Lenovo Lingtuo: Empowering Business Growth in the AI Era

In this rapidly evolving digital age, one pressing question lingers among businesses and organizations: what constitutes their most distinctive competitive edge? The unmistakable answer is dataAs generative AI technologies advance at an unprecedented pace, the development of new productive forces is becoming a universal consensus within the industryBusinesses increasingly recognize that data serves as the foundation for all operations, being pivotal for enterprises to ride the wave of AI, achieve qualitative shifts in productivity, and forge unique competitive advantages.

Indeed, the rise of generative AI has accentuated the significance and value of data while simultaneously ushering in a range of novel storage requirements and challengesConsequently, enterprises are under pressure to establish robust digital frameworks through intelligent data infrastructures that continuously supply the ‘fuel’ necessary for AI training and inference

By doing so, they can fully leverage AI applications in their digital transformation journeys.

Among a myriad of vendors, Lenovo is carving out a strong niche, capitalizing on the synergy between advanced technology and local research and development (R&D). Through a series of innovative hardware and software solutions, Lenovo is assisting businesses in China to build intelligent data foundations, ensuring they can embrace the surge of AI innovationsAs Lin Yousheng, Senior Director of Product Management and Marketing at Lenovo, succinctly puts it: "The core of new productive forces is artificial intelligenceThe next three years will represent a crucial window for the integration of AI into business, leading to transformative changes." He adds, "AI needs to engage with data, making data the decisive factor for the applications of AI."

For AI readiness, the necessity for substantial groundwork cannot be overstated.

Computing power is valuable, but data storage capabilities are invaluable

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As industries universally adopt AI technologies, enterprises are realizing that generative AI represents a complex engineering challenge characterized by the management of large-scale, high-quality data and its efficient processingThe quality of data is inherently linked to the data infrastructure, which must meet the stringent requirements for storage, training, analysis, and inference through performance, capacity, scalability, and stability.

Consider the ongoing transition towards multimodal AI models; multimodal data varies greatly in scale and form, requiring significant capacity and processing capabilitiesFurthermore, as models grow in size, so do the clusters necessary to train them—meaning training processes generate vast and frequent checkpoints that exponentially challenge the reliability of data storageAdditionally, as AI models become integrated with business contexts, they generate substantial inference demand, leading to massive parallel processing and complicated input/output operations.

Thus, data infrastructure must display exceptional "hard skills," particularly in performance to meet the rigorous requirements of the entire AI application lifecycle.

Lenovo is setting new standards for data infrastructure in the AI era

Take, for example, the newly introduced NetApp AFF A series, which includes models like A70, A90, and A1KThese all-flash unified storage systems can scale up to 64 controllers, providing 40 million IOPS and a staggering 1 TB/s data throughput capability while boasting validated data availability of 99.9999%.

Lin emphasizes that high performance is a must-have capability for advanced data storage solutions and one of the core elements of intelligent data infrastructureThe NetApp AFF A series employs a brand-new bus architecture design and features chip-level hardware acceleration to ensure exceptional performance across any data type and under even the most demanding workloads.

Moreover, as technologies like generative AI, multi-cloud, and big data analytics permeate the business landscape, enterprises confront a far more intricate data environment than ever beforeBeyond the essential "hard skills" related to performance, the demand for robust, extensive data management software capabilities is becoming ever more critical

If performance elevates the minimum standards for data infrastructure, then the soft skills associated with effective data management have the potential to significantly enhance its upper limits.

Simplifying complexity hinges upon harnessing soft power.

The modern business landscape is fraught with the challenges posed by the complexities of data environmentsFor instance, generative AI encompasses various stages including data acquisition, pre-processing, model training, and application deployment, each of these stages features unique data types and processing requirements, necessitating significant collaboration and oversightIf each stage were to rely on separate data storage systems, it would severely hamper the efficiency of data mobility and collaboration, potentially becoming a bottleneck in the overall application of generative AI.

The fast-paced evolution of AI technologies has driven the urgent development of collaborative cloud scenarios, normalizing the flow and cooperation of data across cloud, edge, and terminal environments

Businesses must build formidable data management capabilities to facilitate efficient data flow and management within multi-cloud settings.

Additionally, the rise of ransomware has underscored the rising incidence of cyberattacks, with data associated with generative AI models becoming prime targetsThe reliance of vertical industries on proprietary data for model training heightens the risks; if attackers breach this sensitive data, the consequences for enterprises could be catastrophic.

The necessity for a unified storage platform that simplifies data management and supports comprehensive data management throughout the AI lifecycle, as well as effective data protection, is becoming an essential condition for the growth of enterprises.

As a pioneer in unified data storage solutions, Lenovo’s parent company, NetApp, has garnered over three decades of experience in the data storage sector

Its ONTAP software platform has long been recognized for its leadership in data management, collaboration, and multi-cloud integrationWith ongoing enhancements to the ONTAP 9.15 software platform, Lenovo hopes to infuse even more powerful capabilities into the data infrastructures of Chinese enterprises.

Firstly, as a proven unified storage platform, ONTAP naturally supports compatibility across NAS, object storage, block storage, and big data protocolsA single platform can efficiently handle the full-cycle data storage and management needs for AI, helping businesses eliminate data silos and significantly accelerating the implementation of AI applications.

Second, on the offensive against complexity, ONTAP’s pioneering Data Fabric ideology facilitates true data fluidity, collaboration, and management, effectively transforming convoluted data environments into streamlined operational frameworks that drive business in a data-driven manner.

Third, ONTAP possesses robust data protection capabilities, having withstood the tests of various strict business scenarios equipped with features like SnapMirror and FlexCache

Moreover, embedded machine learning models enhance its ability to autonomously detect ransomware, achieving over 99% accuracy in identifying ransomware attacks, thereby fortifying data protection within the infrastructure.

“Simplifying data management and reliable data security are fundamental components of intelligent data infrastructure,” Lin states.

Crafting ecological capabilities for the AI age is paramount.

McKinsey forecasts that by 2030, generative AI will potentially contribute $7 trillion to the global economy, with China, as a hub for AI development and application, expected to capture one-third of the total benefits through strategic investments.

There's no denying that China’s emphasis on artificial intelligence and new productive forces will significantly catalyze the digital transformation and upgrading of vertical industries

Simultaneously, as generative AI, big data analytics, and multi-cloud technologies rapidly become integrated into business scenarios, the importance of ecological systems takes on heightened significance.

Lenovo is keenly focused on building future-oriented ecosystems centered around new productive forcesFor instance, the complexity inherent in generative AI poses high deployment and development hurdles in vertical industries, creating substantial barriers to its widespread adoptionAccording to a report by Gartner named “Top Storage Recommendations to Support Generative AI,” it is predicted that by 2028, three-quarters of organizations possessing generative AI training data will implement a single storage platform, thus facilitating easier integration and deployment across vertical industries.

In light of this, Lenovo’s parent companies have proactively recognized the pivotal role of ecological collaboration in promoting the practical application and proliferation of generative AI

To this end, they have launched the “NetApp AIPod with Lenovo” solution, featuring Lenovo’s high-performance ThinkSystem servers equipped with NVIDIA GPUs, alongside NVIDIA Spectrum-X networks and NetApp AFF storageThis convergence infrastructure is specifically designed for generative AI retrieval enhancement and inference use cases.

“AIPod serves as a reference architecture, allowing users the flexibility to select appropriate storage based on their specific applications,” Lin explained.

Furthermore, Lenovo is also investing in vertical industry solutions, collaborating with partners to create readily deployable industry solutions tailored to the needs of sectors such as healthcare, manufacturing, transportation, and finance.

“Lenovo’s greatest strength lies in our combination of local R&D and advanced technology, enabling us to offer a robust local support framework backed by industry-leading technological capabilities