only mine resources further away.
Mines located far away may require individual calculations for verification, making mining increasingly difficult.
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