In a groundbreaking moment for the artificial intelligence landscape, DeepSeek has emerged as a seismic force that has fundamentally altered the dynamics of the AI model arenaThis revolutionary application, known as DeepSeek-R1, has captured the global spotlight, reaching an astounding user base of over 100 million within just six days of its launchIts peak daily active user count surged to 71.8 million, surpassing even the momentum of established giants like ChatGPT, establishing itself as the fastest-growing AI application worldwide.
Following DeepSeek's meteoric rise, a series of remarkable reactions have unfolded, sparking a transformation in the playbook of the AI model sectorThis development is particularly significant as it marks a decisive shift away from the relentless arms race of computational power that has dominated the industry for the past three yearsInstead, a new era encompassing a revolution in efficiency and the restructuring of ecosystems has taken center stage.
DeepSeek fundamentally redefines the competitive landscape by putting an abrupt halt to the cash-burning race fueled by previous technologiesThis shift is evident in both the channels through which AI services are marketed and the overarching trends shaping the industryWhat has been referred to as an "industrial earthquake" driven by technological innovation signifies the advent of a "post-burn capital age" in AI, where technical efficacy triumphs over mere capital investment, and collaboration usurps the notion of solitary endeavors.
The channel dynamics are experiencing a transformation, with a noticeable retreat from previously aggressive ad spending strategiesIt's essential to recognize that the AI model landscape, despite its exponential growth, had been characterized by a lack of substantive change in its underlying business models and competitive strategiesFor years, many players involved in the so-called "model battle" relied on heavy capital investments and massive advertising to attract users, mirroring strategies seen in other internet sectors.
Take, for instance, the instance of Kimi, a product under the banner of the company known as "Monthly Dark Side." Its shocking spending strategies only serve to illustrate the old ways of doing business
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Reports indicate that Kimi had been investing upwards of ten million yuan monthly since March of the previous year, with a staggering ad budget peaking at 220 million yuan in OctoberAt one point, Kimi even made headlines for burning through 100 million yuan in just 20 days, showcasing not only the lengths companies would go to for user acquisition but also the precariousness of such tactics.
Yet, despite the aggressive nature of this spending, critiques of Kimi's methods emerged from within the sectorIndustry veterans like Li Yanhong (also known as Robin Li) expressed reservations, emphasizing that the pursuit of Artificial General Intelligence (AGI) requires a more measured approach that doesn't necessitate the kind of reckless promotion exemplified by Kimi.
As DeepSeek disrupted this entrenched pattern, it provided an alternative that allowed for high performance at remarkably low costs, thereby challenging the long-held competitive logic that leaned on heavy financial investmentsIn the realm of AI models, numerous enterprises adhered to a closed-source model inherently built on the principles of "technical monopolization and paid subscriptions." However, DeepSeek's open-source approach dismantled this business cycle, ushering in a new strategy that focused on accessibility without compromising quality.
Notably, DeepSeek's API is priced at just one-tenth of the market average, with the added capability for private deployment, allowing businesses to customize AI services without reliance on tech giantsThis factor alone propelled DeepSeek beyond numerous closed-source competitors, representing a dynamic shift in the industry akin to a catfish stirring up a stagnant pond, referred to as a victory for open-source modelsThe result is a self-sustaining growth loop formed by an expanding base of regular users and developers.
This growth narrative also marks the end of traditional user acquisition pathsCompetitors of DeepSeek, who once heavily invested in extensive advertising, are now rethinking their strategies
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Reports have emerged indicating that Monthly Dark Side has made substantial cuts to its ad spending, ceasing various Android promotions and halting collaborations with third-party advertising platformsThis shift reflects broader strategic adjustments influenced by external factors.
The recent weeks marked a pivotal transition in the AI model ecosystem, with many tech giants, smartphone manufacturers, telecom operators, and smaller software firms eagerly embracing DeepSeekCompanies that lagged behind in this transition found themselves possibly sliding into obsolescence, underscoring a race against time for others to remain relevant.
Take the case of Honor, a smartphone maker that recently announced its integration with DeepSeek, becoming the first Android manufacturer to do soThis announcement was not just strategic but framed as a significant milestone, further solidifying the urgency for others to adopt similar integrationsConcurrently, the Ministry of Industry and Information Technology confirmed that three major telecommunications companies are now fully integrating DeepSeek's open-source model, leading to an uptick in their stock prices.
As tech giants like Tencent, Alibaba, and Baidu responded promptly by welcoming collaboration with DeepSeek, they recognized the potential for synergies rather than competitive isolationFor example, Tencent's WeChat has initiated grey-scale testing for DeepSeek's capabilities, potentially directing its colossal user base towards this new paradigm and fundamentally transforming the interaction within the AI space.
While these powerful companies previously held ambitions to establish their dominance with proprietary AI models, the emergence of DeepSeek has compelled them to pivot towards greater ecosystem collaborationThis cooperation not only saves on exorbitant development costs but also opens the door to expanded market presence, reducing the fervor for standalone, costly self-developed solutions.
Looking ahead, it seems likely that as organizations adopt these new strategies, their investments in the AI model landscape will wane, leading to a cooling-off period in the capital-intensive race that once characterized the sector
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