If one were to encapsulate the current landscape of the AI large model sector in a succinct phrase, "entering the deep-water zone" would undoubtedly be the most apt. Previously, the unveiling of AI large models by various entities was often perceived as a means to garner attention. Consequently, at the initial launch of an AI large model, it was straightforward to pinpoint the entity behind it. However, as the AI large model industry progresses into this more challenging phase, particularly with external focus shifting towards the intrinsic capabilities of these models, an increasing number of entities are opting for anonymous releases.

The process of anonymous release, followed by community blind testing, and culminating in official acknowledgment, has emerged as a standardized approach for entities to validate the prowess of their large models. From the erstwhile popular baseball videos to the subsequent Happy Horse videos, and now the recent Space Rabbit, all have adhered to this trajectory. As AI large model entities undergo a profound shift in their release strategies, we not only witness the continuous enhancement of AI large model capabilities but also sense that the current AI large model sector has transcended being a mere platform for technological showcase. It has now evolved into a rigorous arena where capabilities speak volumes, and genuine strength compels users to pay.

Through this novel release pathway of AI large models, we observe the maturation of these models and also discern emerging development trends within the sector. So, what is the present developmental state of the AI large model sector, and what considerations do entities harbor for the future?

AI Large Models: No Longer Just Tales for the Capital Market

Recalling the era of rapid releases of AI large models, we notice a conspicuous phenomenon: during that period, capital market investment in AI large models was also fervent. For entities capable of iterating and upgrading their AI large models, continuous releases could attract capital market attention and encourage further investment from capital institutions. Hence, at that juncture, AI large models were often narratives spun for the capital market.

As the capital market's involvement in AI large models begins to wane, especially as the entire AI large model industry transitions from a relatively niche existence to a more mature one, relying solely on narratives to captivate the capital market is no longer adequate. Consequently, an increasing number of entities are commencing to deeply integrate AI large models with specific businesses, industries, and scenarios. Whether in content creation, commercial, or industrial domains, the presence of AI large models is palpable.

As the release of AI large models leans towards anonymity, we must acknowledge that AI large models are no longer just narratives for the capital market or mere parameter comparisons. Instead, they have morphed into entities capable of genuinely moving users and instigating profound changes in real-world business environments. In the future, only by truly garnering user acceptance and forging deep connections with real-world scenarios can new developments be sustained in the deep-water zone of AI large models.

AI Large Models: No Longer Just the Playground of a Select Few

We are all aware that when large models first emerged, AI large models were primarily the purview of early adopters or leading entities. At that time, only those who took the lead in strategic布局 (layout) or the top players could truly release their own AI large models. As the AI large model sector gradually matures, especially as more and more entities begin to view AI large models as a pivotal part of their strategy, AI large models are no longer just the playground of a select few but have become standard equipment for nearly all entities.

Consequently, AI large models have evolved from a singular standout to a vibrant ecosystem. When AI large models become standard for almost all entities, what genuinely tests these entities is no longer just whether they possess an AI large model but whether they can truly leverage it to accomplish tasks, resolve real-world problems, and bring about iteration and upgrades to industries.

At this juncture, what genuinely tests entities is how to garner user favor as much as possible in the era of stock AI large models. This essentially tests the entities' own capabilities and the depth and breadth of their implementation in real-world business scenarios. How to generate effectiveness with AI large models and achieve industrial upgrades will become inevitable issues for every entity to address. Transitioning from mere technological showcase to in-depth problem-solving will become a pivotal issue for AI large model entities to tackle in the next stage.

AI Large Models: No Longer Isolated Entities

In the past, AI large models were predominantly confined to specific vertical scenarios and domains, existing as isolated entities. As the AI large model industry advances into the deep-water zone, large models are now shifting from early "parameter competition" to "implementation competition." Moreover, AI large models are now present in nearly every scenario, alongside general-purpose AI large model entities. Establishing connections between vertical AI large models across different scenarios and industries and achieving integration between vertical and general-purpose AI large models have become crucial for maximizing the effectiveness of AI large models.

Breaking down barriers between AI large models and fostering collaboration among them has become key to unleashing their full potential. Therefore, at this stage, AI large model entities are no longer just competing on parameters or simply showcasing technology but are focusing more on collaboration and industrial ecosystems.

For AI large model entities, breaking free from the cycle of competing solely on quantity and truly achieving collaboration between different models, especially enabling AI large models to bring about profound industrial changes, will be the key to success in the deep-water zone of AI large models. From this vantage point, AI large models are no longer just about showcasing technology but are now more about collaboration and ecosystems.

Conclusion

As the release pathway of AI large models shifts from early high-profile launches to current anonymous releases, we witness the reality that competition in the AI large model sector has entered the deep-water zone. In this zone, finding truly suitable development paths for entities and ushering in a new cycle for AI large model development may be the crucial topics that every AI large model entity must contemplate. The new cycle for AI large models has arrived. Are you ready?