AI is in a rapidly moving modern-day arms race as companies worldwide try to create powerful, practical, and accessible generative AI models. Competitors are generally grouped into two categories: proprietary AI models developed by tech giants with a host of resources and open-source startups with significantly less funding. Can open-source AI truly challenge big tech? How can businesses ensure security and ethical practices when data is open to so many people?

The Rise of Efficient AI Models

The norm in AI development has long been standardized by singular corporations investing enormous amounts of resources into computing power and data processing. Some of the biggest generative AI companies, like OpenAI, have historically required hundreds of millions of dollars to produce a viable product.

Instead, recent technological advancements show that AI models can achieve competitive performance with significantly fewer resources. DeepSeek R1 was trained with just 2,000 GPUs and a $5.7 million investment—a fraction of the cost of competing US tech giants.

David Bader, a professor and Director of the Institute for Data Science at New Jersey Institute of Technology, is a nationally recognized expert on high-performance computing and AI. He says, “DeepSeek’s approach demonstrates that highly capable AI models no longer require vast financial and computational resources. This shift could open the door for more innovation across industries and make AI more accessible.” 

Open-Source AI: A Double-Edged Sword

There are both advantages and disadvantages to consider when naming open-source AI as the ultimate AI-creation solution. 

Open-source AI makes development more accessible than ever. Businesses and developers who lack the resources to develop a model from scratch can turn to community-driven improvements. With open collaboration, finding bugs, redundancies, and missing features is easier when several experienced minds are working on the same project. It can also be a cost-saving option for companies looking to integrate AI without relying on expensive third-party models.

On the other hand, intellectual property may become an issue when an AI model is open-source. With many hands on deck and without a coordinated supervisor, data privacy is of increasing concern. Individuals may make unauthorized modifications or maliciously use the project.  While it may seem far from reality, autonomous AI systems have the potential to transgress ethical boundaries unintentionally or operate unpredictably. 

The Future of AI Development and Security

Predictions say that training costs will likely continue to decrease over the next five years. Cheaper AI development could lead to its adoption across industries like healthcare, finance, and customer service. Rather than hiring companies to integrate a pre-made system, existing businesses will be able to create AI that accommodates their unique needs more easily. 

There will continue to be a debate over data security when comparing proprietary versus open-source models. Open-source AI can offer complete transparency and customization, but it may also be vulnerable to internal security threats. 

Proprietary models have highly controlled access and security, but they are also limited in accessibility and have higher expenses associated with them. A hybrid AI approach could balance the benefits of openness with robust protective security measures.

Innovation With Open-Source AI Models

While developing an AI model has traditionally been exclusive to established tech giants, open-source models and lower development costs make it more accessible. While open-source development democratizes good ideas, it also introduces challenges with cyber security and ethics.

Several factors must be considered in AI development before creating a universal standard. However, open-source AI is a realistic option if companies want to create high-quality models without vast access to resources. Open-source development is far from perfect, but it’s a step in the right direction toward creating a world where developers aren’t limited by funding or location.