The domestic large-scale model competition is in full swing Huawei's Pangu large model was upgraded in July

The wave set off by the AI big model is one wave after another. Not long ago, NVIDIA's total market capitalization exceeded trillion dollars for the first time, becoming the fifth largest company in the US stock market by value after Apple, Microsoft, Google and Amazon. "NVIDIA's market value skyrocketed by $200 billion a day, equal to one AMB and two Intels, largely stemming from the demand for computing power for AI training." On June 17, Zhang Ke, Executive Chairman of Beijing Frontier Financial Regulatory Technology Research Institute and Chairman and CEO of Baker Capital, sighed at the first stop of Huawei Developer Co-creation Day in Shenzhen.

Industry experts pointed out that the scale of parameters of large models is getting bigger and bigger, ChatGPT-3 has 175 billion parameters, GPT4 is not disclosed, but it is expected to exceed the order of trillions, which is similar to the number of human neuronal connections.

At the event, the guests exchanged views on the trend of AI technology, industry applications, and developer growth.

Large models lead a new round of man-machine revolution

Looking back at the history of the development of artificial intelligence, from the 1960s to the 1990s, the first generation of artificial intelligence was knowledge-driven artificial intelligence, mainly represented by expert systems; From 1990 to 2020, the second generation of artificial intelligence was connectionism represented by data-driven deep learning, which was characterized by data + computing power + algorithms; Since 2020, the third generation of artificial intelligence has been driven by "knowledge + data", characterized by the ability to think like humans such as common sense, experience, and reasoning.

At the meeting, Wang Chen, an AI technology planning expert from Huawei, introduced that large model technology is being used in enterprise services to help enterprises upgrade applications through deployment modes such as public cloud, private cloud, and Finetune (proprietary training + inference resources). Wang Chen believes that the current deep learning of artificial intelligence still faces three major problems: one is poor generalization, the other is difficult to integrate with domain knowledge, and the third is safe and credible. The US Natural Science Foundation pointed out that the key to the entry of AI systems into thousands of industries is to integrate more key knowledge areas, such as the combination of AI and technologies in agriculture, physics, and chemistry; At this year's AI conference, a charter was issued on adhering to the responsible use of AI, and put forward the principles adhered to in the era of large models, such as human auditability, open source accessibility and other standards.

Wang Chen said that it is currently in the stage of alternating from the second generation of artificial intelligence to the third generation of artificial intelligence, and the "knowledge + data" drive makes the AI system have the ability of human thinking such as common sense, experience, reasoning, etc.

He believes that there are three directions for future AI technology breakthroughs: first, based on large models, "language" drives the "AI codec" model architecture to become unified, and the future model evolves to "modal spatiotemporal dynamics"; The second is the general solver, from games to AI4Science, combined with expert knowledge to break through the NP-hard problem, and the future "prediction and control" will be deeply applied; The third is EmobodiedAI, integrated AI, AI interaction with the physical world, accumulate more experience and common sense, improve reasoning ability, and achieve symbiosis with humans. Wang Chen also reminded that AI must be used responsibly in the future.

The AIGC exploded

By 2025, 10% of data will be created by AI

Artificial intelligence has entered a new stage, and AIGC continues to be popular. Al Generated Content (AlGC), generative Al refers to the computer through machine learning to learn the elements of an object (item, product or task) from existing data, and then generate a new, original, real, similar to the original content.

Xia Fei, an AI ecosystem technology expert at HUAWEI CLOUD, believes that the popularity of AIGC indicates the trend of artificial intelligence development, from perceiving the world to understanding the world, and now it has begun to create the world.

Gartner's 2021 book The Impact of Artificial Intelligence on Humans and Society predicted that 20% of content will be created by generative Al by 2023, and that by 2025, generative AI will generate 10% of all data, up from less than 1% today.

According to the data cited by Xia Fei, it is expected that in 2030, China's AIGC market (including only content creation, excluding Al code generation) will reach a trillion yuan. Similar to the proportion of Al market space, the global market is about 5~7 trillion. In the past 1-2 years, the market space has mainly focused on AI-generated content as a business monetization point. In the next 3~5 years, the larger market space will extend to marketing promotion, data synthesis (as a way to complete data), virtual companionship, game strategy generation, game character generation, etc.

Xia Fei also pointed out that many companies have entered the track of AIGC, but AIGC not only needs technological breakthroughs, but also a systematic project, from the underlying computing power resource requirements, to the above integration framework layer and AI platform layer need to have a certain accumulation, can not blindly follow the trend.

The big model competition is a war between giants, and Baidu Wenxin Yiyan, Aliyun Tongyi Qianwen, Tencent Mixed Yuan Big Model, Huawei Pangu Big Model, etc. have been born in China. Industry insiders believe that there are only 5 companies in China that can train 20,000 GPU cards, and only 3 to 4 can make general-purpose large models.

And Huawei is an important seed player in this competition. At the event site that day, Xia Fei also mentioned that the Pangu model will be upgraded in July.

Xia Fei introduced that Huawei Pangu Big Model has released CV large models, NLP large models, scientific computing large models, etc., Huawei has been researching in the field of large models for many years, and has a multi-modal Chinese database, combining discriminant models and generative models, which can flexibly support downstream tasks, such as text and life diagrams, text-oriented image completion, and image editing.

At the event, Xia Fei also showed that with the support of Huawei's Pangu model, AIGC has completed internal applications such as text generation, image generation, and video editing, and AIGC cooperates with mobile phone manufacturers to automatically generate mobile phone screensavers, and cooperates with brand retailers to generate posters and advertising images for different products.

Tencent Cloud lays out a large model in the industry

Tang Daosheng: Accelerate the innovation and exploration of large models in industrial scenarios

ChatGPT has triggered a global "big model" boom, and the artificial intelligence industry has entered a new stage of development. How to grasp the core competitiveness of the "next decade" and build advantages in the new inflection point has become a new proposition for enterprises. On June 19, Tencent Cloud held the Industry Big Model and Intelligent Application Technology Summit at the National Science and Technology Communication Center, announcing for the first time the R&D progress of Tencent Cloud's industry big model, relying on the Tencent Cloud TI platform to build a selected store for industry large models, and exploring feasible paths for large model application practices.

Ecological co-construction is AI development

Valid path

At the meeting, Tencent Cloud and 22 customers officially launched the cooperation on the co-construction of large models in the industry, and jointly launched the "Tencent Cloud Industry Big Model Ecological Plan" with 17 ecological partners, committed to jointly promoting the innovation and implementation of large models in the industrial field. Based on Tencent's HCC high-performance computing cluster and large-model capabilities, Tencent Cloud has provided more than 50 large-model industry solutions for more than 10 industries, including media, cultural tourism, government affairs, and finance.

Tang Daosheng, Senior Executive Vice President of Tencent Group and CEO of Cloud and Smart Industry Business Group, said that ecological co-construction is an effective path for AI development, and Tencent will adhere to ecological openness, provide high-quality model services for enterprises, and support customer multi-model training tasks to accelerate the innovation and exploration of large models in industrial scenarios.

At present, the general big language model has certain limitations in coping with the landing of industrial scenarios. First of all, the training data of the general large model mainly comes from public datasets or network data, and the knowledge of specialized domain knowledge for specific industries is limited. In addition, the training of general-purpose large language models requires a lot of computing resources and a long training cycle, which can be expensive and time-consuming for enterprises. At the same time, safety and compliance are necessary considerations.

According to the requirements of your own business scenario

Customized model services of different specifications

For enterprises, choosing to customize a large model may be the best answer to solve these problems. In response to the pain points and needs of the above-mentioned industry applications, Tencent Cloud relies on the Tencent Cloud TI platform to build a select store for industry large models, providing one-stop industry large model solutions covering model pre-training, model fine tuning, and intelligent application development. On the basis of the built-in industry large model of the TI platform, enterprises can quickly generate their own exclusive models by adding their own unique scenario data. At the same time, model services with different parameters and specifications can also be "tailored and customized on demand" according to the needs of its own business scenarios.

While accelerating the exploration of industry scenarios, Tencent Cloud's industry big model capability has been first applied in many leading SaaS products such as Tencent Qidian, Tencent Meeting, and Tencent Cloud AI Code Assistant.

Tang Daosheng said: "Today, we are once again standing at the starting point of the digital technology revolution, the big model is only the beginning, and the integration of AI and industry will bloom into the future of creativity." ”

Written by: Nandu Bay Finance Agency reporter Cheng Yang photo provided by the interviewee