380 billion, 300+ open source models, it’s hard to get a ticket, the stock price has hit the limit, the familiar Alibaba is back!
The first picture is that classmate Mengfei was blocked by the enthusiastic audience from the door that was shared more than ten meters away.
He took this interesting photo, and the popularity is evident.
The second picture is the summary information of the Qianwen model family.
It is hard to imagine that Qianwen now has 300+ open source models, full size, full mode, and multiple scenes.
Behind this is a lot of investment in money, time, and equipment.
I give a thumbs up to all manufacturers who make open source models👍.
Not only do we not get stuck, but we also have many features and competitiveness.
I am actually more interested in the introduction about AI Infra given by Mother Wu in the morning.
380 billion has been invested in AI Infra in three years.
What will it be used for?
The first stage: "Intelligence Emergence", AI acquires generalized intelligence by learning massive amounts of human knowledge.
The second stage: "autonomous action", AI masters the use of tools and programming capabilities to "assist people".
This is the stage the industry is currently in.
The third stage: "Self-iteration", AI connects to the physical world and achieves self-learning, ultimately achieving "surpassing humans".
To achieve this goal, Wu Yongming clarified Alibaba Cloud's strategic path.
As a "full-stack artificial intelligence service provider", Alibaba Cloud will implement its AI strategy through two core paths: First, Tongyi Qianwen adheres to the open source and open line and is committed to creating "Android in the AI era"; second, it builds a super AI cloud as a "next generation computer" to provide an intelligent computing network for the world.
Wu Yongming said that Alibaba is actively promoting a three-year 380 billion AI infrastructure construction plan and will continue to make additional investments.
In 2032, the energy consumption of Alibaba Cloud's global data centers will increase by 10 times.
The familiar spirit returned.
As soon as Wu Ma finished speaking, Alibaba's stock price hit the limit.
In fact, our domestic AI infrastructure and basic model research and development are currently all funded by the big manufacturers themselves.
It is basically impossible to spread the word like Oracle, Nvidia, and OpenAI to make the pool bigger.
All costs must be borne alone in the early and mid-term, and the payment habits of domestic AI subscriptions have not been established.
So where are the opportunities?
My personal analysis is on the enterprise side, on the B side.
Domestic enterprises of any size are now in a stage where they are eager to be fed.
There are huge opportunities here.
The process of enterprises moving to the cloud has basically been completed.
The most reliable thing that AI can do at this stage is cost reduction and efficiency improvement.
The internal operation of the enterprise scenario needs to improve efficiency, and the enterprise's own business can reduce costs through AI.
This is also a new challenge for us personally.
As Wu Ma said, it is not just AI coding, but a larger AI w orking, AI organizations, this is a bigger change.
380 billion is the lever to leverage this change and the ticket.
Haha, I haven’t written for a long time.
It’s really worth recording today.
The gears of fate are starting to turn slowly.
