Navigating DeepSeek’s deep sea in a rapidly evolving AI landscape

The AI world just got a serious shake up. DeepSeek, a Chinese based AI startup, has stormed onto the scene with its R1 model – a rival to OpenAI’s ChatGPT, but at a fraction of the cost and computing power. 

‍What is DeepSeek?‍

DeepSeek's R1 model is based on a new radically efficient approach to training AI. Using a combination of novel optimizations, the model is able to activate only the necessary computing resources for each task. This drastically reduces the time to train LLMs, and the compute resources required for inference. To put it in perspective: DeepSeek claims it trained R1 on just 2,000 Nvidia H800 GPUs over 55 days for $5.6 million—a stark contrast to U.S. competitors pouring upwards of billions of dollars into training similar models.

‍Why it’s a damn big deal‍

The efficiency and performance of R1 have sent shockwaves through the industry, so much so that US tech stocks shed over $1 trillion in market capitalization. This shift signals the start of the era of cost effective AI models, where foundational model development is accessible to every organization, and cost effective & performant AI can be embedded in every interaction. I personally think this increase in accessibility and affordability will drive overall increases in AI infrastructure demand, making the market reaction premature.

‍Enterprise opportunities vs. risks‍

For enterprises, DeepSeek’s rise presents a double-edged sword. Its low cost and high quality are driving rapid consumer adoption, but if that adoption is within your own workforce, it comes with some major concerns:

1. Data security risks: As a China-based model, there are concerns about data sovereignty and how information will be processed. How is your data being used? Where is it stored? What third parties will it be shared with?‍

2. Cybersecurity vulnerabilities: DeepSeek has already experienced multiple cybersecurity incidents – a stark reminder that in the fast paced AI industry, the latest and greatest mathematical innovations may not always come along with the operational security and platform maturity enterprises required.

3. Compliance challenges: Public LLMs handling enterprise data pose significant regulatory risks, especially in finance, healthcare, and government sectors. These risks have been present with public LLMs since day one. And while the risks have become so well understood that the clickbait headlines have faded, the risks have actually continued to grow.

‍Private model efficiencies: an open-source edge ‍

DeepSeek's open-source approach offers enterprises the opportunity to leverage efficient self-hosted solutions. However like all private GenAI models, to make it a usable and secure solution for an enterprise workforce requires significant investment in development and LLM expertise to at a minimum:

• Build a user interface
• Implement access controls for both foundational and tuned models
• Create policy-based guardrails
• Develop and maintain caching layers
• Integrate with enterprise data sources with role-based access controls

Staying agile in an arms race

AI innovation is not slowing down. The pace is relentless. Enterprises can’t afford to rebuild their LLM infrastructure and applications with every new model release. The key? A flexible control plane that can integrate with any model, allowing companies to focus on their own breakthroughs, not on endless AI plumbing.

How enterprises can govern GenAI adoption 

1. Mitigate risks: Implement comprehensive security measures to protect against data leaks
2. Set guardrails: Deploy policy frameworks to govern AI use 
3. Leverage the Cloud: Consider secure private instances (such as AWS Bedrock).
4. Secure data access: Ensure any RAG architecture has strong role-based access controls, and only leverage enterprise data with open-source models when they are hosted in your own trusted and secure environments.
5. Apply usage controls: Use role-based access to prevent misuse

The SurePath AI advantage‍

This is where SurePath AI comes in. Our platform helps enterprises securely adopt and govern GenAI with

• Real time visibility and control over GenAI traffic
• Centralized policy management
• Sensitive data detection and redaction
• Secure integration with enterprise data sources
• Comprehensive audit trails and analytics

With SurePath AI, you get the benefits of cutting-edge GenAI models without sacrificing security, compliance, or control. ‍

Final takeaway: Test it, block it, or securely enable it‍

The DeepSeek revolution is here. The opportunities are massive, and so are the risks. 

While you can test DeepSeek or block it, we suggest getting on a SurePath to safely enable your workforce on their GenAI journeys.

Start your SurePath AI trial today.