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The history of the information revolution in the past few decades tells us that the success of science and technology does not lie in the scale of the industry or the number of equipment, but in the number of devices. People lie in their imagination and creativity.
When teenagers develop amazing AI applications on campus; when office workers use AI to solve problems that have plagued the industry for a long time; when an ordinary person realizes his dream by becoming a developer, then we can There is no doubt that technology has won and AI has won.
Since 2023, the Chinese market has ushered in the “hundreds of models rushing to take the exam”of grand occasion. But when we put our perspective on specific AI developers, we will find that the difference that developers can feel is not big. Most large AI models cannot truly become capabilities and tools in the hands of developers. The ecosystem of AI developers around large models is difficult to consolidate. There is a relatively obvious separation between model and application development. There is a clear generation gap between technological evolution at the model level and the real needs of developers.
How to resolve this situation? How can big models really leave the hands of developers?
On April 16, the Create 2024 Baidu AI Developer Conference with the theme of “Creating the Future” was held at the Shenzhen International Convention and Exhibition Center. During the period, Baidu Chief Technology Officer Wang Haifeng delivered a speech with the theme of “Technological Foundation, Galaxy is Bright”, explaining the key technologies and latest progress of many cultural large-scale models such as agents, codes, and multi-models. Wang Haifeng said, “In the future, we will continue to devote ourselves to cultivating talents, so that the stars of talents can merge into a brilliant galaxy. In the intelligent era, everyone is a pioneer and everyone is an inventor. Let us work together to create a better future.” .
Unlike most large model projects, the emphasis is on parameters, accuracy and other indicators. Wenxin Big Model has chosen another path: to understand the needs and ideals of developers, and Wenxin will do whatever developers need.
Along this trajectory, Wen Xin evolved all the way, showing great technological explosive power. This not only established the scale effect of the Wenxin large-scale model, but also established its long-term development direction.
Wenxin’s future is very clear: by connecting the developers’ dreams together, a splendid galaxy of AI large-scale models can be formed.
Where is the galaxy? The developer’s dream is the galaxy
Today we can clearly say that the Wenxin large model is one of the large models with the fastest technological advancement and the most frequent systematic upgrades in China, and even in the world. Since the release of the knowledge-enhanced large language model Wenxin on March 16 this year, Baidu has continued to promote the upgrade and iteration of the Wenxin large model.
And every version upgrade shows the evolution of core technologies. Speed has become a unique sight in the AI industry.
For example, in Wenxin large model version 3.0, knowledge enhancement, search enhancement and dialogue enhancement technologies have been fully added; Wenxin version 3.5 RW Escorts This principle brings a comprehensive upgrade of the basic model, adding capabilities such as fine-tuning technical innovation, enhanced knowledge points, and enhanced logical reasoning; Wenxin 4.0 realizes large-scale parallelization of Wanka’s computing power Training, through joint tuning with the flying paddle platform, brings technical capabilities such as multi-dimensional data, multi-stage alignment, and reproducible training.
In the process of large-scale and high-efficiency upgrades, Wenxin’s large model capabilities have become more powerful, and its effects and performance have been comprehensively improved. At this time, many friends will be curious, how did Wen Xin discover Rwandans Sugardaddy So many technical upgrade directions? Why maintain such a high-intensity upgrade trend?
In Create 2024, we can find the answer.
From a developer’s perspective, AI large models are bringing about a cross-generational development singularity. The original application development gap was suddenly broken. AI has brought a huge number of new application types, a comprehensive lowering of development thresholds, and unprecedented development efficiency. But to truly realize the dream of AI application development, new technical foundations are needed as an anchor. The ability to truly turn AI large models into the hands of developers needs to solve three major problems today:
1. How to use AI large models as a basis to break past development gaps and turn those unprecedented development ideas into To be able to? How to achieve more intelligent and cutting-edge AI development?
2. How to take a further step to lower the development threshold and realize a low-code or even no-code development paradigm, thereby realizing the vision of the era in which everyone is an AI developer?
3. How to reduce development costs, improve development efficiency, and further improve the application development mechanism based on AI large models to make AI application development more maneuverable and implementable?
Breaking barriers, lowering barriers, and optimizing mechanisms are currently the three most urgent wishes of developers for AI large models. The latest upgrade of the Wenxin large model also just responds to the needs of developers.
Wang Haifeng said, “I hope that the little stars of talents can merge into a splendid galaxy.”
For Wenxin Big Model, only by responding to the needs of developers and understanding their wishes can these stars be lit.
For Wenxin Big Model, Rwanda Sugar Daddy The dream of AI developers is to pursue every step of the way of the galaxy.
Intelligent agents, crossing the development gap
First, let us look at how the Wenxin large model breaks the development gap and brings developers the most cutting-edge technological possibilities.
Today, the most hotly discussed technical direction in the global AI industry is intelligent agents. The intelligent agent mechanism with multiple capabilities such as thinking, analysis, and reasoning is widely regarded as the future development direction of AI technology. It is also an important pivot for the implementation of large models into native AI applications.
In October this year, Baidu introduced an agent mechanism into the Wenxin model. Wang Haifeng shared his understanding of fast thinking and slow thinking. At the just Create 2024 Baidu AI Developer Conference, intelligent agents were officially added to the technical architecture of Wenxin Large Model. Wang Haifeng said, “Intelligent agents are an important development direction and will bring about more application explosions. Intelligent agents are a further step to carry out thinking-enhanced training on the basic model, including supervised fine-tuning of the thinking process and action decision-making. Diligent learning of planning and enhanced learning of result reflection can lead to the acquisition of thinking models. The thinking model of an agent is like a human being, who can read instructions and learn how to use tools, and then can call tools to complete tasks.”
At the scene, Wang Haifeng demonstrated how to call tools on the Wenxin Big Model 4.0 tool version. Xiang Wen Xinyi asked, “I am going to the Greater Bay Area for a business trip for a week. I want to think about the weather changes so I can decide what clothes to bring. Please help me check the temperatures in Beijing and Shenzhen in the next week and tell me what clothes I should bring for the business trip. , and organized into tables.”
Faced with this series of complex questions, as well as the very specialized requirements for information processing and table generation, Wen Xin’s intelligent agent mechanism can think and plan like a human being, thereby breaking down the requirements into multiple As a subtask, first call the “Advanced Networking” tool to query weather information, then call the “Code Analyzer” to draw a temperature trend chart, and then choose appropriate clothing based on the weather conditions in the coming week. Finally, consider and confirm the results. And take the initiative to summarize it into a table.
Such technical capabilities have far exceeded the capability boundaries of previous AI technology and even large model technology. Developers can explore a more diverse and broader intelligent future through the new technology base.
Breaking the gap is the first gift that Wenxin 4.0 brings to developers.
Smart code, changes in development paradigm
We all know that the traditional application development paradigm is based on code writing in different programming languages. The biggest change that AI large models bring to the development paradigm is that the large models themselves can help generate code, and even achieve application generation without code.
In response to the widespread needs of AI developers and potential AI developers for low-threshold development, Baidu has developed code intelligence based on the natural language capabilities and coding capabilities of Wenxin large models Rwandans Sugardaddy and smart code assistant.
Among them, code agents can realize code-free application development, allowing everyone to become an AI developer.
Code agents Rwandans Escort is technically based on the thinking model and code interpreter. First, the thinking model will understand the user needs, and after thinking, combine the instructions and instructions to complete the task. The relevant information is integrated into the prompts and output to the code interpreter. Then, the code interpreter interprets the user RW Escorts according to the prompts. It needs to be translated into code and executed to obtain the execution results or debugging information. Then, the thinking model will reflect and confirm the execution results of the code interpreter. If it is correct, the result will be returned to the user. If it is not correct, it will continue to iterate independently and replace it with new ones. Materials. Through such a logic mechanism, the agent can fully understand the user’s code generation needs and be responsible for the results, realizing “AI application development can be achieved by just speaking”
Intelligent code assistant. , which can help professional programmers write high-tool quality code more efficiently and more conveniently. On the basis of continuous improvement of model performance, Baidu has further built an intelligent code assistant with context enhancement, private domain knowledge enhancement, and RW Escorts capabilities such as seamless process integration
Currently, the overall adoption rate of the intelligent code assistant Comate has reached 46%. The proportion of new code generated has reached 27%, and Comate capability can seamlessly integrate code understanding, generation, optimization and other capabilities into all aspects of the R&D process, helping to improve the quality and efficiency of code development tools. a href=”https://rwanda-sugar.com/”>RW EscortsWith simple instructions, you can quicklyRwanda Sugar Quickly understand the structure of the entire code, and even the specific implementation logic of each module. You can also automatically generate new code that meets the requirements based on the current project code and third-party code, thus making the developer’s work easier and gaining more benefits. Support and assistance are more comprehensive.
Code assistance and code-free generation are the basis for the reform of development paradigm in the AI era. Baidu has continued to work hard in these two aspects, giving AI developers the second important gift-super. Low-threshold development opportunities.
Multi-model, optimization of development mechanism
In addition to agent and code capabilities, Baidu also focuses on releasing multi-model technology for developers to actually develop AI applications.During the process, the call and selection of AI models are very complicated, and there are often problems that require multi-model matching based on different scenarios, and model switching based on the surrounding conditions of software and hardware. However, various compatibility difficulties and forced choices often arise during the multi-model selection process.
In order to achieve a balance between effect, efficiency and cost of large model applications, Baidu has launched multi-model technology.
First of all, it is a model that fully supports efficient and low-cost Rwanda Sugar. In order to achieve high-efficiency and low-cost model birth, Baidu has developed a training mechanism for large and small model collaboration, which can effectively carry out knowledge inheritance and efficiently give birth to high-quality small models with high tools. Small models can also be used to achieve comparative enhancement and assist in the training of large models. .
At the same time, Baidu has established a seed model matrix, a data improvement and enhancement mechanism, and a complete set of pre-training, fine-tuning and alignment, model compression, and inference deployment Rwandans SugardaddyEast-West chain. The efficient and low-cost model childbirth mechanism can help application development to be faster, lower cost, and better.
In terms of RW Escorts multi-model reasoning, Baidu has developed end-to-end multi-model reasoning technology based on feedback learning and built Intelligent routing models carry out end-to-end feedback learning and give full play to the ability of different models to handle different tasks to achieve a balance between effect, efficiency and cost.
Facing the future, multi-models have become an important trend in the implementation of large AI models, and Baidu once again takes the lead and uses it as the third gift to developers.
Progress all the way to the galaxy
Insight into the needs of developers and help develop their dreams. This simple logic constructs the progress coordinates of Wenxin’s large model, allowing it to continue running and move forward courageously.
In addition to agents, codes and multi-model technologies, Wenxin Large Model has also made continuous innovations in many aspects, including a data system based on model feedback closed loop, large model alignment technology based on self-reflective enhancement, and Multimodal techniques and more. Overall, the performance of Wenxin Large Model 4.0 has continued to improve. In the six months since its release, the overall performance has increased by 52.5%Rwanda SugarFruit.
The continuous rapid evolution of Wenxin large models benefits from Baidu’s full-stack layout in chips, frameworks, models and applications, especially The joint optimization of the Feipiao deep learning platform and Wenxin’s large model has achieved a weekly average training effectiveness of 98.8%. Compared with when Wenxinyiyan was released a year ago, the training efficiency has increased to 5.1 times and the inference rate has increased to 105 times.
In the continuous technological innovation, Wenxin large models have become the first choice for AI developers so far. Feipiao Wenxin ecosystem has gathered 12.95 million developers, served 244,000 enterprise work units, and created 895,000 models based on Feipiao and Wenxin. The cumulative user scale has reached 200 million, with average daily calls. It has reached 200 million, meeting the intelligent needs of thousands of industries.
In the key talent training link, Baidu proposed in 2020 that the goal of cultivating 5 million AI talents for the whole society in five years has been achieved ahead of schedule. It has become the only choice for AI developers to start their dream journey
Use the developers’ real needs as the guide, the developers’ broad expectations as the roadmap, and the developers’ great dreams as the future. This is how Wenxin progresses all the way, insisting on high-speed iteration and comprehensive evolution. Wenxin will continue to evolve. Today, on the day when countless AI developers realize their dreams, on the day when China’s science and technology fully awakens the power of new generations, on the day when AGI dawns, we meet across the galaxy
Review Editor Huang Yu
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