Hard Krypton exclusively learned that artificial intelligence Internet of Things (AIoT) enterprise “Teslian” recently completed the D round of 2 billion yuan financing. This round of financing is led by AL Capital and Yangming Equity Investment Fund, followed by new and old shareholders such as Foton Capital, Gemdale Group, Chongke Holdings, Digital Chongqing, Nanchang Government Platform Company, Xuzhou Industry Fund, Beike Construction Group, Everbright Holdings, Sensetime Technology. Prior to this, “Teslink” also received investment support from IDG Capital, CITIC Industrial Capital, Jingdong Technology, and IFlytek.

After this round of financing, “Teslian” will further consolidate the digital intelligent infrastructure with green intelligent computer as the core, deepen the larger model open platform of “model + system”, take its own business scenario as the traction, quickly form industrialization and clustering effect, and assist partners in various industries to complete the digital intelligent transformation.

PMC-21125001000003000K “Teslian” was founded in 2015, the company based on artificial intelligence (AI) and the Internet of Things (IoT) technology integration innovation origin, focusing on building, community, park, city, double carbon five core scenes, long-term commitment to intelligent technology to drive the scene of intelligent upgrading, industrial ecological prosperity and green low-carbon landing.

In recent years, with the popularization of AI, 5G, edge computing and other technologies, the AIoT industry has ushered in explosive growth, and its application has increased significantly in all aspects of life. AIoT collects all kinds of information through various sensors, and uses AI technology to do real-time structured processing and analysis at the nearby edge or cloud, so as to realize the interconnection between devices and scenes, and build a digital world where everything is intelligent.

Public data show that the market size of the artificial intelligence Internet of Things industry chain is continuing to expand, in 2024, China’s AloT industry market size is expected to reach 1.7 trillion yuan, the market size growth rate of 17%, the next few years will continue to maintain rapid growth.

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Among them, the arrival of the AI 2.0 era represented by large models, the interconnection of large models and terminal heterogeneous devices, and the mobilization of a wider range of iot terminals through generative AI, has brought new opportunities for the development of AIoT. Ai Yu, founder and CEO of “Teslian”, pointed out that the large model is the tuyere, which is both a challenge and an opportunity for the technology enterprises represented by “Teslian”.

Different from the previous generation of AI+ iot technology, the AIoT scenario needs to face a large number of heterogeneous data, and the information is richer. At the same time, the perception and decision-making capabilities of IoT devices are also higher, requiring real-time capture of the tiny needs of individuals. Under the current wave of Large models, LLMs (Large Language Model) has limited its understanding of the world PMC-21125001000003000K to a single language mode. In order to achieve a better understanding, multi-modal data and industry Know-how integration are indispensable. By aligning large models with IoT hardware semantics, humans and machines can coexist. This is very consistent with “Teslian” has always adhered to the AIoT field as the core technology strategy.

In this context, “Teslian” innovatively proposed the landing technology strategy of “model + system” and released five major models in the field, namely AIoT grand model, park grand model, enterprise grand model, economic grand model and energy grand model. Through the deep combination of domain large model and specific scene, the problem of cross-modal data modeling is overcome with the help of scene definition system, and the domain model is gradually equipped with cross-modal capability, which is a faster path for the large-scale landing of large models in industry scenes in the short term.

Take the large model of the park field created by “Teslian” as an example. The model integrating professional scene knowledge can learn the user’s usage habits in real time and provide automated services for the user’s immediate response according to their preferences. For example, adjusting air conditioning and lighting according to spatial density, dynamic automatic capture according to participants, robot-assisted rescue, etc., embedding large models into AIoT automated management and service processes, so that the model can adapt to users, and achieve a high degree of intelligence between people, iot devices and cities.