At the Yunqi Conference, witness the vast universe of AI

If you think the development of AI has already brought you enough shocks, then at the Yunqi Conference, you might see a world far more beautiful than the present. Through this year's Yunqi Conference, the author feels even more that the current development, which is in full swing, is just the beginning. As AI gradually matures and improves, the changes and imagination it can bring us may be far more shocking than they are now.

One

Eddie Wu's speech at the Yunqi Conference clearly demonstrated this point. According to him, the current AI is just the beginning. As AI gradually matures, humanity will eventually move towards the era of superintelligence capable of autonomous iteration, the so-called ASI era. To finally reach the ASI era, it will go through three stages:

The first stage is the emergence of intelligence, characterized by learning from humans and possessing generalized intelligence capabilities. After 2-3 years of development, AI has approached the peak of human capabilities in various disciplines;

The second stage is autonomous action, characterized by assisting humans, using and creating tools in the real world, enabling large models to connect all digital tools, complete real-world tasks, and quickly penetrate industries such as logistics, manufacturing, software, business, biotech, and finance. Currently, Agents mainly solve standardized and short-cycle tasks. To solve long-cycle tasks, the most critical need is to improve coding capabilities, which is the necessary path to AGI. In the future, there may be more AI agents than the global population working alongside humans;

The third stage is self-iteration, characterized by surpassing humans. There are two key elements: first, connecting to the full amount of raw data from the real world. Currently, the fastest progress in AI is in content creation, mathematics, and coding, because the knowledge in these fields is 100% defined and created by humans, all in text, which AI can 100% understand. But this also brings limitations. For AI to achieve breakthroughs beyond humans, it needs to directly obtain more comprehensive and raw data from the physical world. The second key point is self-learning, enabling the model to learn on its own, accept real-time feedback, and achieve self-iteration and upgrades.

It can be seen that the current AI applications and implementations that have already brought us so many shocks are just the beginning. As AI applications and implementations gradually improve, AGI will be able to act autonomously and truly move towards a new era that surpasses humans. For many, this may be the vast ocean of stars that inspires new dividends and trends.

Two

First, let's look at what stage AI is currently in. According to the author's understanding, current AI is still in the second half of the intelligence emergence stage. For many AI products, although they are still learning human knowledge at their own speed, it will still take some time to truly integrate human knowledge and information.

As Eddie Wu said, AI has approached the top level of human testing in various disciplines, such as the gold medal level of the International Mathematical Olympiad. AI has gradually gained the possibility of entering the real world, solving real problems, and creating real value.

For the players involved, how to fully integrate AI into the real world, truly solve real problems, and create real value still has great development potential. It is in this process that Alibaba has increased its related investments. Eddie Wu stated that Alibaba is actively promoting a three-year 380 billion AI infrastructure construction plan and will continue to make additional larger investments. According to long-term plans, to welcome the arrival of the ASI era, compared to 2022, the first year of GenAI, Alibaba Cloud's global data center energy consumption scale will increase by 10 times by 2032.

Behind these large-scale investments is the concrete manifestation of its layout for intelligence emergence. For any player who wants to make a difference on the road to ASI in the future, only by continuously increasing investment like Alibaba and achieving intelligence emergence can a solid foundation be laid.

In addition to Alibaba, we have also seen many players such as Tencent, Meta, and Baidu almost all moving forward along this path. Thanks to the arrival of the intelligence emergence trend, we have seen the long-silent technology sector begin to have new investment directions. It is precisely because of this that we have seen the AI-led sector become a new investment trend. On Monday local time, Cathie Wood, the star fund manager of Wall Street, managed Ark Investment to restart its position in Alibaba (BABA.N), which is also the first time in four years. The ARK Fintech Innovation ETF (ARKF) and the ARK Next Generation Internet ETF (ARKW) bought a total of 99,090 shares of Alibaba Group, with a total value of $16.13 million.

Three

If we regard the growth dividends brought by the intelligence emergence stage as a new trend driven by capital, then as AI development enters the autonomous action stage, the dividends it brings us are a new growth dominated by the iteration and upgrading of real business. At this stage, the vast ocean of stars shown by AI far exceeds the previous development model.

Now, the AI applications and implementations we see in different scenarios and industries are a direct manifestation of this phenomenon. Especially after Internet players began to fully embrace AI, this phenomenon has become clearer and more certain. The reason for this is that after the catalysis of the Internet era, almost all human businesses and scenarios have been connected to the Internet. When Internet players began to fully embrace AI, different industries and scenarios began to have a comprehensive connection with AI on the basis of the Internet era.

The intelligent driving we see now; the smart finance we see now; the dark factories we see now are all direct manifestations of this phenomenon. For players who are determined to make a difference at this stage, as long as they continue to increase the application and implementation of AI in different industries and scenarios, and continue to use AI to improve efficiency, they can obtain new development dividends.

From the changes brought to their own business modules by major Internet giants after fully embracing AI, we can see that in the initial stage of autonomous action, AI has already released such huge development dividends. This is just the beginning. According to Eddie Wu, current AI can only solve standardized and short-cycle problems. When it can solve long-cycle and non-standardized tasks, it will release greater development dividends.

From this perspective, AI will also open up a new vast ocean of stars for us, and the current AI applications and implementations we see in a series of industries and scenarios are just the beginning.

Four

When AI development moves from the autonomous action stage to the self-iteration stage, the development dividends it releases will be greater, and the momentum it can bring to social development will be greater.

In this regard, Eddie Wu gave an example. For example, the CEO of a car company wants to iterate next year's product. It is very likely that through countless user surveys or internal discussions, it will be decided what functions the next car will have, what advantages it will have compared to competitors, and what capabilities it will retain. It is still very difficult for AI to do this now. The core point is that the data and information it obtains are all second-hand data from surveys. If one day AI has the opportunity to connect all the information and data of this car, the next car it creates will far exceed the one created through countless brainstorming sessions.

It can be imagined that when AI enters the self-iteration stage, especially after it fully surpasses humans, the growth momentum it can bring and the reshaping and reconstruction it can bring to the industry will be far stronger than what we see now. At this stage, what AI transforms is not only the Internet and traditional industries, but also the industries and scenarios derived from the intelligence emergence stage and the autonomous stage.

When such a stage comes, the development potential it releases may be far more imaginative than what we see now. For players who have already made a difference in the intelligence emergence stage and the autonomous action stage, it is another new release of dividends, another new industry reconstruction, and the development potential it brings us is even stronger.

Final Words

Through this year's Yunqi Conference, we have seen a new vast ocean of stars that is far more imaginative than ever before. The most critical point is that it has drawn a clear roadmap for us from the AGI era to the ASI era. On the road to ASI, every stage has new dividends released, and almost every stage can redo all industries. This is not just a reconstruction of the Internet industry, but also a repeated reconstruction of all human productivity and production relations.