Baidu Cloud Intelligence Conference: The intersection of technology and innovation

This
Baidu Cloud Intelligence Conference can be said to be full of highlights——

Released the newly upgraded Qianfan Large Model Platform 2.0 containing 42 large models, 41 data sets, and 10 selected application paradigms, released the first large model ecological partner program, and also announced the release of Wenxin Large Model 4.0. The report card of the model service is also very impressive: the number of monthly active companies has reached nearly 10,000, covering more than 400 scenarios in finance, manufacturing, energy, government affairs, transportation and other industries.

What stood out to me at this conference was the Wenxin large model and the reconstruction of the four major industry solutions based on the large model. It can be said that it has fundamentally completed the deconstruction of the industry.

As the Wenxin model with the largest scale of industrial implementation, the current industry breadth and coverage scenarios, as well as practical application experience, it should be the number one nationwide. In this answer, I will simply continue the part that interests me the most, tell you in detail about these four industry solutions, and fundamentally explore the method of "deconstruction".

Let’s first talk about the government solution for urban governance—Jiuzhou.

Kyushu, the name is the same as a novel of the same name that I like, and its pattern has really opened up. It is equivalent to reshaping a brain for the city. Its original core concept of digital government construction of "one network for unified management, one network for all services, and one network for collaboration" can be said to be even more powerful for urban management.

For example, urban governance in the past was actually very complex, and generally required high-frequency scenarios and static analysis as the main governance methods. But now with the assistance of unified management of large models, we can not only extract new thinking from the historical content of the city, understand the problems and give the best suggestions in a timely manner, but also in a sense add more to the past governance methods. Objective and scientific basis.

The "one-stop service" is mainly reflected in serving the people. The large model can understand all kinds of government affairs knowledge and terminology. Each citizen can have his own service assistant, which greatly reduces the labor force at the consultation desk and agency window.

One-network collaboration is mainly reflected in improving the efficiency of internal government offices. From official document writing to department coordination and decision-making support, office efficiency can be improved dozens of times.

What are the biggest benefits of using AI to improve things? It lies in objectivity and science, but it also lies in the execution of efficiency and the corresponding demand for the fastest delivery——

For regional governance like China, which has a huge land area and fragmented regions, this is simply a dimensionality-reducing blow. For example, grassroots urban and rural governance and local industrial applications based on different local conditions use AI to directly promote the integrated and coordinated development of urban and rural areas.

Let’s talk about the financial aspect, Baidu Intelligent Cloud Financial Solution: Kaiyuan.

In fact, the financial aspect is now almost the original intention of many companies to develop large models. The purpose of many companies creating large models is to serve finance. However, it is very difficult to achieve the scale of Wenxin's large model, from the technical threshold to the implementation threshold.

Baidu's Kaiyuan has narrowed the problem from a macro perspective and focused on two levels to solve the biggest pain points in the financial industry -

Operational efficiency and business quality.

These two aspects are undoubtedly problems that the financial industry has always wanted to solve, but there is no particularly good way to solve them. The final solution is often only one: stacking manpower.

low efficiency? Adding people, but the quality of service is poor? Adding a elimination and replacement mechanism and a service quality evaluation mechanism will eventually require adding more people.

Through Baidu's Kaiyuan, in terms of operational efficiency, through the compression and learning of massive financial professional knowledge, Kaiyuan has created a large financial model for financial institutions that meets regulatory requirements, running through the front, middle and back offices of financial institutions' businesses, to achieve large-scale cost reduction Increase efficiency.

In terms of business quality, Baidu provides two sets of intelligent application solution suites: digital business operations and generative collaborative office. On the one hand, it assists employees in their daily work through the "Investment Research Analysis Assistant" and on the other hand, it generates digital employees. The two work together to Support business growth.

If employees are liberated from the complicated and inefficient work of the past, will they still worry that the service is not good enough?
This is the perfect solution that can only be derived from the understanding and deconstruction of the industry at the bottom.

Let’s talk about the industrial aspect. Baidu’s naming really never disappoints me – Baidu Intelligent Cloud Industrial Solution Kaiwu.

In fact, our country has always been in a relatively awkward position with regard to the degree of digitalization of industry. The promotion of digitalization has indeed been ongoing, but the cost of actual implementation has always been high, which has greatly increased the survival costs of many small and medium-sized industrial enterprises.

And how is Kaiwu made? Directly using the generalization capabilities of large industrial models helps industrial companies build more intelligent applications for production lines in less time with smaller data samples and computing power, and the large models’ own unique capabilities—

Generative automation capabilities can realize intelligent scheduling and management between factory-level models, use a large language model to connect intelligent applications in different production lines, and achieve global resource allocation and intelligent data flow at the enterprise level or even the industry chain level. The seamless transmission of data will naturally drive up the efficiency of the industry.

Finally, let’s talk about the intelligent transportation solution: ACE3.0.

Baidu has really put a lot of effort into urban transportation.

In the past five years or so, Baidu has also made many achievements in the field of intelligent transportation, and has become the only company in the world to achieve a closed-loop full-stack core technology of cars, roads, clouds, and images. In this process, Baidu is Accumulate to the greatest extent based on the basic elements of transportation, such as dynamic and static traffic data, transportation industry knowledge map and engineering capabilities.

Utilizing the powerful knowledge compression capabilities of large models, ACE 3.0 can aggregate and generalize the basic capabilities of vehicles, roads, clouds, maps, and all transportation elements to develop intelligent transportation solutions based on regional specificities.

For example, for the traffic police department, there were originally only dozens of congestion identification factors, but now they can be increased to one or two hundred through large models, and the traffic organization plan can be redesigned faster and better based on the large model. and optimization, and continue to expand this scope.

The above is the interpretation of industry solutions at this Baidu Cloud Intelligence Conference. These solutions are outstanding. They not only cover the B-side and C-side business scenarios, but also effectively realize China Unicom. It may be that the actual implementation value has not been fully released yet, but when the technology With more maturity and more stable computing power, a new migration in the Internet era may come earlier.

I also look forward to the official arrival of an era of large model problem solving.

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