The DeepSeek Disruption: How Affordable AI is Changing the Game and Why Data Security is More Critical Than Ever
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Technological evolutions often follow a familiar pattern – what was once prohibitively expensive and exclusive eventually becomes widely accessible and transformative. We’ve seen this with the rise of cloud computing, where companies once required massive on-premises data centers but can now leverage flexible, scalable cloud solutions at a fraction of the cost. Similarly, the mobile revolution transitioned computing from stationary desktops to powerful, pocket-sized devices accessible to billions.
A strong parallel can also be drawn to the early days of open-source software. Initially, enterprise software was dominated by proprietary systems from companies like Microsoft and Oracle. Then, Linux and open-source databases like MySQL disrupted the market, lowering costs and accelerating innovation. Today, the AI industry is experiencing a similar shift.
For years, training and deploying Large Language Models (LLMs) was reserved for those who could raise a lot of cash very quickly – often supported by the largest tech companies – with OpenAI, Anthropic, and others spending over $100 million just on compute resources. These costs required massive data centers with thousands of $40,000 GPUs.
DeepSeek, however, has shattered this model by proving that state-of-the-art LLMs can be trained just as effectively at a fraction of the cost. This shift is democratizing AI development, allowing businesses of all sizes to access powerful AI tools that were previously out of reach.
Yet while this newfound affordability is great for innovation and accessibility, it doesn’t eliminate the foundational requirements of data security, governance, and quality. Businesses eager to use AI must ensure they have strong data estate management to drive success.
How DeepSeek Redefined AI Efficiency
DeepSeek’s cost-cutting isn’t just theoretical – it’s built on smart engineering and rethinking old assumptions. Here’s how they did it:
- Precision Optimization: Traditional AI models work by storing every number with 32 decimal places, even when 8 would suffice. DeepSeek cut unnecessary precision, reducing memory usage by 75% without sacrificing accuracy.
- Multi-Token Processing: Most models read word by word, but DeepSeek processes full phrases at once. This doubles processing speed while keeping 90% accuracy.
- Mixture of Experts (MoE) Model: Instead of keeping all 1.8 trillion parameters active, DeepSeek’s model selectively activates only 37 billion at a time—drastically reducing compute needs.
- Efficient Hardware Usage: Instead of relying on massive data centers with AI-specific hardware, DeepSeek’s models run on commodity gaming GPUs, reducing infrastructure costs and making AI more accessible.
- Open-Source Transparency: While DeepSeek’s models are open-source, it's important to note that the West – in addition to closed LLMs from OpenAI and others – also has popular open-source LLMs, including Llama (Meta), Mistral AI, and Abacus AI. These efforts further democratize AI development and expand access to innovative capabilities. In fact, DeepSeek is built on top of these existing open-source models.
The impact? Companies no longer need billion-dollar budgets to train and deploy powerful AI models. This democratization of AI development is a game-changer for businesses worldwide.
Why the Tech World is on Edge
DeepSeek’s efficiency threatens the status quo in several ways:
- Disrupting Established AI Leaders: OpenAI, Anthropic, and other Western AI leaders are now facing real competition. If high-quality AI can be built for a fraction of the cost, their first-mover advantage could diminish.
- Democratizing AI Development: The days of AI being monopolized by large corporations are numbered. More companies, researchers, and even startups can now experiment with and deploy LLMs.
- Cost Pressures on AI Business Models: Companies charging premium prices for AI services may struggle to justify high costs as cheaper alternatives emerge.
- Geopolitical Implications: DeepSeek’s rapid rise signals China’s growing influence in AI, increasing competition on a global scale.
The accessibility of commercial and open-source AI models like DeepSeek, Llama, and Mistral is a significant step forward, but businesses that want to fully realize AI’s potential must take the next step: customization.
While these models provide a strong foundation, true value emerges when companies refine and adapt them with their proprietary data to address specific industry and business needs. This refinement modeling, where organizations fine-tune existing AI with their own unique datasets, is where AI becomes a true competitive differentiator.
However, this also raises critical questions about data estate management, governance, and security. Without the right strategy in place, businesses risk exposing sensitive information, mismanaging AI outputs, or failing to comply with regulatory requirements. This is where AvePoint provides essential support—ensuring that companies can implement AI securely while protecting their proprietary data.
Building a Secure and Scalable AI Foundation
The foundation of any successful AI deployment isn’t just the model itself – it’s the data governance and security strategy behind it. Companies looking to integrate AI effectively must address the following areas:
- Data Classification and Management: Organizations must ensure they have visibility into their data estate, categorizing sensitive information and applying the right access controls to prevent misuse.
- Security and Compliance Measures: AI models must be aligned with industry regulations such as GDPR, CCPA, and emerging AI governance frameworks. Strong encryption, role-based access control, and regular audits are critical.
- Ensuring AI Trustworthiness: AI outputs are only as dependable as the data businesses train them on. Businesses must ensure that AI systems are free from biases, grounded in accurate data, and regularly monitored for reliability.
- Scalability and Interoperability: AI is not a standalone solution – it must integrate seamlessly with existing enterprise workflows and data management systems. Companies must ensure their AI platforms can scale and adapt as business needs evolve.
How Businesses Can Leverage AI Securely
If businesses want to take advantage of DeepSeek’s AI breakthroughs, they need a solid foundation of data management. Here are the key steps to ensure AI success:
- Assess AI Readiness: Evaluate your current data architecture to ensure it supports AI deployment securely.
- Implement Governance Best Practices: Establish clear policies on data access, storage, and usage.
- Prioritize Security and Compliance: Ensure AI models comply with industry regulations and data protection standards.
- Conduct Vendor Due Diligence: Evaluate AI vendors based on their technological expertise, data handling policies, compliance with regulations, and security protocols.
- Leverage Open-Source AI Cautiously: While open-source AI is powerful, businesses may fear the code is unsafe. The beauty of open source is you can review the source code yourself. Subsequently, businesses must assess risks, including data leakage, security vulnerabilities, and biases.
- Safeguard Proprietary Data: Don't use free services on the web as your proprietary data may be used for training and show up in knowledgebase of the next version.
AvePoint: Your Partner for AI Success
In the age of AI, businesses face mounting challenges, including explosive data growth, increasingly sophisticated cybersecurity threats, complex regulatory environments, and the pressing need for automation. Successfully using AI requires a trusted partner who can provide security, governance, and resilience – this is where AvePoint excels.
AvePoint helps organizations maximize the potential of AI while maintaining compliance and security. Our expertise in data security, governance, and resilience enables businesses to unlock the full potential of their data, accelerate digital transformation, and securely integrate AI into their workflows.
The AvePoint Confidence Platform integrates innovative technologies with robust data management strategies, ensuring businesses are positioned for success in the AI-driven era. Our platform strategy is designed to support organizations at every stage of their AI journey and address the needs of their vast, dispersed data estates, focusing on:
- Interoperability: Seamlessly integrating AI capabilities with existing enterprise solutions.
- Data Protection: Ensuring data is backed up, securely stored, and easily recoverable.
- Data Governance: Implementing clear data access policies and compliance frameworks.
- Data Archiving and Disposal: Managing redundant, obsolete, or trivial data to optimize AI performance while reducing storage costs.
Many software companies focus on just one aspect of data management, requiring businesses to manage multiple vendors. AvePoint offers a holistic, all-in-one approach, streamlining AI deployment and reducing complexity. Our AI deployment strategy integrates data security, governance, and business continuity into an easy-to-deploy platform, making us the preferred partner for enterprises worldwide.
At AvePoint, we go beyond traditional data security insufficient to address business’ digital transformations. Our Beyond Secure approach ensures organizations don’t just protect data but also optimize it to fuel AI-driven innovation. By addressing these inadequacies, we empower companies to focus on transformation, efficiency, and competitive advantage without worrying about data risks.
AI presents a massive opportunity, but success depends on a strong, secure data foundation. Let AvePoint help you establish the governance, protection, and resilience needed to unlock AI’s full potential.
Final Thoughts
DeepSeek’s breakthroughs mark a pivotal moment in AI’s evolution. Affordable, high-performance AI is now within reach for businesses of all sizes. However, simply having access to powerful AI isn’t enough – companies must ensure they have the right data management, security, and governance strategies in place.
Those who get ahead of these challenges today will be the ones leading the AI-driven future. Learn how AvePoint can help your business navigate AI adoption securely.
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John Peluso is AvePoint’s Chief Technology Officer. In this role, he aligns the Company’s technology and product roadmaps to grow AvePoint’s market share, and accelerate the ideation, development, and launch of innovative software products tailored to anticipate customer needs. Prior to this role, John held multiple leadership roles over his 13-year tenure at AvePoint, including Chief Product Officer, SVP of Product Strategy, Director of Education, and Chief Technology Officer, Public Sector.
Before joining AvePoint, John served in a variety of technology and business roles at New Horizons Northeast and New Horizons of Central and Northern NJ. He earned his undergraduate degree from The New School.