Companies developing autonomous driving technology are finding it very difficult to secure investment.

Because investors will ask you, what makes you think you can beat Tesla? What makes you think you can beat Baidu? And domestic new energy vehicle companies all have their own autonomous driving departments.

What will you rely on to seize the market?

For example, Baidu has been burning money in the field of autonomous driving for many years, but has not yet achieved any commercial results.

Not to mention startups, investors will wonder how much money I need to burn before I can see results. What if I burn billions and you still can't beat other companies?

It's extremely difficult to attract investment in this way.

Secondmind was able to attract investment and successfully pass its Series B funding round mainly because it not only develops autonomous driving algorithms and deep learning platforms, but also designs AI chips.

There are few players in this field, and SecondMind, backed by Cambridge and located in England, has a very strong team of talented individuals.

Moreover, their Series B funding was not large, so they were able to attract investment.

Cheng Gang asked, "When will SecondMind reach Series C funding? Will you participate in the Series C round?"

The head of Tencent's investment department took a sip of coffee:

"I guess it'll be soon. They only raised 24 million US dollars in their Series B funding round, and it's been two years now. They've probably burned through most of it."

"Personally, I'm inclined to invest a little to try it out. We only invested six million US dollars in the B round, and even if the price doubles in the C round, it will only be twelve million, which is nothing."

"We will probably follow suit, but we still need to decide after a meeting."

"To be honest, I don't expect SecondMind to achieve anything significant in the field of autonomous driving, but their deep learning in some areas of vehicle performance tuning is quite good."

"In China, starting a team from scratch doesn't cost much less than investing in SecondMind. If you want to participate in the Series C funding, I can help you make connections."

“RB Capital, one of the Series B investors, happened to want to exit.”

Tencent's investment department reviews more than 200 projects every year, and manages hundreds of projects.

Their investment project management system updates the latest information for each project in real time, making it easy to access.

Cheng Gang had already found out the information he wanted, so he naturally had to reveal some in exchange: "We plan to enter the semiconductor industry and want to acquire an AI chip company with a certain foundation in the industry and a good team."

"SecondMind is one of our goals."

The first reaction of the head of Tencent's investment department was:

"You're going to enter the semiconductor industry? Kechuang Bio's stock price is going to rise again. I might consider buying a few shares and holding them."

"Semiconductors are a money pit; billions can be burned up in no time."

"You're planning to develop brain-computer interface chips? Well, if you want to create a deeper competitive advantage, you can only do so by focusing on this area."

"I've always been curious whether Chairman Zheng's brain is structured differently from ours. Not only is he good at scientific research, but he also has a good vision for the company's strategic planning."

"If you develop a brain-computer interface chip, it will be difficult for Musk's Neuralink to catch up with you."

From the perspective of a professional investor, he believes that Kechuang Bio's leading advantage in the field of brain-computer interfaces is not yet obvious enough.

Of course, the market share in the brain-computer interface field is large enough to accommodate several players.

However, the market values ​​monopolies and monopolies with one dominant player and many strong players differently.

......

St. Petersburg is often overcast, and Perelman likes to think on overcast days and daydream when the sun is out.

When inspiration strikes, I write it down; when I lack inspiration, I keep thinking. I often put my writings together and think about whether they can be connected.

The more I think about it, the more I appreciate the brilliance of the Haber algorithm, which perfectly combines analysis, geometry, and algebra.

Perelman found it nearly impossible to devise a universal method to find a general solution.

If we simplify the problem, it's like if we can't prove "1+1", we can start with "8+9" and gradually work our way up to "1+2".

Perelman's approach was to use the Haber algorithm and the Haber constant to determine the set of coordinates that fit the Magic Coin.

The set is then compared and calculated with astronomical observation data to further narrow down the set.

Finally, smaller sets are computed using supercomputers.

We're currently stuck on the first step.

Russian computer scientists are taking the final step of researching suitable algorithms and writing programs.

They planned to start the calculations while waiting for Perelman's progress.

A cold wind blew in through the window, making him shiver; winter was just around the corner.

Problems like math problems don't allow for collaborative work, and it's generally impossible to pressure researchers to speed things up.

Therefore, while news of professors exploiting graduate students has frequently surfaced in other fields over the years, such news has never occurred in the field of mathematics.

Because if you don't know it, you just don't know it. No matter how hard you try, you won't figure it out. It's not a subject where spending time guarantees a result.

When it comes to the most cutting-edge problems in mathematics, the gap between knowing and not knowing cannot be bridged by time.

The mentor is actually worried that the student might develop a mental illness due to being too persistent.

Other mathematicians in other countries have also come up with Perelman's idea.

The Clay Mathematics Institute in America simplified the problem, made it public, and announced that anyone who solved it would receive a prize of ten million US dollars.

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