The conversation about AI alignment is more critical than ever. With DeepSeek revolutionizing the tech world, the question of aligning AI models to human values and preferences takes center stage.
DeepSeek: A Paradigm Shift in AI
DeepSeek’s recent breakthroughs challenge long-standing assumptions in AI development:
- Efficiency Over Compute: Until now, it was believed that achieving state-of-the-art AI required massive computational resources, leading to high energy and water consumption. DeepSeek V3 has shattered this notion by delivering top-tier quality using just 5% of the GPUs required to train GPT-4.
- Minimal Human-Labeled Data: Traditionally, human-labeled data has been considered essential for model quality. DeepSeek R1 leverages an intermediate model (R1-Zero) to generate the necessary cold-start data, minimizing the need for extensive human annotation. Through large-scale, reasoning-oriented reinforcement learning, the model achieves remarkable accuracy and efficiency.
- Open-Source and Transparent: Unlike many cutting-edge models, DeepSeek is open-source with a permissive MIT license, offering complete transparency into its reasoning steps.
Disclaimer: there are many open questions about the data and training parameters used, and it is possible that existing LLMs were used to bootstrap its capabilities.
AI Alignment: A Geopolitical Issue
From a Western perspective, DeepSeek V3 and R1 appear to be censored. From a technical standpoint, however, they are simply aligned—to Chinese values and the Chinese government’s belief system.
All LLMs are aligned to somebody’s values.
Every large language model (LLM) is inherently shaped by the cultural values and societal norms of its country of origin, government policies, and corporate priorities. The alignment process—often referred to as preference fine-tuning—determines how an AI system responds, what it prioritizes, and what it filters out. More specifically, these models are aligned to the preferences of the humans that provided the labeled data to finetune these models, or in the case of DeepSeek, the preferences encoded in the synthetic data that was generated and used to finetune their R1 model.
This is why AI development is not just a technological competition—it is a geopolitical race. The models that power our businesses, governments, and societies are not neutral; they carry the imprint of the institutions that develop them.
Taking Control of Your AI Alignment
For businesses and governments, the key takeaway is this: you need to control your AI’s alignment.
No matter what LLMs or ML models power your applications—today or in the future—you must ensure that they are aligned to your values, your governance frameworks, and your objectives. Otherwise, you risk deploying AI systems influenced by external priorities, whether from another company, country, or regulatory body.